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The underwater sensor network (UWSN) has become the most demandable area because of its numerous advancements in the real world. Water covers over 70% of the earth's surface, and there is more important information below the water's surface. Sensor networks detect information in the water and transmit it to the base station via the sink. UWSN is made up of autonomous and independent sensor nodes. These are placed spatially in the water to gather and transmit pertinent data. However, the communication may suffer due to several challenges like 3D topology, less bandwidth, routing and power constraints. This paper reviews underwater sensor networks based on routing, localization, and fault tolerance. It also reviews and compares the recently proposed algorithms to fulfil drawbacks in existing methods. Each factor's challenges are briefly discussed and compared in this paper. Future directions for underwater sensor networks are analyzed and discussed, along with their emerging applications and challenges. [ABSTRACT FROM AUTHOR]

In Internet of Things (IoT), WSNs are crucial components because they sense, acquire data and communicate with the base station. Because IoT connects devices with scarce resources, the energy needed for communication is viewed as one of the most challenging issues facing WSN assisted IoT. Clustering techniques have the potential to conserve energy and keep network nodes running for longer periods of time. Traditional hierarchical routing protocols are based on a random probability equation for cluster head (CH) selection. Moreover, there is scope to enhance the network lifespan by improving the CH selection approach. To address this, we present the hybrid K-means ant Lion optimization approach for Energy-efficient clustering based Routing (K-LionER) scheme for WSN supported by the IoT. The proposed K-LionER focuses on prolonging the network lifespan and improving energy efficiency. The clusters in WSN under investigation are created using K-means and each CH is chosen using ant lion optimization. CHs acquire the data from cluster members and transmit the agglomerated data to the base station. K-LionER selects the CH based on routing metrics, Remnant Energy (RE), distance between the CHs and Base station (CBD) and Intra-cluster Communication Cost (ICC). A comprehensive simulation is carried out on MATLAB 2017a. K-LionER's accomplishment is contrasted with LEACH, ECFU and GADA-LEACH. The simulation's outcome reveals gains in performance in various aspects, such as alive nodes, stability period, dead nodes and network lifetime metrics. In comparison to the aforementioned routing protocols, the proposed K-LionER protocol improves the network's lifetime by 10% to 48%. [ABSTRACT FROM AUTHOR]

Reflection attacks are one of the most intimidating threats organizations face. A reflection attack is a special type of distributed denial-of-service attack that amplifies the amount of malicious traffic by using reflectors and hides the identity of the attacker. Reflection attacks are known to be one of the most common causes of service disruption in large networks. Large networks perform extensive logging of NetFlow data, and parsing this data is an advocated basis for identifying network attacks. We conduct a comprehensive analysis of NetFlow data containing 1.7 billion NetFlow records and identified reflection attacks on the network time protocol (NTP) and NetBIOS servers. We set up three regression models including the Ridge, Elastic Net and LASSO. To the best of our knowledge, there is no work that studied different regression models to understand patterns of reflection attacks in a large network. In this paper, we (a) propose an approach for identifying correlations of reflection attacks, and (b) evaluate the three regression models on real NetFlow data. Our results show that (a) reflection attacks on the NTP servers are not correlated, (b) reflection attacks on the NetBIOS servers are not correlated, (c) the traffic generated by those reflection attacks did not overwhelm the NTP and NetBIOS servers, and (d) the dwell times of reflection attacks on the NTP and NetBIOS servers are too small for predicting reflection attacks on these servers. Our work on reflection attacks identification highlights recommendations that could facilitate better handling of reflection attacks in large networks. [ABSTRACT FROM AUTHOR]

The rapid development of the digital healthcare and the electronic health records (EHR) requires smooth networking infrastructure to access data using Hypertext Transfer Protocol (HTTP)-based applications. The new HTTP/3 standard should provide performance and security improvements over HTTP/2. The goal of our work was to test the performance of HTTP/2 and HTTP/3 in the context of the EHRs. We used 45,000 test FHIR Patient resources downloaded and uploaded using 20, 50, 100 and 200 resources per Bundle, which resulted in 2251, 901, 451 and 226 HTTP GET and POST requests respectively. The first test downloading 20 resources per Bundle showed that HTTP/3 outperformed HTTP/2 in the local (mean request time 16.57 ms ± 7.2 standard deviation [SD]) and in the remote network (71.45 ms ± 43.5 SD) which is almost 3 times faster. In the 50 and 100 resources per Bundle test the HTTP/3 protocol demonstrated again more than two times gain in downloading performance for remote requests with mean request time 91.13 ms ± 34.54 SD and 88.09 ms ± 21.66 SD respectively. Furthermore, HTTP/3 outperformed HTTP/2 in the constructed clinical dataset remote transfer. In the upload tests HTTP/3 showed only a slight gain in performance merely in the remote network. The HTTP/3 protocol is a relatively new development and a major improvement for the worldwide web. This new technology is still missing in the digital health and EHRs. Its use could offer a major performance gain in situations where data is gathered from multiple remote locations. [ABSTRACT FROM AUTHOR]

Blockchain technology has been increasingly integrated into various fields of economic and social development. However, scalability issues such as low broadcast efficiency, high communication overhead, and high redundant transmission rate have greatly limited the large-scale application of blockchain. This paper proposes a new scalability-enhanced Kademlia network protocol (SEKad), which optimizes blockchain network transmission in terms of both network topology and communication broadcast mechanism, provides a new approach to solving the scalability problem from the network layer. In SEKad protocol, firstly, SEKad employs a method that aligns the physical topology with the network topology for node clustering. This strategy groups neighboring nodes into clusters, streamlining network complexity and reducing network diameter. Secondly, SEKad presents a cluster-adaptable network topology based on Kademlia (Kad-CA). Kad-CA improves the rationality and efficiency of per-hop routing, optimizing the construction of K buckets and thus enhancing overall network efficiency. Finally, within the network transmission model, SEKad devise the smallest sub-tree broadcasting mechanism and the minimum redundant transmission mechanism for Kad-CA. These mechanisms work to reduce the redundant transmission rate, and enhance broadcasting efficiency. In order to evaluate the performance of SEKad, we built an experimental platform and conducted evaluations. The experimental results show that SEKad has better network scalability and stability, the network diameter size can be reduced by 27% and the redundant transmission rate can be reduced by 30%. [ABSTRACT FROM AUTHOR]

With the rapid convergence of the Internet of Things (IoT) and command and control communication networks, there is a swift surge in computation-intensive applications and heterogenous devices. Building an edge computing network near the protocol gateway not only facilitates network protocol conversion, but also alleviates computational load on the gateway. Nevertheless, traditional protocol gateways necessitate the inclusion of conversion methods for all communication protocols in the network for data interoperability with other devices. Consequently, constructing low-complexity protocol conversion programs, and the more efficient and equitable allocation of edge server resources, are critical challenges that need to be addressed. This paper investigates the joint problem of task offloading and heterogeneous protocol device access in command and control communication networks, deriving the benefit parameters of task offloading. We propose a real-time data unified access platform, which, by distributing configuration files, enables the IoT gateway to generate protocol conversion programs, thereby transforming all device protocols into a unified common protocol. Furthermore, to enhance the efficiency of heterogeneous device access to the network, we design a data parsing/encapsulation algorithm based on the real-time data unified access platform, supporting bidirectional mapping of two types of data. Experimental validation confirms the reasonability and effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

In recent years, Censorship and anti-censorship technology is developing rapidly. The censorship and surveillance systems track traffic on the network; they identify protocols and traffic, block malicious and illegal transportation, and keep the network under control. It can protect the security of network users but also bring risks to their private security, especially that of users chat. In this paper, we introduce MuChat, a free convert chat application for instant communication on mobile, which is designed as censorship as well as surveillance-resistant platform for coverting communication in the censorship region. To evade detection by Internet censors, MuChat uses multi-instant messaging channels provided by public companies to transform messages. It applies end-to-end encryption for information security and transmits data covertly by steganography technology for individual privacy. It also provides perfect forward security protection of users' historical messages. We design and implement MuChat, with this report on the security and performance of MuChat. The evaluation shows that MuChat has proved its high security in terms of running against active attacks, passive attacks, and traffic analysis methods in recent years. It supports all the functions of instant messages with low latency. For short words, it takes only 1–2 s while the base channels take about 0.5 s, and for 20-megabyte files messages with 35–45 s while about 30–40 s for base channels. In our view, this meets the instant communication needs of users. Besides, its architecture can fully support any other public communication channels which can be added by the user. [ABSTRACT FROM AUTHOR]

The adoption of reliable and real-time communication technology is an absolute necessity for the advancement of Internet of Things (IoT) applications. Messaging protocols such as MQTT, AMQP, and HTTP are frequently used for communication with resource-constrained IoT devices. However, choosing a suitable and effective messaging protocol presents a daunting challenge for organizations, as it depends on the specific characteristics and messaging requirements of the IoT system. Therefore, it is crucial to have a comprehensive understanding of three established messaging protocols, such as the Hypertext Transfer Protocol (HTTP), the Message Queuing Telemetry Transport (MQTT), and the Advanced Message Queuing Protocol (AMQP), to appropriately apply them in practical projects. In this paper, information technology solutions are provided for a chain of solar farms to improve harvest productivity, facilitate warning notifications, and enable remote control. Subsequently, a detailed comparative analysis is performed, considering various interconnected criteria, to gain valuable insight into the strengths and limitations of these protocols. The results show that MQTT and AMQP play a role in enhancing overall efficiency and speed within the framework of our suggested photovoltaic system. [ABSTRACT FROM AUTHOR]

In this study, we focus on real-time anomaly detection using the gated graph neural network (GGNN) and long short-term memory (LSTM) algorithms for the most commonly used network protocols of HTTP and TELNET. In a network, the flow of the various protocols is determined by their respective roles. Each protocol consists of options with individual tasks, and protocols are processed based on these tasks. Therefore, when analyzing flow, a unique repetitive pattern emerges according to the flow and mission. Accordingly, when an anomaly signal is involved, the pattern shows different characteristics from the existing pattern. This study identifies the flow of input and output values based on the correlation between the options defined at each port, whereby the correlation is analyzed, and the detection accuracy of the anomaly signal is determined using the GGNN and LSTM algorithms. The experimental results demonstrate an accuracy of 99.36% for GGNN and 89.46% for LSTM in detecting network anomalies. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) and Internet of Things (IoT) are essential for numerous applications. WSN nodes often operate on limited battery capacity, so energy efficiency is a significant problem for clustering and routing. In addition to these limitations, one of the primary issues of WSNs is achieving reliability and security of transmitted data in vulnerable environments to prevent malicious node attacks. This work aims to develop a secure and energy-efficient routing protocol for fault data prediction to enhance WSNs network lifespan and data reliability. The proposed technique has three major phases: cluster construction, optimal route selection, and intrusion detection. The adaptive shark smell optimization (ASSO) technique was initially used with three input parameters for CH selection. These parameters are the residual energy, the distance to the BS, and the node density. After clustering, salp swarm optimization (SSO) is used to select the optimum path for data transmission between clusters, resulting in an energy-efficient WSN. Finally, to ensure the security of cluster-based WSNs, an effective intrusion detection system based on a modified Elman recurrent neural network (MERNN) is implemented to detect the presence of intrusions in the network. The experimental results show that it outperforms the competing methods in various performance metrics. The performance results of quality of service (QoS) parameters are expressed as dispersion value (0.8072), packet delivery rate (98%), average delay (160 ms), network lifetime (3200 rounds), and the accuracy of this method is 99.2%. Compared to the SVM, ELM, HMM, and MK-ELM protocols, the proposed protocol increases network lifetime by 77%, 60%, 45.4%, and 14.2%, respectively. [ABSTRACT FROM AUTHOR]

Federated learning (FL) enables participants to collaboratively train machine and deep learning models while safeguarding data privacy. However, the FL paradigm still has drawbacks that affect its trustworthiness, as malicious participants could launch adversarial attacks against the training process. Previous research has examined the robustness of horizontal FL scenarios under various attacks. However, there is a lack of research evaluating the robustness of decentralized vertical FL and comparing it with horizontal FL architectures affected by adversarial attacks. Therefore, this study proposes three decentralized FL architectures: HoriChain, VertiChain, and VertiComb. These architectures feature different neural networks and training protocols suitable for horizontal and vertical scenarios. Subsequently, a decentralized, privacy-preserving, and federated use case with non-IID data to classify handwritten digits is deployed to assess the performance of the three architectures. Finally, a series of experiments computes and compares the robustness of the proposed architectures when they are affected by different data poisoning methods, including image watermarks and gradient poisoning adversarial attacks. The experiments demonstrate that while specific configurations of both attacks can undermine the classification performance of the architectures, HoriChain is the most robust one. [ABSTRACT FROM AUTHOR]

Routing protocol plays a vital role in FANETs (Flying Ad-Hoc Networks) by facilitating communication between nodes and enabling the establishment of efficient routes. In a FANET, where the nodes can be drones, airplanes or other unmanned aerial vehicles, mobility is a key aspect that requires proper route management. Among the most well-known and widely used routing protocols in different types of networks is AODV (Ad hoc On-Demand Distance Vector). AODV is a reactive routing protocol specially designed for ad hoc networks, including FANET networks. It offers an efficient solution to establish dynamic routes between nodes when direct communication between a source node and the destination node is not possible. However, most of the studies available in the literature mainly focus on the comparison between different routing protocols. They often neglect to examine in detail the performance of the same routing protocol under different circumstances or conditions. This paper offers a thorough investigation into the influence of noise on the AODV protocol in FANET networks. Furthermore, we introduce a proposed enhancement to the AODV protocol, specifically designed to improve its ability to withstand the effects of noise. Additionally, we present simulation results that evaluate the performance of AODV in terms of throughput, End-to-End Delay, Packet Delivery Ratio (PDR), and energy consumption. [ABSTRACT FROM AUTHOR]

The security context, generally stored in the universal subscriber identity module card or the baseband chip, is the critical information applied by the subscriber to access the 5G network during the fast authentication procedure. Once exposed or illegally used, the security context can be exploited to derive various keys for authentication and encryption. Despite its importance, challenges and questions still remain in the previous relevant research. To fill this gap, by adopting the security protocol verification tool ProVerif, we provide a comprehensive formal model of the fast authentication procedure based on the security context to analyze whether security goals can be met. Unfortunately, we uncover two vulnerabilities, including one never reported before. Our analysis shows that these vulnerabilities stem from fundamental design flaws in the cellular network protocol and thus apply to the 4G network. These vulnerabilities could be exploited to launch several attacks, including impersonation and eavesdropping. We have validated these attacks using 5 mobile phones from 5 different baseband manufacturers through experimentation in three mobile carriers. We find an insecure implementation of one of these phones, which exposed it to replay attacks. And we further discuss the security threats posed by the impersonation attack, such as location spoofing and one-tap authentication bypass, which is verified on 10 popular apps. We finally propose several countermeasures to eliminate these security issues. Actually, we have reported the novel vulnerability to the GSM Association and received a confirmation in the form of a coordinated vulnerability disclosure (CVD) number CVD-2022-0057. [ABSTRACT FROM AUTHOR]

Internet of Vehicles is in demand with the technological expansion, where smart vehicles can communicate with other vehicles, infrastructure, and humans. Traffic management has become more complex with increased traffic density on the road. To avoid severe road accidents, emergency message dissemination in a timely manner is a significant challenge. In this paper, we proposed an emergency message dissemination technique for vehicular networks with the integration of Software defined networks and fog computing. The aim is to offer V2I and V2V communication with minimal latency, reduced congestion, and a high packet delivery rate while achieving maximum information coverage. Three distinct communication modes are defined, each with its own set of algorithms. In the event of a failure in any of these mechanisms, an alternative method is available to deliver a message without the need for an extended wait for link recovery. An optimum forwarder node is selected to rebroadcast a message to the destination. The proposed architecture is analyzed and compared with an existing protocol by conducting a set of simulations. The results section demonstrates the efficiency of our proposed architecture. [ABSTRACT FROM AUTHOR]

Vehicular Internet of Things (VIoT) refers to integrating Internet of Things (IoT) technology into the transportation sector, specifically vehicles. It aims to enhance transportation safety, efficiency, and sustainability by using connected devices and real-time data exchange between vehicles, road infrastructure, and transportation management systems. RFID can provide valuable insights into the functioning and performance of vehicles, enabling the development of intelligent transportation systems and contributing to the growth of the VIoT. To secure essential driving data tag location, data privacy, and road safety are the primary concerns in the VIoT system. An attacker can perform a variety of attacks on the tag and compromise its privacy through the wireless channel between it and the reader. To ensure secure communication for the various application of the VIoT system, An RFID-based protocol is proposed, which is referred to as UPSRVNet (Ultralightweight, Privacy preserved, and Secure RFID-based authentication protocol for VIoT Networks). The proposed protocol guarantees secure authentication in VIoT networks using ultralightweight, privacy-preserving RFID tags by substituting bit formation and right-shift rotation for high-computing operations like hash functions and encryption/decryption algorithms. It also reduces RFID tags' storage and communication overhead and aims to secure the driver's location, personal information, and resistance from known attacks. As per the experiment result, the proposed UPSRVNet protocol showed a significant reduction in communication overhead between tag and reader, that is 50%, and the storage cost on the tag is also reduced by 33.33% compared to existing protocols. Due to this, the certification and authentication processes may be performed quickly. The protocol ensured the security requirements by informal analysis using the Scyther tool. A comprehensive analysis of the proposed protocol reveals its substantial advantages over the existing protocol concerning computation complexity, communication efficacy, and storage expenditure. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) in tourism refers to the use of interconnected devices and systems to enhance the travel experience for tourists. IoT applications in the tourism industry include using and promoting new wireless communication mediums, which will have a significant impact on this business. Wireless network sensors (WSNs) significantly influence the future of communication because they offer a new channel for communication among linked tourist machinery and equipment. The effective routing method of sensor nodes can be helpful for the application of wireless sensors and IoT in eco-cultural tourism. The routing approach of sensor nodes is crucial to the entire network's performance. Routing protocols select several intermediary nodes between the source nodes and the destination nodes to build an effective data transmission path by enhancing WSN's performance in eco-cultural tourism. This study use the Dynamic Host Configuration Protocol (DHCP) and the conventional Minimum Maximum Battery Cost Routing (MMBCR) protocol to lower the network's energy consumption and packet loss rate. According to the experimental findings, the DHCP protocol's network latency was 0.01 s, and the MMBCR protocol's network delay was 0.05 s, when there were 30 nodes in the network. Similarly, the MMBCR protocol's network latency was 0.17 s, and the DHCP protocol's network delay was 0.07 s when there were 150 nodes. The DHCP protocol's network delay increased but did not change abruptly, but the delay of the MMBCR protocol increased constantly and quicker based on the experimental outcomes. It demonstrates how the DHCP protocol is more flexible to data rate increases and more suited to enhancing the speed of sensor nodes as a new medium for communication. [ABSTRACT FROM AUTHOR]

The popularity of small office and home office routers has brought convenience, but it also caused many security issues due to vulnerabilities. Black-box fuzzing through network protocols to discover vulnerabilities becomes a viable option. The main drawbacks of state-of-the-art black-box fuzzers can be summarized as follows. First, the feedback process neglects to discover the missing fields in the raw message. Secondly, the guidance of the raw message content in the mutation process is aimless. Finally, the randomized validity of the test case structure can cause most fuzzing tests to end up with an invalid response of the tested device. To address these challenges, we propose a novel black-box fuzzing framework called MSLFuzzer. MSLFuzzer infers the raw message structure according to the response from a tested device and generates a message segment list. Furthermore, MSLFuzzer performs semantic, sequence, and stability analyses on each message segment to enhance the complementation of missing fields in the raw message and guide the mutation process. We construct a dataset of 35 real-world vulnerabilities and evaluate MSLFuzzer. The evaluation results show that MSLFuzzer can find more vulnerabilities and elicit more types of responses from fuzzing targets. Additionally, MSLFuzzer successfully discovered 10 previously unknown vulnerabilities. [ABSTRACT FROM AUTHOR]

The world's first five-agent network, also called Wuxing network in ancient China, had been fully established in the second century BC. Surprisingly, the key to cracking the operation of Wuxing network is the golden ratio, the world's most astonishing number originating from ancient Greece. Wuxing network is composed of five agents located on the vertices of a pentagon such that adjacent agents cooperate with each other, while spaced-apart agents oppose each other. Although it was proposed more than 2000 years ago, it is still an unparalleled network operation protocol. This article reveals the role of the golden ratio in the balance and stability of Wuxing network, and demonstrates how to detect the golden ratio experimentally in Wuxing electronic circuits and in Wuxing formation flight of drones. [ABSTRACT FROM AUTHOR]

Internet of Medical Thing (IoMT) is an emerging technology in healthcare that can be used to realize a wide variety of medical applications. It improves people's quality of life and makes it easier to care for the sick individuals in an efficient and safe manner. To do this, IoMT leverages the capabilities of some new technologies including IoT, Artificial Intelligence, cloud computing, computer networks and medicine. Combining these technologies to monitor the patient's health conditions in real-time or semi-real-time is a critical challenge in IoMT. In this regard, one of the most crucial components of IoMT are network communication protocols that should provide a fast and reliable communication path between a connected biosensor to a patient and cloud computing environment. In this paper, we propose EQRSRL as an efficient routing mechanism for different types of IoMT applications. The aim of EQRSRL is to provide a reasonable level of Quality of Service (QoS) for IoMT traffics. To achieve this goal, it categorizes the network traffic into three classes and treats them differently concerning their QoS requirements. Moreover, EQRSRL divides the network environment into multiple zones to decrease the number of message exchange between the nodes. In order to compute optimal paths between the nodes, it considers QoS and energy metrics, and makes use of a reinforcement learning approach in path computation process. Simulation results show that the implementation of EQRSRL in IoMT is practical and leads to improvement of 82% in average energy consumption, 25% in end-to-end delay and 7% packet delivery ration in compared to the state-of-the-art routing techniques. [ABSTRACT FROM AUTHOR]

The consumer measurement uncertainty of a local time scale deviation in relation to remote NTP (Network Time Protocol) servers is analyzed. The calculations were conducted regularly based on the latest measurements published on the COOMET website, specifically the document 605/RU/13 TC 1.11 Time and frequency. The results of measuring the discrepancy between the time scales of the KazStandard and VNIIFTRI NTP servers are presented. These results provide information on the uncertainty of comparison and the accuracy of time scale synchronization for the consumers utilizing NTP time servers on the Internet. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) is the interconnection of devices with the internet to deliver its tasks. Nowadays, security is the main concern relating to these devices. Low in power storage, low in processing capabilities and low in data storage make it hard to provide a strong set of security protocols to protect the vulnerable devices "things". Having internet as its backbone, allows the devices to communicate seamlessly. However, without any form of protection, it would open the door for hackers or middleman to hijack the connection, steal data and sabotage the information. In this paper, Secure Socket Layer and Transport Layer Security (SSL/TLS) protocol is implemented on top of Message Queuing Telemetry Transport (MQTT) IoT application protocol and the performance of the network is evaluated and analyzed in a typical IoT testbed comprising Raspberry Pi4 and ESP32 nodes. This work focuses on energy consumption, generated overhead, system complexity and required data storage resources. Experimental results of stress testing the system indicates that SSL/TLS encryption, operating with MQTT Quality of Service (QoS) level 2, while increasing the traffic rate 3.5 orders of magnitude yields more than two thousand times the amount of overhead generated and results in 73.25 J of consumed energy. Whereas operating without the SSL/TLS encryption under the same stress testing conditions yields only 140 times the amount of overhead generated and results in a mere 18.76 J of consumed energy. This difference of 4 folds on consumed energy indicates that the SSL/TLS -enabled node battery can only last a quarter of the lifespan of the TLS-free node and concluding the SSL/TLS encryption is not a viable solution for battery-operated IoT nodes. [ABSTRACT FROM AUTHOR]

In this paper, network energy assesses the capacity of a node to convey messages to others. In most cases, network energy is created when two nodes interact with one another. If a node is part of the same network as the node it is connecting with, then it will be able to make an inter-network energy connection with the node it is meeting. In the case that this does not take place, there will be an accumulation of energy within the part of the network that is facing the node. A node with higher inter-network energy is considered suitable for forwarding. The energy optimisation is achieved using efficient identification of source and destination pairs. This work has considered two scenarios, i.e. lossless transmission and lossy transmission, for our experiments and evaluated the detection probability. The performance of the proposed PPM is evaluated in terms of delivery ratio, overhead and hops count performance measures. When the buffer size is set to 100 MB, PPM delivers 59% of messages with message overhead of 750 and it has a hop count of 2, which is comparable to the state-of-the-art methods. With lengthy lifetimes of IOT networks, PPM is capable of giving higher performance while maintaining the privacy of network. The detection probability for the lossy observations model is applied to a 10-node, 20-node, 30-node and 40-node IoT network. [ABSTRACT FROM AUTHOR]

Many previous studies showed that some nodes should be in a sleeping state while the traffic is high. These nodes can wake up periodically to transmit data while they have data to transmit. The system throughput will be increased while each node can change between wake-up and sleeping states periodically. If a node can estimate the active rate and wake up at the optimal time, the collision probability decreases. This study proposes a Q-learning-based distributed queuing medium access control (QL-based DQMAC) protocol for Internet-of-Things (IoT) networks. In the proposed QL-based DQMAC, we derive the optimal number of contention IoT nodes. Each node calculates the active rate by itself through the Q-learning algorithm. Then, each node determines whether it will be active or in sleeping mode in the next contention period according to the active rate. Finding the optimal IoT nodes in each contention period decreases the probability of collision. The energy consumption due to the contention and delay for MAC contention is reduced owing to the lower number of contentions. Protocol comparison with other DQMAC protocols shows that the proposed QL-based DQMAC protocol achieves higher performance in IoT networks. [ABSTRACT FROM AUTHOR]

The Internet Engineering Task Force (IETF) has defined routing protocols for low power and lossy networks (RPL) for constrained devices. RPL constructs DODAGs (destination oriented directed acyclic graphs), to optimize routing. RPL ensures acyclic topology with the DODAG version number. However, the control message's DODAG version number is not authenticated. So, RPL is vulnerable to network resource attack known as DODAG Version Number (DVN) attack. DVN attack creates a packet delay, packet loss, cyclic topology, etc., in the network. This paper proposes a method for detecting DODAG version number attacks. Several existing schemes to defend against the DVN, such as cryptographic techniques, trust-based, threshold-based and mitigation are computationally intensive or require protocol modification. DVN does not change the packet format or sequence of packets, but can still perform attacks and hence fall under the category of stealthy attacks, which are difficult to detect using traditional intrusion detection system's (IDS). Discrete-event system (DES) based IDS have been applied in the literature for stealthy attacks that achieve low overhead, low false alarm rate, etc. However, the construction of DES-based IDS for network protocol may lead to errors, as modelling is manual. The resulting IDS, therefore, is unable to guarantee its correctness. This paper proposes linear temporal logic (LTL) based DES paradigm to detect DVN. LTL-based paradigm facilitates formal verification of the DES-based IDS, and hence the correctness of the scheme is ascertained. The proposed technique is simulated using the Contiki cooja simulator. When the percentage of spiteful nodes in the network increases, the true positive rate, and packet delivery rate drops, while the false positive rate and control message overhead increase. The memory requirement for sending the packets and verifying the nodes is minimal. The LTL-based IDS has been formally verified using NuSMV to ensure the correctness of the framework. [ABSTRACT FROM AUTHOR]

LoRa is a low-power WAN technology designed for the Internet of Things. When large-scale nodes are deployed in a LoRa network channel conflicts increase and packet transmission collisions will lead to a significant reduction in the transmission efficiency of the network. It has been shown that the CSMA protocol based on the CAD mechanism of LoRa devices can be a good solution to such channel conflict problems, but less research has been done on the limitations of CAD itself. In this paper, we analyze in detail the listening range of LoRa network service area and CAD, get the relationship between ED location and the corresponding number of hidden EDs, and establish the communication model of LoRa network based on CSMA. The analysis shows that the CAD listening range of the nodes does not cover the whole LoRa network due to the limitation of the device performance, and the hidden nodes in their blind zones negatively affect the CSMA operation, and this effect is increasing as the number of deployed nodes increases and the network transmission efficiency keeps decreasing to p-ALOHA. To address this problem, this paper proposes a CSMA channel access scheme based on ED location and communication time planning (LT-CSMA), which plans the communication time of EDs at different locations in the LoRa network, aiming at the communication time of Eds within the CAD listening range of each ED to be adjacent to each other, while hidden nodes outside the listening range will be isolated from them in terms of communication time, thus avoiding the channel conflicts caused by hidden nodes. Simulation experiments prove that LT-CSMA can make full use of idle radio channels and has very good results for packet transmission in LoRa networks with small deployment size, and its packet success probability is much higher than that of channel access mechanisms such as CSMA, s-ALOHA, and p-ALOHA. And as the number of EDs deployed increases, LT-CSMA always outperforms CSMA, p-ALOHA in terms of data transmission efficiency, demonstrating good scalability. [ABSTRACT FROM AUTHOR]

TCP-Transmission Control Protocol provides connection oriented and reliable communication. TCP's default consideration of any loss as a cause of network congestion degrades the end-to-end performance in wireless networks specially in MANETs-Mobile Adhoc Networks. TCP should identify various non congestion losses such as channel loss and route failure loss to act accordingly. Over the years, researchers have proposed Machine Learning based network protocols for accurate and efficient decision making. Reinforcement learning suits better for the dynamic networks with unpredictable traffic and topology. TCP-RLLD, TCP with Reinforcement Learning based Loss Differentiation is an end-to-end transport layer solution to predict cause of a packet loss. TCP's default consideration of any loss as a congestion loss is overruled by TCP-RLLD to avoid unnecessary reduction of the transmission rate. TCP-RLLD is evaluated with multiple TCP variants for the Mobile Adhoc Networks. The extensive evaluation is performed with NS-3 simulator. This paper discusses TCP-RLLD architecture along with the detail of performance improvement. [ABSTRACT FROM AUTHOR]

The Internet of Things in 5G and next-generation data communication networks have relied heavily on Wireless Sensor Networks (WSNs). Data aggregation, Energy consumption, bandwidth utilization, and dynamic traffic routing play a significant role and impose challenges in achieving QoS in a sensor network. Therefore, it is crucial to concentrate on these factors in order to increase the network's lifetime and quality of service. The research's goal is to analyse IoT WSNs in terms of their architecture, framework, security, data aggregation, and routing techniques. In IoT WSNs, the data aggregation technique reduces the energy consumption of the network's nodes. This improves the network's energy and other QoS parameter's efficiency. The network layer hybrid data aggregation and routing protocol proposed in this study is new and efficient. In this work, a novel method for data aggregation based on anchor-based routing and matrix filling theory is proposed. It is suggested to use improved Anchor-based Routing protocol for Event Reporting (ARER), an anchor-based routing technique that includes dynamic clustering and constrained flooding. In order to achieve QoS in IoT WSN, the proposed hybrid network layer protocol has outperformed. The proposed protocol has performed better in terms of QoS metrics like throughput, end-to-end delay, routing overhead, packet delivery ratio, and energy consumption. [ABSTRACT FROM AUTHOR]

Protecting users' privacy over the Internet is of great importance; however, it becomes harder and harder to maintain due to the increasing complexity of network protocols and components. Therefore, investigating and understanding how data are leaked from the information transmission platforms and protocols can lead us to a more secure environment. In this paper, we propose a framework to systematically find the most vulnerable information fields in a network protocol. To this end, focusing on the transport layer security (TLS) protocol, we perform different machine-learning-based fingerprinting attacks on the collected data from more than 70 domains (websites) to understand how and where this information leakage occurs in the TLS protocol. Then, by employing the interpretation techniques developed in the machine learning community and applying our framework, we find the most vulnerable information fields in the TLS protocol. Our findings demonstrate that the TLS handshake (which is mainly unencrypted), the TLS record length appearing in the TLS application data header, and the IV field are among the most critical leaker parts in this protocol, respectively. [ABSTRACT FROM AUTHOR]

With the dense deployment of basic service set (BSS) in the next generation Wireless Local Access Network (WLAN). The overlapping coverage of multiple BSSs leads to intensified contention conflicts, low efficiency of buffer state reports (BSR) collection and a sharp decline in system throughput. To solve this problem, this paper proposes an access point (AP) cooperation based multi-BSS multi-user full duplex multiple access protocol (CMMFD). Firstly, access control (AC) divides the STAs in the cooperative network area into overlapping STA and non-overlapping STA. A bi-level channel resource allocation algorithm is designed. The first level is channel resource allocation in the collection stage of BSR and inter-node interference information (BI), and the second level is channel resource allocation in full duplex data transmission. Secondly, a protocol framework for parallel BI information collection of cooperative APs is designed. AC schedules cooperative APs to send trigger frame at the same time, and triggers STAs in each BSS to report BI information on the assigned channel resource with p -probability access mode. Finally, AP forwards the collected BI information to AC, and AC assigns the STAs in the multi-BSS to perform multi-user full-duplex transmission on the resource unit (RU). Theoretical analysis gives the closed form expressions of the mean number of STAs successfully collected by AC in the cooperation area and saturated network throughput. Simulation results show that compared with MU-FuPlex and EnFD-OMAX protocol, CMMFD protocol improves the network throughput by 29.6% and 31.2% respectively. [ABSTRACT FROM AUTHOR]

In Wireless Sensor Network (WSN), the consumption of energy is high due to the data transmission in the sensing region. The Optimized Distributed Voronoi-based Collaboration (ODVOC) optimizes data delivery and it suffers from huge energy consumption. To overcome this drawback, a data aggregation scheme is introduced to expand the lifetime of the network and to minimize the energy utilization. Data aggregation is a significant approach that preserves the unwanted usage of energy during data transmission. In this paper, the Optimized Distributed Voronoi-based Cooperation scheme with Energy-aware Dual-path Geographic Routing (DAOHS-ODVOC-EDGR) is proposed which incorporates the polydisperse aggregation scheme and it aggregates the indispensable data in the intermediary nodes. The effective data aggregation is achieved by the estimation of the waiting time of the data at every intermediary node and cost function that is used for electing the next-hop node. In the proposed protocol, the buffer value of every node is divided to retain diversified kinds of flow for effective and fair delivery of data. The rate of transmission at the source and intermediary node is altered during the congestion. The proposed DAOHS- ODVOC-EDGR protocol is tested via simulation scheme. The result of the simulation exposes that DAOHS-ODVOC-EDGR outperforms the TESDA and DVOC protocol in terms of network lifetime, energy efficiency, and hop count delay. [ABSTRACT FROM AUTHOR]

The wireless sensor network is of great interest due to its special features and applications. Due to the computational limitation and power supply of these networks, hierarchical cluster routing is mentioned as a solution to improve the problem of energy consumption and network lifetime. In our study, a fuzzy-based clustering routing protocol was proposed that uses network zoning and node residual energy parameters, node distance to the center of each zone, and node-to-base station angle as fuzzy input for cluster head selection. In the proposed method with the aim of reducing network energy consumption, the responsibility of choosing CHs in each area, determining the area of each node, calculating the distance of each node to the center and calculating the angle of each node was assigned to the BS. The proposed method was carried out with Farahzadi, LEACH, MSCR protocols in terms of network lifetime evaluation criteria, stability period, selection and number of CH and average residual energy in MATLAB environment. The comparison of the results showed that the proposed method has performed better in terms of criteria, so that the network lifetime as one of the important indicators, the proposed method has improved by 50%, 40% and 20%, respectively, compared to LEACH, Farahzadi and MSCR methods. [ABSTRACT FROM AUTHOR]

There is a large number of connected devices in the Internet of Things (IoT) networks that are typically several orders of magnitude bigger than enterprise networks and campus networks. The exponential increase in the number of interconnected smart devices is expected to exceed 60 billion smart objects shortly. The requirements needed for IoT networks are scalability, low power consumption, and simplified routing and security protocols. IoT networks are also heterogeneous, composing different types of networks together. Legacy network protocols like IPv4 has deemed to be inefficient for IoT networks. As the number of IPv4 addresses is almost consumed with regular network devices, we propose the use of IPv6 addressing for IoT-connected devices as IPv4 cannot accommodate the scalability requirement of IoT. IPv6 provides extended address space and enhanced mobility which are very essential for IoT networks. In this research, we apply IPv6 to IoT networks to avoid the scalability bottleneck of the IPv4 subnet. IPv6 accommodates a large number of connected devices and solves issues resulting from the heterogeneous nature and access methods of IoT devices. However, IPv6 is a large protocol that does not suit itself well in the IoT world. The Maximum Transmission Unit (MTU) permitted for IEEE 802.15.4 MAC data frames with their encapsulated IPv6 packet is limited to 127 bytes. We need 40 bytes for the uncompressed IPv6 header and 8 bytes are needed for the uncompressed UDP header. As a result, there are either 54 bytes left for the payload when security is not considered or 33 bytes when security is considered. We investigate throughput improvement for IoT networks by applying adaptation to IPv6 through header compression with UDP header compression. We also apply fragmentation for MAC frames that exceed the 127 bytes MTU limit. Simulation results showed that IPv6 compression with or without fragmentation serves toward adapting IPv6 packets to IoT networks. In the case of applying fragmentation, the technique of fragment forwarding greatly enhances the performance. Network traffic within the same network can be compressed to 2 bytes. On leaving the 802.15.4 network, the header increases to 12 bytes if the network prefix is known or to 20 bytes if the network prefix is unknown. Two evaluation metrics, namely, Compression Gain and Packet Delivery Ratio were applied to our proposed implementation method to prove the validity and the efficiency of our proposal. [ABSTRACT FROM AUTHOR]

Wireless body area networks are communication networks between the sensors and hubs in-body, on-body and out-body. IEEE 802.15.6 protocol has been developed for such networks. In this study, modulation techniques proposed in IEEE 802.15.6 ultra-broadband physical layer were compared with orthogonal frequency division multiplexing based dual carrier modulation techniques in wireless body area networks channels. The dual carrier modulation is defined with 16-quadrature amplitude modulation constellation diagrams. In order to have reliable communication, dual carrier modulation with lower level modulations such as quadrature amplitude modulation and binary phase shift keying constellation diagrams has been presented in this study. IEEE 802.15.6 ultra-broadband physical layer has been simulated and compared with the dual carrier modulation and types discussed on the same wireless body area networks channels and according to the timing parameters proposed in the protocol. Performance results have been given as bit error rate—signal to noise ratio graphs. At low data rates, it was observed that the performances were high, while the dual carrier modulation performances were even higher. Due to the high dispersion of wireless body area networks channels, the performances of both protocol modulations and dual carrier modulations are quite low in wireless body area networks channels at high data rates. Therefore, at high data rates, a suitable channel equalizer or high number of subcarriers should be used for modulations with orthogonal frequency division multiplexing because of the high tap number of wireless body area network channel. By using dual carrier modulation with higher subcarrier, better performance results are achieved with trade off hardware complexity. [ABSTRACT FROM AUTHOR]

Currently, the proportion of unknown traffic in networks continues to increase. This poses great challenges to the management and security of cyberspace. The unknown traffic refers to network traffic generated by previously unknown protocols in a preconstructed traffic identification system. Measures to address this challenge can be developed by grouping the mixed unknown traffic into multiple clusters, where, ideally, each cluster contains just one traffic class. In this paper, we propose a novel scheme for clustering unknown traffic, named dual-path autoencoder-based clustering, to discover protocol-based traffic classes. The dual-path autoencoder model refers to the combination of convolutional autoencoder and deep autoencoder, which realizes the extraction and aggregation of payload features and statistical features. Then, the fusion feature is clustered by the correlation-adjusted clustering module, and the unknown traffic flows are divided into multiple high-purity clusters. To evaluate our scheme, experiments are conducted on two public network traffic datasets and one campus network dataset. Using seven common application layer protocols to simulate unknown traffic, the evaluation results show that our scheme can achieve above 98% on each dataset when the preset number of clusters is 60. This establishes the effectiveness of the proposed scheme for clustering unknown network protocols. [ABSTRACT FROM AUTHOR]

Video communication gained wide popularity since it offers a more real-time mode of face-to-face interaction. This paper mainly aims to enhance the video transmission quality of multimedia applications via communication network security improvement and an adaptive resource allocation strategy. The main aim of the resource allocation strategy is to achieve efficient usage of spectrum resources since video communication utilizes the orthogonal subcarriers for data transmission and the need for conversion of non-flat channels to flat. An optimized Hybrid Deep Random Neural Network (HDRaNN) architecture is used to overcome the adaptive spectrum resource allocation problem in the single-frequency network transmission by taking into account the different time–frequency resources and regions for overlapping areas and the same time–frequency for non-overlapping areas. The Sheep Flock Optimization algorithm is used to minimize the network error rate of the HDRaNN architecture by optimizing the weights and biases. The basic purpose of communication network security in this paper is to ensure that data communicated over a network connection are safe and secure. The network security protocol offers protection from unauthorized data retrieval and attempts to obtain data. The protocols utilized for secure communication in the proposed technique are Secure Hypertext Transfer Protocol, Secure Socket Layer, Simple Network Management Protocol, and Secure File Transfer Protocol. This protocol also assures that unauthorized users, devices, or services do not have access to your network data and works on all network mediums and data types. The extensive experiments conducted using the proposed methodology show improvements in the video transmission quality in terms of high diversity gain, security, increased throughput, and minimized bit error rate. [ABSTRACT FROM AUTHOR]

The 802.11ah standard is a new energy-efficient, wireless networking protocol which allows thousands of indoor and outdoor devices to be connected to the same access point. The Centralized Authentication Control (CAC) method, described in the standard, enables up to 8000 stations to be authenticated and associated with the same access point. A baseline implementation of the CAC method has been reported; however, it suffers from a few limitations. In this paper, an efficient methodology is proposed to minimize the CAC method's association time. The proposed methodology allows the association of a large number of stations by predicting the size of the network followed by selecting the best step size that will enable fast association between the access point and the stations of the network. The methodology consists of three stages. The first stage provides a baseline implementation of the 802.11ah standard, while the second stage eliminates the effect of too large or too small step sizes. The third stage finds the optimal step size and step repeat for each network size and predicts network size based on queue size. The performance of the proposed methodology is evaluated and compared in terms of total association time, number of total trials and percentage of ineffective trials. The methodology outperforms the baseline implementation by achieving a 30% reduction in the total association time, 30% reduction in the total number of trials and 45% reduction in the total number of ineffective trials. [ABSTRACT FROM AUTHOR]

The advancement of the Internet of Things (IoT) has tremendously influenced many fields of human life. The Internet of Medical Things, Internet of Flying Things, Internet of Floating Things and Internet of Autonomous Things are recent evolution of IoT. The protocols used in all forms of IoT are critical during the execution demanding formal verification methods to ensure correctness. However, the most challenging part of formal verification is abstracting the system under test, making many systems unverified. Formal protocol verification is essential for detecting specification and design flaws that go undetected and corrected during the testing phase. This paper proposes novel methods for abstracting communication patterns for IoT protocols. Message broadcasts, periodic message advertisements, topology encoding, and topology change are examples of communication patterns. An attempt is made to model these patterns using pi-calculus and PROMELA. Finally, the trickle, a wireless sensor network dissemination protocol, has been modelled using pi-calculus and PROMELA. The Spin model checker verifies design flaws, such as deadlocks and non-progress cycles. The verification results ensure that there are no deadlocks or non-progress loops. The protocol is statically verified for message transmission semantics. The analysis revealed that the protocol could only guarantee message transmission for lossy connections if an alternative route covers all other nodes. The empirical results and theorem show that the abstraction mechanism can be directly utilised for automated and theoretical verification. Researchers can use the abstraction framework described in this paper to create validation models for static and automated verification of existing and new IoT protocols. [ABSTRACT FROM AUTHOR]

The congestion problem can occur in a cooperative network because of the non-responsiveness of intermediate nodes or heavy traffic. Existing DSR cannot optimize the communication route in a such high congestion situation. In this paper, a new CPEDSR protocol is presented for handling energy and congestion-critical situations in the mobile network. The main objective of the proposed protocol is to identify the suspected attacked and congested nodes and perform communication over safe and reliable nodes.In this improved protocol, a congestion ratio-based probabilistic measure is employed for computing the congestion-resistance (CR) for each node. The weight is evaluated based on connectivity count (CC), residual energy (RE), average participation (AP), and average failure (AF) ratios. After computing the individual parameter, the overall CR is estimated to label the congestion-safe nodes. The weight rules are implied on CR for deciding the participation eligibility of the node. With each communication session, a more effective and accurate decision for node participation is taken. It is an experience adaptive protocol that acquires some weightage of the previous status for making decisions about the current node. This participation degree of neighbor nodes is processed by the DSR protocol to identify the next effective hop. The simulation is performed in congested and DDOS-infected networks. The comparative analysis is done against the existing and improved reactive protocols. The proposed protocol is validated on four network scenarios with a varied number of nodes and in attacked, non-attacked, and heavy traffic situations. The proposed CPEDSR protocol is validated against DSR, AODV, SAODV, PSAODV, PDS-AODV, and RSKNSN protocols. The average loss rate of AODV, DSR, SAODV, PSAODV, PDS-AODV, RSKNSN, and the proposed CPEDSR protocols for all scenarios is 15.07, 18.99, 10.62, 7.09, 8.30, 9.27, and 6.08%. The average number of dead nodes for all scenarios is 20.75 for AODV, 22.75 for DSR, 19.75 for SAODV, 18.5 for PSAODV, 18.25 for PDS-AODV, 16.75 for RSKNSN, and 14 for CPEDSR. It shows that the proposed protocol improved the network life and reduced communication loss during transmission. [ABSTRACT FROM AUTHOR]

It is well known that the Sixth Generation (6G) communication system integrating multiple access networks promotes the internet of everything world-widely. However, due to the differentiated underlying network protocols, it is difficult to find a general authentication solution to support various authentication methods in different access networks. Blockchain is a new technology that supports network heterogeneity, which provides a potential solution for differentiated authentication. In this paper, we propose a blockchain-based differentiated authentication mechanism for 6G Heterogeneous Networks (HetNets), which can efficiently authenticate user identities through scheduling different authentication methods. Particularly, we analyze the authentication architecture of 6G HetNets and put forward a blockchain-based differentiated authentication framework. Besides, to improve the scalability of user authentication, it is the first time to use various blockchain authentication contracts to represent different authentication methods. Meanwhile, a differentiated authentication management contract is proposed to uniformly manage different authentication contracts to realize differentiated identity authentication. Based on the evaluation of the prototype system, the proposed mechanism can dynamically provide differentiated authentication services (e.g. EAP-MD5, 5G-AKA) with low additional time (milliseconds levels) cost. [ABSTRACT FROM AUTHOR]

Routing protocol for low power and lossy networks (RPL) serves the routing process in Internet Protocol version 6 over low-power wireless personal area network protocol stack. RPL protocol is deployed on sensor nodes and is vulnerable to many attacks due to the resource-constrained and non-tamper-resistant nature of these nodes. Many attacks on RPL-based networks can be carried out by an attacker using either an insider or an outsider attack method. The concerns associated with the RPL protocol regarding security and privacy may restrict its global adaption. Therefore, it is necessary to conduct a thorough investigation of RPL-specific attacks and their effects on the underlying network. To this end, our work provides a detailed investigation of the rank attack, a type of denial-of-service attack and its effect on the RPL network. We made an in-depth experimental study on four different RPL network topologies and analysed the impact of rank attack. To analyse the effect of rank attack, we use both grid and random variants of the network topologies. Based on the location of the sink node, we classify the grid topology as grid corner and grid centre, whereas, based on mobility, we classify the random topology as random topology with static nodes and random topology with mobile nodes. Under the attack scenario, the average number of packets received in grid topology with sink node at centre degrades by 10%. For grid topology having the sink node at the corner, the average number of packets received degraded by 13.44%. The percentage degradation of the average number of packets received at the sink node with random topology is nearly 8%. Random topology with mobile nodes has 7.4% lesser number of packets received at the sink node. Next, the value of average inter-packet time with random mobile topology has the highest increase of about 19% under attack. At the same time, we notice an increase in average inter-packet time of about 6.4% with random topology, 3.7% with grid topology having the sink node at the corner, and 0.7% with grid topology having the sink node at the centre. Further, when the rank attack is mounted, we notice a hike of 24% in message count with random mobile and 28% with grid corner topology. Moreover, both random topology and grid topology with sink at the centre have a hike of about 13% in message count. Furthermore, when average power consumption is considered under attack scenario, random topology with mobile nodes and grid topology with the sink node placed at the corner demonstrate an increase of 11% under attack. At the same time, random and grid topologies with the sink node at the centre have a rise of nearly 2% as compared to normal RPL. The results of our experiments show that the rank attack considerably degrades network performance in terms of packets received at the sink node, inter-packet time, control message count, and average power consumption. Further, our investigation also confirms that the position of the attacker node in the network topology has a significant impact on the effect of the rank attack. Furthermore, we also suggest some potential solutions to mitigate this attack. [ABSTRACT FROM AUTHOR]

Clock synchronization is one of the most fundamental and crucial network communication strategies. With the expansion of the Industrial Internet in numerous industrial applications, a new requirement for the precision, security, complexity, and other features of the clock synchronization mechanism has emerged in various industrial situations. This paper presents a study of standardized clock synchronization protocols and techniques for various types of networks, and a discussion of how these protocols and techniques might be classified. Following that is a description of how certain clock synchronization protocols and technologies, such as PROFINET, Time-Sensitive Networking (TSN), and other well-known industrial networking protocols, can be applied in a number of industrial situations. This study also investigates the possible future development of clock synchronization techniques and technologies. [ABSTRACT FROM AUTHOR]

IETF 6TiSCH, which is composed of the IEEE802.15.4e and IPv6 RPL protocols, is a highly reliable and low-power industrial wireless network protocol stack. IEEE802.15.4e is the medium access control (MAC) layer protocol of the protocol stack—it defines a time-slotted channel hopping communication mode. IPv6 RPL is the network layer protocol of the protocol stack—it allows multiple nodes to form a multi-hop network. Scheduling is vital to the 6TiSCH protocol stack, as it defines the MAC layer cells to send/receive by the network packets. Herein, we propose an efficient distributed scheduling function (EDSF) for 6TiSCH wireless networks; it fully considers the use probability and distance of cells rather than random selection. Additionally, a schedule collision detection algorithm is proposed to detect two pairs of neighbor nodes that use the same cell. It fully utilizes the historical statistical data from the cell packet delivery ratio. Finally, we implement the EDSF scheme and verify its performance through experiments on a 6TiSCH simulator. The experimental results show that our proposed scheme can achieve a low end-to-end latency without additional costs. [ABSTRACT FROM AUTHOR]

The exponential growth of internet connected devices in this past year has led to a significant increase in IoT targeted attacks. The lack of proper integration of security in IoT development life cycle along with a plethora of different protocols (e.g., Zigbee, LoRa, MQTT, etc.) have greatly impacted the resilience of such devices against cyber-attacks, a fact also exacerbated by the size and physical hardware structure of these devices. Thus, it is imperative to develop effective and efficient countermeasures that can also be applied post-production to help build resilience in modern IoT systems. Honeypots are prime example of this notion. Being designed to act as vulnerable computer components or systems, they provide useful intelligence regarding potential attackers. Nevertheless, honeypots have seen little use in protection IoT systems and their underlying protocols, especially in cases where honeypots can leverage the decentralized nature of IoT. In this research, we enhance the HosTaGe honeypot to build an IoT protocol honeypot that runs over mobile devices. The purpose of this paper is to introduce a honeypot specifically for IoT communication protocols over public networks that is easy-to-use and utilizes Android devices. The protocol honeypot utilizes the cellular network to establish decentralized, simulated infrastructures of IoT systems over different types of IoT network protocols. We test four IoT network implementations, one for each of the newly implemented MQTT, CoAP and AMQP protocols. Additionally, we upgrade existing Telnet and SSH protocols used in IoT systems to work over the simulated mobile honeypot. We use the virtualized honeypot networks to capture log, and analyze real-world public attacks on these protocols from the internet and provide an interface for interaction with the implemented honeypot. [ABSTRACT FROM AUTHOR]

Ocean acidification is one of the parameters that affect underwater wireless sensor network routing protocols. The underlying network-level metrics of sensor nodes correspond to depth-dependent interactions. The spatial relevancy of sensor nodes varies drastically due to the mobility of the ocean column. In this work, complexity of the underwater environment and its characteristics are fed along with the sensor node capabilities of internetworking and its communication void. The wireless sensor node embeds medium access control layer timing of sensor packet transmission associated with its communication range and underwater characteristics of transmission and absorption losses. Underwater routing protocol for void avoidance transmission probability (UWRPVA-TP) is proposed, and sensors are deployed across diverse depths. Multi-hop communications as a function of depth-dependent attenuation across the ocean columns and their transmission probabilities have been calculated under mobility scenarios. The simulation result of UWRPVA-TP has been validated for the protocol using different attenuation models for energy consumption and number of alive nodes. Finally, the packet reliability ratio and deadline miss ratio has been calculated to understand the application of the time complexity associated with packet transfer. [ABSTRACT FROM AUTHOR]

Network function virtualization provides programmable in-network middlewares by leveraging virtualization technologies and commodity hardware and has gained popularity among all mainstream network device manufacturers. Yet it is challenging to apply coverage-guided fuzzing, one of the state-of-the-art vulnerability discovery approaches, to those virtualized network devices, due to inevitable integrity protection adopted by those devices. In this paper, we propose a coverage-guided fuzzing framework NDFuzz for virtualized network devices with a novel integrity protection bypassing method, which is able to distinguish processes of virtualized network devices from hypervisors with a carefully designed non-intrusive page global directory inference technique. We implement NDFuzz atop of two black-box fuzzers and evaluate NDFuzz with three representative network protocols, SNMP , DHCP and NTP , on nine popular virtualized network devices. NDFuzz obtains an average 36% coverage improvement in comparison with its black-box counterparts. NDFuzz discovers 2 0-Day vulnerabilities and 1 1-Day vulnerability with coverage guidance while the black-box fuzzer can find only one of them. All discovered vulnerabilities are confirmed by corresponding vendors. [ABSTRACT FROM AUTHOR]

In present days, the utilization of mobile edge computing (MEC) and Internet of Things (IoT) in mobile networks offers a bottleneck in the evolving technological requirements. Wireless Sensors Network (WSN) become an important component of the IoT and is the major source of big data. In IoT enabled WSN, a massive amount of data collection generated from a resource-limited network is a tedious process, posing several challenging issues. Traditional networking protocols offer unfeasible mechanisms for large-scaled networks and might be applied to IoT platform without any modifications. Information-Centric Networking (ICN) is a revolutionary archetype which that can resolve those big data gathering challenges. Employing the ICN architecture for resource-limited WSN enabled IoT networks may additionally enhance the data access mechanism, reliability challenges in case of a mobility event, and maximum delay under multihop communication. In this view, this paper proposes an IoT enabled cluster based routing (CBR) protocol for information centric wireless sensor networks (ICWSN), named CBR-ICWSN. The proposed model undergoes a black widow optimization (BWO) based clustering technique to select the optimal set of cluster heads (CHs) effectively. Besides, the CBR-ICWSN technique involves an oppositional artificial bee colony (OABC) based routing process for optimal selection of paths. A series of simulations take place to verify the performance of the CBR-ICWSN technique and the results are examined under several aspects. The experimental outcome of the CBR-ICWSN technique has outperformed the compared methods interms of network lifetime and energy efficiency. [ABSTRACT FROM AUTHOR]

This work focuses on cognitive users and its utilization of spectrum with channel bonding. Recurrent Channel Bonding Cognitive Users protocol (RCBCU) has been proposed. Spectrum access is enabled to cognitive users in the absence of primary users. Initially, channel bonding and multi-hop communication are established to balance the communication mismatch that occurs at bottleneck nodes. Theingress and egress nodesare modelled with forward and backward parameters analogous to recurrent neural network. Reporting the packet loss is being reduced and instantaneously increasing the channel bonding size is achieved. The ordering of cognitive user channels and composite function of packet loss encountered are back propagated to improve the instant throughput. Thus, as the network links increases subsequently the throughput increases, but the network converges to optimal latency with concurrent transmissions. Simulation comparison of RCBCU using the network simulator with the existing channel bonding scheme shows efficient utilization of channel with fairness, delay and starvation ratio. [ABSTRACT FROM AUTHOR]

Blockchain technology with its inherent security features revolutionizes the field of distributed networks and has become one of the significant areas of research. To preserve the security features and to maintain its global state, consensus mechanisms are very essential and are performed by a set of peers in the underlying network called miners. Therefore, the miners need to be a trusted entity and their trustworthiness plays a vital role in preserving the security of the asset ledger. To ensure trusted nodes perform the consensus process, fuzzy-based trust models are robust and effective. Therefore, fuzzy inference system-based trusted consensus mechanism (FISTCON) is proposed as an effective security solution resulting in a fast and secure consensus process. The proposed scheme works in two phases. In phase 1, a fuzzy-based trust model that includes transaction history and trust feedback (F-THTF trust model) to identify trusted miners for consensus is proposed. In phase 2, a fuzzy-based effective practical byzantine fault tolerance (F-EpBFT) consensus protocol with an optimized broadcasting mechanism to decrease the communication overhead is proposed. The proposed work is implemented in the Hyperledger fabric framework, and the outcomes are thoroughly analyzed to prove the efficiency of the proposed scheme in a variety of scenarios. [ABSTRACT FROM AUTHOR]

Focusing specifically on sensing devices with restricted resources, heterogeneous internet of things (HIoT) is an attractive scenario for IoT networks. Nonetheless, the very nature of wireless channels in these networks has given rise to a series of security challenges, which need to be considered while developing authentication protocols. Here, we scrutinized Yu and Park's, Kumari et al.'s, and Ostad-sharif et al.'s protocols and illustrated their weaknesses against key compromise attacks, insider attacks, and violation of anonymity. Furthermore, for heterogeneous IoT contexts, a lightweight and secure authentication and key agreement protocol for heterogeneous IoT environments is presented. Concerning the restricted resources of sensing devices, an attempt is made to provide an efficient HIoT-based authentication protocol to enhance network security and performance. The gateway as a trusted authority with the maximum workload and sensing devices with the highest restrictions on resources are considered in the suggested protocol. As a result, the user bears the brunt of the workload in the individual session. The Burrows–Abadi–Needham (BAN) logic is used to validate the proposed protocol, and the Automated Validation of Internet Security Protocols and Applications (AVISPA) tool is utilized to demonstrate resilience to existing active attacks. Simulation findings and performance assessment revealed that our protocol improved communication overheads by up to 110%, computation overheads by up to 83%, and sensing device maximum storage capacity by up to 51%. [ABSTRACT FROM AUTHOR]

RabbitMQ, an implementation of Advanced Message Queuing Protocol (AMQP), is a very popular message middleware. It supports concurrency, guarantees sequential consistency, and enables independent applications and services to communicate. Consequently, it is of great significance to ensure the secure communication of RabbitMQ. Therefore, Kerberos, a network authentication protocol, is introduced to combine with RabbitMQ to address this security issue. In this paper, we apply formal methods to model and verify RabbitMQ with Kerberos. By utilizing UPPAAL, RabbitMQ is abstracted to timed automata. Further, we validate the constructed model with the simulator in UPPAAL. On this basis, we verify whether RabbitMQ meets some basic but essential properties, including Reachability of Data, Concurrency, Sequence Consistency and Heartbeat Mechanism. Additionally, the security property Secure Communication is verified as well. From the verification results via UPPAAL, it can be found that RabbitMQ can totally cater for these properties and it maintains secure communication under the umbrella of Kerberos. [ABSTRACT FROM AUTHOR]