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We study consensus in a protocol capturing in a simplified manner the major features of the majority of Proof of Stake blockchains. A committee is formed; one member proposes a block; and the others can check its validity and vote for it. Blocks with a majority of votes are produced. When an invalid block is produced, the stakes of the members who voted for it are "slashed." Profit-maximizing members interact with adversaries seeking to disrupt consensus. When slashing is limited, free-riding and moral-hazard lead to invalid blocks in equilibrium. We propose a protocol modification producing only valid blocks in equilibrium. Authors have furnished an Internet Appendix , which is available on the Oxford University Press Web site next to the link to the final published paper online. [ABSTRACT FROM AUTHOR]

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]

The convergence of heterogeneous wireless sensor networks provides many benefits, including increased coverage, flexible load balancing capabilities, more efficient use of network resources, and the provision of additional data by different types of sensors, thus leading to improved customer service based on more complete information. However, despite these advances, the challenge of ensuring reliability and survivability remains due to low-cost sensor requirements and the inherent unreliability of the wireless environment. Integrating different sensor networks and unifying protocols naturally leads to the creation of a network with multiple sinks, necessitating the exploration of new approaches to rational reliability assurance. The failure of some sensors does not necessarily lead to a shutdown of the network, since other sensors can duplicate information and deliver data to sinks via an increased number of alternative routes. In this paper, the reliability indicator is defined as the probability that sinks can collect data from a given number of sensors. In this context, a dedicated reliability metric is introduced and examined for its effectiveness. This metric is computed using an algorithm rooted in the modified factoring method. Furthermore, we introduce a heuristic algorithm designed for optimal sink placement in wireless sensor networks to achieve the highest level of network reliability. [ABSTRACT FROM AUTHOR]

• Temporary continuous observation task using non-customized constellation is studied. • A hybrid method for multi-satellite scheduling and task planning is proposed. • A joint simulation software system is developed via STK and Python. • The proposed technique has higher efficiency and target adaptability. This paper put forward a method to address the problem, of how to select multiple satellites from a given heterogeneous constellation and plan their tasks to implement a temporary mission for ground or aerial targets successive observation, while hardly affecting the constellation's original mission as much as possible. First, considering the observation geometric constraints of the satellite on the target, an observability analysis model for effective observation of the satellite on the target is established to characterize the observable spatio-temporal scope. Considering the time-length requirement of sustained observation on the target, a multi-satellite-to-target sustained observation model is constructed for the scheduling of satellites. Second, to address the problem of selecting task satellites in a given heterogeneous constellation, a mathematical model for task planning is established to maximize observation benefits and minimize task burdens. Third, a hybrid method of multi-satellite scheduling and task planning is designed with fault tolerance, based on dynamic programming and an improved contract network protocol algorithm. Next, a joint simulation software system is established through the secondary development of STK and Python, which includes satellite-target observability analysis, task satellite selection, task allocation and planning, and full process visible demonstration functions. Finally, simulation cases verified the effectiveness and superiority of the proposed technique. [ABSTRACT FROM AUTHOR]

Recently, there has been a focus on the significance of swarm intelligenceinspired routing algorithms for achieving optimum solutions in biologically inspired wireless sensor networks (WSNs). These protocols depict a network of wireless mobile nodes forming an infrastructure that is agile, dynamic, and independent of a central administrative facility. Among the challenges faced by bio-inspired WSNs, mobility awareness and excessive energy consumption (EC) stand out as significant hurdles, particularly in dynamic models with intermittent connections. This project seeks to tackle these obstacles by deploying the hybrid energy efficiency (HEED) approach to distributed clustering for network system cluster formation, along with fusion routing protocol of particle swarm optimization (PSO) and PIO to select cluster-heads and optimize solutions in bio-inspired WSNs. The success of the suggested approach is assessed using a variety of criteria, such as energy usage, rate of packet delivery, EC, and routing overhead and network lifetime. The methods like ad hoc on-demand distance vector's (AODV) and ant colony optimization (ACO) methods are employed in the testing and validation. In comparison to the reactive AODV routing protocol and ACO, the suggested routing protocol (HPSOPIO) reduces energy usage and increases network lifespan. [ABSTRACT FROM AUTHOR]

With large-scale Cyber-Physical Systems (Internet of Things) deployments, the low-cost networked devices are becoming ubiquitous. Time stamping of events is a basic requirement and it is crucial for distributed/isolated systems/devices to work in unison. The system clocks of these devices are not very stable and their behaviour is affected by ageing and environmental conditions. A clock’s timing behaviour is generally analysed independently by comparison to a highly stable standard reference clock using specialized instruments. Network Time Protocol (NTP) is widely used for time synchronization over computer networks. As the NTP server clock is more stable in comparison to a client’s system clock, the variation in the end device’s clock offset values with respect to the NTP server clock over a long time can be considered for analysing the behaviour of the end device’s clock. This paper presents a method for analysing clock behaviour based on NTP messages. A computer programme is developed, which utilizes an open-source NTP client library to exchange NTP messages and records end device’s system clock’s offset variations over time for a given periodicity to analyse the behaviour. This black box analysis approach does not require any direct access to the end device’s clock circuit. The solution may be useful for analysing clock behaviour for long-term stability under actual environmental conditions, for deciding time synchronization periodicity to optimize the number of synchronization packet exchanges, and for pre-deployment timing stability assessment of devices for deployment scenarios having intermittent/non-availability of periodic time synchronization. [ABSTRACT FROM AUTHOR]

Summary The cluster networking protocols are the roots that embed intelligent decision‐making and enhance the lifespan of wireless sensor networks (WSNs). Wireless sensors with limited capabilities face several challenges due to the heterogeneous application environments. Especially, the mobility‐incorporated sensors in most situations trouble the cluster network's robustness. Many cluster networking protocols have been presented in the past to enhance the network lifespan and data delivery ratio. However, they lack a dedicated and efficient mechanism for mobility assistance, an adequate cluster management process and cluster head selection criteria. To overcome these issues and for the uniform energy load distribution, we propose a mobility‐compatible cache controlled cluster networking protocol (MC‐CCCNP) in this paper. It is an energy‐efficient cluster networking protocol that supports sensor movement. Network resource management and routing are controlled distributively by an optimal number of cache nodes. It defines a new strategy for cache node deployment based on neighbour density as well as a weight formula for cluster head selection and cluster formation based on the residual energy, the distance to the base station and the node velocity. It also includes techniques for detaching and reconnecting a mobile node to an appropriate cluster cache if it crosses the cluster boundary. We simulate and compare the performance of our protocol with the centralised energy‐efficient clustering routing, energy‐efficient mobility‐based cluster head selection protocol and dual tier cluster‐based routing protocols over different network configurations with varying mobility, scalability and heterogeneity. The MC‐CCCNP showed remarkable improvements in energy utilisation uniformity and energy consumption. With the improved network lifespan, it also maintains a higher data throughput rate of 95% or more in almost all network configurations. [ABSTRACT FROM AUTHOR]

Efficient and reliable data routing is critical in Advanced Metering Infrastructure (AMI) within Smart Grids, dictating the overall network performance and resilience. This paper introduces Q-RPL, a novel Q-learning-based Routing Protocol designed to enhance routing decisions in AMI deployments based on wireless mesh technologies. Q-RPL leverages the principles of Reinforcement Learning (RL) to dynamically select optimal next-hop forwarding candidates, adapting to changing network conditions. The protocol operates on top of the standard IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL), integrating it with intelligent decision-making capabilities. Through extensive simulations carried out in real map scenarios, Q-RPL demonstrates a significant improvement in key performance metrics such as packet delivery ratio, end-to-end delay, and compliant factor compared to the standard RPL implementation and other benchmark algorithms found in the literature. The adaptability and robustness of Q-RPL mark a significant advancement in the evolution of routing protocols for Smart Grid AMI, promising enhanced efficiency and reliability for future intelligent energy systems. The findings of this study also underscore the potential of Reinforcement Learning to improve networking protocols. [ABSTRACT FROM AUTHOR]

As the global deployment of Fifth Generation (5G) is being well consolidated, the exploration of Sixth Generation (6G) wireless networks has intensified, focusing on novel Key Performance Indicators (KPIs) and Key Value Indicators (KVIs) that extend beyond traditional metrics like throughput and latency. As 5G begins transitioning to vertical-oriented applications, 6G aims go beyond, providing a ubiquitous communication experience by integrating diverse Radio Access Networks (RANs) and fixed-access networks to form a hyper-converged edge. This unified platform will enable seamless network federation, thus realizing the so-called network of networks vision. Emphasizing energy efficiency, the present paper discusses the importance of reducing telecommunications' environmental impact, aligning with global sustainability goals. Central to this vision is the proposal of a novel user plane network protocol architecture, called 6G Recursive User Plane Architecture (6G-RUPA), designed to be scalable, flexible, and energy-efficient. Briefly, 6G-RUPA offers superior flexibility in network adaptation, federation, scalability, and mobility management, aiming to enhance overall network performance and sustainability. This study provides a comprehensive analysis of 6G's potential, from its conceptual framework to the high-level design of 6G-RUPA, addressing current challenges and proposing actionable solutions for next-generation mobile networks. [ABSTRACT FROM AUTHOR]

For computer networks, bandwidth management is essential. Bandwidth management is a strategy used in network administration to try and provide fair and acceptable network performance. Researchers have monitored the effectiveness of bandwidth management methods including Per Connection Queue (PCQ), Random Early Detection (RED), and First In First Out (FIFO) schemes using the Simple Network Management Protocol (SNMP) protocol. (1) To ascertain which of the PCQ, RED, and FIFO bandwidth management techniques performs best is the main goal of this study. (2) Is able to forecast how well bandwidth management techniques will function on a network, providing a guide for putting the best techniques into practice. This study included a variety of methodologies, including testing, design, implementation, and analysis. The PCQ method performs better than the RED or FIFO methods when monitored using the SNMP protocol and the Cacti application as an interface. Predictions using multiple linear regression on bandwidth management methods are used to estimate the CPU and memory performance of the PCQ, RED, and FIFO Mikrotik routers that are implemented on the network constructed by researchers. Compared to the prediction accuracy on CPU performance, which has a total average error value of 0.9204, the memory performance prediction accuracy using multiple linear regression is more accurate, with a total average error value of 0.0315. [ABSTRACT FROM AUTHOR]

The seamless integration of intelligent Internet of Things devices with conventional wireless sensor networks has revolutionized data communication for different applications, such as remote health monitoring, industrial monitoring, transportation, and smart agriculture. Efficient and reliable data routing is one of the major challenges in the Internet of Things network due to the heterogeneity of nodes. This paper presents a traffic-aware, cluster-based, and energy-efficient routing protocol that employs traffic-aware and cluster-based techniques to improve the data delivery in such networks. The proposed protocol divides the network into clusters where optimal cluster heads are selected among super and normal nodes based on their residual energies. The protocol considers multi-criteria attributes, i.e. energy, traffic load, and distance parameters to select the next hop for data delivery towards the base station. The performance of the proposed protocol is evaluated through the network simulator NS3.40. For different traffic rates, number of nodes, and different packet sizes, the proposed protocol outperformed LoRaWAN in terms of end-to-end packet delivery ratio, energy consumption, end-to-end delay, and network lifetime. For 100 nodes, the proposed protocol achieved a 13% improvement in packet delivery ratio, 10 ms improvement in delay, and 10 mJ improvement in average energy consumption over LoRaWAN. [ABSTRACT FROM AUTHOR]

Designing smart building IoT applications is a complex task. It requires efficiently integrating a broad number of heterogeneous, low-resource devices that adopt lightweight strategies. IoT frameworks, especially if they are standard-based, may help designers to scaffold the applications. OpenFog, established as IEEE 1934 standard, promotes the use of free open source (FOS) technologies and has been identified for use in smart buildings. However, smart building systems may present vulnerabilities, which can put their integrity at risk. Adopting state-of-the-art security mechanisms in this domain is critical but not trivial. It complicates the design and operation of the applications, increasing the cost of the deployed systems. In addition, difficulties may arise in finding qualified cybersecurity personnel. OpenFog identifies the security requirements of the applications, although it does not describe clearly how to implement them. This article presents a scalable architecture, based on the OpenFog reference architecture, to provide security by design in buildings of different sizes. It adopts FOS technologies over low-cost IoT devices. Moreover, it presents guidelines to help developers create secure applications, even if they are not security experts. It also proposes a selection of technologies in different layers to achieve the security dimensions defined in the X.805 ITU-T recommendation. A proof-of-concept Indoor Environment Quality (IEQ) system, based on low-cost smart nodes, was deployed in the Faculty of Engineering of Vitoria-Gasteiz to illustrate the implementation of the presented approach. The operation of the IEQ system was analyzed using software tools frequently used to find vulnerabilities in IoT applications. The use of state-of-the-art security mechanisms such as encryption, certificates, protocol selection and network partitioning/configuration in the OpenFog-based architecture improves smart building security. [ABSTRACT FROM AUTHOR]

Bluetooth Low Energy Mesh (BLE Mesh) enables Bluetooth flexibility and coverage by introducing Low-Power Nodes (LPNs) and enhanced networking protocol. It is also a commonly used communication method in sensor networks. In BLE Mesh, LPNs are periodically woken to exchange messages in a stop-and-wait way, where the tradeoff between energy and efficiency is a hard problem. Related works have reduced the energy consumption of LPNs mainly in the direction of changing the bearer layer, improving time synchronization and broadcast channel utilization. These algorithms improve communication efficiency; however, they cause energy loss, especially for the LPNs. In this paper, we propose a constrained flooding algorithm based on time series prediction and lightweight GBN (Go-Back-N). On the one hand, the wake-up cycle of the LPNs is determined by the time series prediction of the surrounding load. On the other, LPNs exchange messages through lightweight GBN, which improves the window and ACK mechanisms. Simulation results validate the effectiveness of the Time series Prediction and LlightWeight GBN (TP-LW) algorithm in energy consumption and throughput. Compared with the original algorithm of BLE Mesh, when fewer packets are transmitted, the throughput is increased by 214.71%, and the energy consumption is reduced by 65.14%. [ABSTRACT FROM AUTHOR]

Over the years, there has been a significant surge in the popularity of instant messaging applications (IMAs). However, the message notification functionality in IMAs exhibits certain limitations. Some IMAs fail to alert users about new messages after their phone restarts unless they unlock the phone. This is a consequence of end-to-end encryption (E2EE) and the app not knowing the message is in the queue until the app decrypts it. This approach using E2EE is used to prevent offline attacks, as the key is unavailable to decrypt the notification messages. In this paper, we introduce a novel design and implementation of a message notification protocol for IMAs based on the Signal protocol. The proposed protocol aims to securely display notifications on a locked device and ensures that cryptographic keys are stored in a location that is isolated from the user's device to prevent offline attacks. This approach enhances the security of private key storage, safeguarding private keys against various external threats. The innovative design strengthens the off-site key management system, rendering it resilient against offline attacks and mitigating the risk of key compromise. Additionally, the proposed protocol is highly efficient, requiring no specialized hardware for implementation. It offers confidentiality of cryptographic keys and protection against offline attacks, further enhancing the overall security of the system. We evaluate the protocol's effectiveness by analyzing multiple independent implementations that pass a suite of formal tests via ProVerif. [ABSTRACT FROM AUTHOR]

In this article, we study consensus robustness and performance problems for continuous‐time multi‐agent systems. We consider first‐order unstable agents coordinated by an output feedback protocol over a network subject to an unknown, uncertain constant delay. Our objectives are twofold. First, we seek to determine the largest range of delay permissible so that the agents may achieve robustly consensus despite variation of the delay length, herein referred to as the delay consensus margin. Second, we attempt to determine consensus error performance quantified under an ℋ2$$ {\mathscr{H}}_2 $$ norm criterion, which measures the disruptive effect of random nodal noises on consensus. We consider both undirected and directed graphs. For undirected graphs, we obtain analytical results for the delay consensus margin and the consensus error performance, while for directed graphs, we develop computational results and analytical bounds. The results provide conceptual insights and exhibit how the agents' unstable pole, nonminimum phase zero, as well as the network topology and network delay may limit fundamentally the consensus robustness and performance of first‐order agents. [ABSTRACT FROM AUTHOR]

Underwater wireless sensor networks are gaining popularity since supporting a broad range of applications, both military and civilian. Wireless acoustics is the most widespread technology adopted in underwater networks, the realization of which must face several challenges induced by channel propagation like signal attenuation, multipath and latency. In order to address such issues, the attention of researchers has recently focused on the concept of cooperative communication and networking, borrowed from terrestrial systems and to be conveniently recast in the underwater scenario. In this paper, we present a comprehensive literature review about cooperative underwater wireless sensor networks, investigating how nodes cooperation can be exploited at the different levels of the network protocol stack. Specifically, we review the diversity techniques employable at the physical layer, error and medium access control link layer protocols, and routing strategies defined at the network layer. We also provide numerical results and performance comparisons among the most widespread approaches. Finally, we present the current and future trends in cooperative underwater networks, considering the use of machine learning algorithms to efficiently manage the different aspects of nodes cooperation. [ABSTRACT FROM AUTHOR]

The rapid development of the Industrial Internet of Things (IIoT) and its application across various sectors has led to increased interconnectivity and data sharing between devices and sensors. While this has brought convenience to users, it has also raised concerns about information security, including data security and identity authentication. IIoT devices are particularly vulnerable to attacks due to their lack of robust key management systems, efficient authentication processes, high fault tolerance, and other issues. To address these challenges, technologies such as blockchain and the formal analysis of security protocols can be utilized. And blockchain-based Industrial Internet of Things (BIIoT) is the new direction. These technologies leverage the strengths of cryptography and logical reasoning to provide secure data communication and ensure reliable identity authentication and verification, thereby becoming a crucial support for maintaining the security of the Industrial Internet. In this paper, based on the theory of the strand space attack model, we improved the Fiber Channel Password Authentication Protocol (FACP) security protocol in the network environment based on symmetric cryptography and asymmetric cryptography. Specifically, in view of the problem that the challenge value cannot reach a consensus under the symmetric cryptography system, and the subject identity cannot reach a consensus under the asymmetric cryptography system, an improved protocol is designed and implemented to meet the authentication requirements, and the corresponding attack examples are shown. Finally, the effectiveness and security of the protocol were verified by simulating different networking environments. The improved protocol has shown an increase in efficiency compared with the original protocol across three different network configurations. There was a 6.43% increase in efficiency when centralized devices were connected to centralized devices, a 5.81% increase in efficiency when centralized devices were connected to distributed devices, and a 6.32% increase in efficiency when distributed devices were connected to distributed devices. Experimental results show that this protocol can enhance the security and efficiency of communication between devices and between devices and nodes (servers, disks) in commonly used Ethernet passive optical network (EPON) environments without affecting the identity authentication function. [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]

Reinforcement Learning (RL) has gained significant momentum in the development of network protocols. However, RL-based protocols are still in their infancy, and substantial research is required to build deployable solutions. Developing a protocol based on RL is a complex and challenging process that involves several model design decisions and requires significant training and evaluation in real and simulated network topologies. Network simulators offer an efficient training environment for RL-based protocols because they are deterministic and can run in parallel. In this article, we introduce RayNet, a scalable and adaptable simulation platform for the development of RL-based network protocols. RayNet integrates OMNeT++, a fully programmable network simulator, with Ray/RLlib, a scalable training platform for distributed RL. RayNet facilitates the methodical development of RL-based network protocols so that researchers can focus on the problem at hand and not on implementation details of the learning aspect of their research. We developed a simple RL-based congestion control approach as a proof of concept showcasing that RayNet can be a valuable platform for RL-based research in computer networks, enabling scalable training and evaluation. We compared RayNet with ns3-gym, a platform with similar objectives to RayNet, and showed that RayNet performs better in terms of how fast agents can collect experience in RL environments. [ABSTRACT FROM AUTHOR]

Multipath wireless access aims to seamlessly aggregate multiple access networks to increase data rates and decrease latency. It is currently being standardized through the ATSSS architectural framework as part of the fifth-generation (5G) cellular networks. However, facilitating efficient multi-access communication in next-generation wireless networks poses several challenges due to the complex interplay between congestion control (CC) and packet scheduling. Given that enhanced ATSSS steering functions for traffic splitting advocate the utilization of multi-access tunnels using congestion-controlled multipath network protocols between user equipment and a proxy, addressing the issue of nested CC becomes imperative. In this paper, we evaluate the impact of such nested congestion control loops on throughput over multi-access tunnels using the recently introduced Multipath DCCP (MP-DCCP) tunneling framework. We evaluate different combinations of endpoint and tunnel CC algorithms, including BBR, BBRv2, CUBIC, and NewReno. Using the Cheapest Path First scheduler, we quantify and analyze the impact of the following on the performance of tunnel-based multipath: (1) the location of the multi-access proxy relative to the user; (2) the bottleneck buffer size, and (3) the choice of the congestion control algorithms. Furthermore, our findings demonstrate the superior performance of BBRv2 as a tunnel CC algorithm. [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]

Network protocol implementations, as integral components of information communication, are critically important for security. Due to its efficiency and automation, fuzzing has become a popular method for protocol security detection. However, the existing protocol-fuzzing techniques face the critical problem of generating high-quality inputs. To address the problem, in this paper, we propose MSFuzz, which is a protocol-fuzzing method with message syntax comprehension. The core observation of MSFuzz is that the source code of protocol implementations contains detailed and comprehensive knowledge of the message syntax. Specifically, we leveraged the code-understanding capabilities of large language models to extract the message syntax from the source code and construct message syntax trees. Then, using these syntax trees, we expanded the initial seed corpus and designed a novel syntax-aware mutation strategy to guide the fuzzing. To evaluate the performance of MSFuzz, we compared it with the state-of-the-art (SOTA) protocol fuzzers, namely, AFLNET and CHATAFL. Experimental results showed that compared with AFLNET and CHATAFL, MSFuzz achieved average improvements of 22.53% and 10.04% in the number of states, 60.62% and 19.52% improvements in the number of state transitions, and 29.30% and 23.13% improvements in branch coverage. Additionally, MSFuzz discovered more vulnerabilities than the SOTA fuzzers. [ABSTRACT FROM AUTHOR]

AbstractObjectivesMethodConclusionPeople living with dementia often experience behavioural and psychological symptoms of dementia (BPSD), which severely affect their well-being during the course of the disease. Particularly for BPSD outcomes, there is a high demand for increasing the evidence-based knowledge of non-pharmacological approaches, such as music-based interventions. Although previous reviews emphasize the potential effects of music-based interventions in people with dementia, they cover a wide range of different interventions and outcomes.Therefore, this systematic review (SR) and network meta-analysis (NMA) aims to not only investigate the efficacy of music-based interventions on BPSD, but also to compare the impact of different types of music-based interventions on outcomes. Preferred reporting items for SR and meta-analysis protocols (PRISMA-P) and the PRISMA NMA extension were followed. Several databases will be searched from inception to the date the search will be performed, for relevant randomized or non-randomized controlled trials comparing a music-based intervention with treatment as usual, active controls, or another music-based intervention. Multivariate pairwise meta-analyses will be conducted for each outcome. NMA based on a frequentist random-effects model will be used to estimate the comparative effects of each type of music-based intervention and related components across outcomes. Heterogeneity will be investigated by meta-regression models.Based on our knowledge, this may be the first SR and NMA study to compare the efficacy of different types of music-based interventions. In addition, combined with our multivariate analysis approach, it will allow us to identify potential effect modifiers in music-based intervention for treating BPSD. [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]

The development of underwater acoustic networks is a significant expansion of Internet-of-Things technology to underwater environments. These networks are essential for a variety of marine applications. For many practical uses, it is more efficient to collect marine data from a remote location over multiple hops, rather than direct point-to-point communications. In this article, we will focus on the underwater acoustic string network (UA-SN) designed for this type of application. We propose a Robust and Adaptive Pipeline Medium Access Control (RAP-MAC) protocol to enhance the network's transmission efficiency, adaptability, and robustness. The protocol includes a scheduling-based concurrent algorithm, online real-time configuration adjustment function, a rate mode adaptive algorithm, and a fault recovery algorithm. We conducted simulations to compare the new protocol with another representative protocol, validating the RAP-MAC protocol's adaptability and fault recovery ability. Additionally, we carried out two large-scale sea trials. The results of these experiments indicate that the RAP-MAC protocol ensures effectiveness and reliability in large-scale multihop UA-SNs. In the South China Sea, we were able to achieve a communication distance of 87 km with a throughput of 601.6 bps, exceeding the recognized upper bound of underwater acoustic communication experiment performance by 40 km·kbps. [ABSTRACT FROM AUTHOR]

This paper investigates the distributed optimization problem for a class of nonlinear uncertain multi-agent systems with unmeasured states, switched parameters, and directed communication topologies changing in the control process. To achieve the goal of optimizing the global objective function, a penalty function is constructed through making up of a sum of local objective functions and integrating consensus conditions of the multi-agent systems to utilize local and neighboring information. Radial basis function neural-networks and neural-networks state observer are applied to approximate the unknown nonlinear functions and obtain the unmeasured states, respectively. To avoid "explosion of complexity" and obtain derivatives for virtual control functions continuously, dynamic surface control technology is proposed to develop a distributed adaptive backstepping neural network control protocol to ensure that all the agents' outputs asymptotically reach consensus to the optimal solution of the global objective function. Simulations demonstrate the effectiveness of the proposed control scheme. [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 wireless sensor network (WSN) is one of the most important achievements of the modern technological revolution and greatly affects human life. These networks suffer from some limitations that affect their performance, such as the limited power of their devices. Clustering technology is one of the effective power conservation techniques that improves the performance of WSNs, so this article focuses on developing aggregation technology by proposing an Energy Saving, Multi-hops, Clustering, and Hierarchy (ESMCH) protocol for homogeneous WSNs. The proposed protocol improves clustering technology in several directions. The first direction is by determining the ideal number of cluster head nodes (CHs) suitable for the network, and the second is through the perfect choice of nodes that will represent CHs. The third trend is the selection of secondary CHs. The last trend is the formation of clusters, which depends on an important parameter (distance to CHs). The proposed system uses the TDMA method to schedule the data transfer process to CHs (inside the cluster) and the CSMA method to organize the exchange of data packets between CHs (outside the clusters) for delivery to the base station. The results of simulation experiments in MATLAB R (2020 a) show that the proposed protocol extends network lifetime by 32% compared to the LEACH algorithm and by 26% compared to the SEP algorithm. The results also display that the ESMCH protocol increased the throughput of the WSN by 16.8% compared to its throughput when using the SEP algorithm and by 30% when using the LEACH algorithm. [ABSTRACT FROM AUTHOR]

The focus of this article lies on the notion of the edge version of doubly resolving sets (EVDRSs) in circulant networks. EVDRSs refer to unique edge subsets that are necessary for identifying individual edges in a network and distinguishing them based on their edge distances to the elements of the EVDRS. The main objectives were to define the minimal size of EVDRSs for circulant networks Cn(1, 2) and to investigate their basic properties. The systematic research helped to achieve a new understanding of the existence, construction, and characterization of EVDRSs in circulant networks Cn(1, 2). It is established that the EVDRSs in the circulant network Cn(1, 2) are finite and are bounded by the order of the network. Among the numerous implications of these findings are those that refer to the design and optimization of distributed sensor networks, improving communication and network protocols, as well as tracking the spread of infectious diseases and epidemics over social networks. The application of the identified methodology helps improve the process of network optimization which contributes to the development of more effective and robust circulant-based structures. [ABSTRACT FROM AUTHOR]

The increasing use of cloud services in several areas has led to the growth of data-intensive applications. It is necessary to find ways to enhance the efficiency of communications within the networks of data centers to improve the performance of cloud environments. Explicit Congestion Notification (ECN) is used by Data Center TCP (DCTCP) to enhance congestion control in data center networks. The DCTCP uses ECN to assess the amount of congestion, whereas normal TCP congestion management can simply detect its presence. This paper examines DCTCP using the Random Early Detection (RED) queue management strategy. The evaluation reveals that employing Random Early Detection incurs certain costs. The RED is criticized on the one hand for both short- and medium-term connections due to longer completion time delays compared to typical DCTCP techniques. Because of ECN, DCTCP may maintain small queue sizes. However, because RED uses the average queue size, it penalizes short-lived traffic because it does not reach the bottleneck quickly. An intelligent queue management mechanism with ECN is believed to enhance DCTCP's performance in a cloud-computing environment by predicting sending rates and providing fast feedback on queue length. [ABSTRACT FROM AUTHOR]

In self-forming Mobile Ad Hoc Networks (MANETs), the work introduces dynamic routing for heterogeneous nodes in an infrastructure-limited environment. Military, healthcare, and disaster recovery applications require efficient communication on these networks. Further, multi-hop MANET communication requires reducing packet loss due to energy limits and buffer overflow. The proposed routing mechanism selects energy-efficient, uncongested intermediary nodes and dynamically optimized routes for communication depending on packet loss likelihood. It greatly lowers packet loss, improving network reliability. Our mechanism outperforms energy-aware, buffer-aware, and reactive protocols in network lifetime and packet delivery. We quantify these improvements to verify our mechanism's effectiveness. The proposed mechanism makes MANETs a reliable solution for important applications by proactively optimizing routes to reduce packet loss. [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 the process of collecting evidence of activities and events in network devices, there are problems with content and storage, and we aim to solve the problems faced by network devices in network forensics. In this paper, we propose a simple method for solving the problems with content and storage in acquiring communication logs on end hosts, implement a sniffing tool that captures raw packets with communication event control, compare it with existing tools, and conduct experiments and considerations. Through these experiments and considerations, we confirmed that the proposed communication log acquisition method can be implemented on the end host, and that the problem can be solved by using a tool that implements the proposed method. Also, we confirmed that it can be applied to real-world communication log collection scenarios, and that it can coexist with existing systems and tools that collect communication logs. [ABSTRACT FROM AUTHOR]

In shaft mining, monitoring the deformation of the roadway due to mining pressure is of great significance to the safe production of coal mines. For this reason, a distributed high-density anchor (cable) support force monitoring system was designed by developing a low-cost anchor (cable) stress monitoring device, which consists of an anchor (cable) stress sensor and a data acquisition device. The whole system consists of an anchor bar (cable) stress monitoring device and a mine roadway deformation monitoring substation. The signals collected by the anchor force sensors are processed by the data acquisition device and sent to the self-developed mine roadway deformation monitoring substation through Long Range Radio (LoRa) wireless communication. All data from the monitoring substation are transmitted to the ground control center in real time via the Message Queuing Telemetry Transport (MQTT) network transmission protocol. The distributed high-density arrangement of monitoring nodes reflects the deformation trend of the whole section of the roadway by monitoring the anchor bar (cable) support force data of multiple sections, which effectively ensures the safety of the roadway. [ABSTRACT FROM AUTHOR]

This paper proposes a new H ∞ static output feedback control method to address the congestion control problem in transmission control protocol networks using active queue management routers. Based on linear matrix inequality optimization, this method determines a static output feedback control law to minimize the H ∞ norm of the transfer function between the controlled queue length of the buffer and the exogenous disturbance affecting the available link bandwidth. A linear matrix inequality formulation is presented as a sufficient condition to guarantee the closed-loop system's asymptotic stability while maintaining disturbance rejection within a specified level, regardless of round-trip time delays. The proposed robust static output feedback control eliminates the need to measure or estimate all system states, thus simplifying practical implementation. The effectiveness of the proposed design method is demonstrated by applying it in a practical process, as illustrated through a numerical example. [ABSTRACT FROM AUTHOR]

Summary: IoT‐assisted WSN contains various nodes, which are placed on a huge scale that increases complications. Thus, the challenges and issues of these networks fluctuate as compared to WSNs. Hence, sensor nodes are imperative unit that runs on less energy resources. Hence, devising a robust and energy‐effective protocol for increasing network lifetime is a complex task. This paper devises a novel hybrid optimization‐driven approach for selecting cluster head (CH) in IoT‐assisted WSNs. Initially, the simulation of IoT nodes is done by configuration. Thereafter, the Cluster Head selection is done using a newly devised optimization technique, namely the Taylor‐Political optimizer (Taylor‐PO). Thus, fitness is newly developed by adapting certain attributes like energy, delay, inter and intra‐cluster distance, Link Lifetime (LLT), predicted energy, and delay. Here, the multipath routing is accomplished using Tunicate Swarm gray wolf optimization (TSGWO). Thus, the proposed Taylor‐PO is offered for effective Cluster Head selection along with multipath routing using TSGWO. The proposed Taylor‐PO offered improved performance with smallest delay of 0.006 sec, highest energy of 2.368 J, highest throughput of 494.043 kbps. [ABSTRACT FROM AUTHOR]

Internet of things (IoT) applications from home applications to military applications have been expanding day by day. Energy efficient routing schemes are vital for resource constraint wireless sensor networks (WSNs) and IoT. Clustering based routing scheme is one of the basic methods to extend the lifetime of WSN-based IoT. On the other hand, clustering is NP-hard problem and metaheuristic algorithms are suitable for clustering. In this paper, a new energy-efficient routing scheme is presented for IoT using two metaheuristic algorithms Harris hawk's optimization (HHO) and whale optimization algorithm (WOA). The selection of the cluster header (CH) is based on the WOA using various parameters such as residual energy of nodes, distance to neighbors, distance to sink. After clustering phase, an energy efficient routing scheme was proposed using the HHO algorithm. The simulation results in MATLAB environment justifies that the proposed protocol improves network life by 10%, average energy consumption by 15%, packet delivery rate (PDR) by 12%, throughput by 11% and number of alive nodes by 15%. [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]

The burgeoning interest in intelligent transportation systems (ITS) and the widespread adoption of in-vehicle amenities like infotainment have spurred a heightened fascination with vehicular ad-hoc networks (VANETs). Multi-hop routing protocols are pivotal in actualizing these in-vehicle services, such as infotainment, wirelessly. This study presents a novel protocol called multiple junction-based traffic-aware routing (MJTAR) for VANET vehicles operating in urban environments. MJTAR represents an advancement over the improved greedy traffic-aware routing (GyTAR) protocol. MJTAR introduces a distributed mechanism capable of recognizing vehicle traffic and computing curve metric distances based on two-hop junctions. Additionally, it employs a technique to dynamically select the most optimal multiple junctions between source and destination using the ant colony optimization (ACO) algorithm. We implemented the proposed protocol using the network simulator 3 (NS-3) and simulation of urban mobility (SUMO) simulators and conducted performance evaluations by comparing it with GSR and GyTAR. Our evaluation demonstrates that the proposed protocol surpasses GSR and GyTAR by over 20% in terms of packet delivery ratio, with the end-to-end delay reduced to less than 1.3 s on average. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) networks always operate within the context of diverse and constrained characteristics of the devices. Low-Power and Lossy Networks (LLNs) constitute a network architecture commonly utilized in IoT application deployments, facilitating networking and the establishment of paths for data transmission. The Routing Protocol for Low-Power and Lossy Networks (RPL) demonstrates promising capabilities for LLN network operations, supporting IPv4 and IPv6-enabled services. The RPL protocol constructs a Destination Oriented Directed Acyclic Graph (DODAG) logical routing topology based on defined Objective Function (OF) metrics. Routing operations within the DODAG utilize these metrics and constraints to select parent nodes and calculate optimal routes between two nodes. Standardized OFs have traditionally focused on either parent node selection or routing objectives within the DODAG, often treating load balancing and bottleneck optimization separately. However, their combined impact on RPL's effectiveness has been overlooked. This paper introduces an Adaptively Composite Objective Function (AC-OF) approach that considers the combined objectives of DODAG load balancing and optimized routing operations. Through simulation evidence, the paper presents improved network parameters. The AC-OF implementation brings out significant results in the form of a balanced DODAG topology and it has good impacts on data transmission, control overhead messages, parent switching, delay, energy consumption, and node lifetime. [ABSTRACT FROM AUTHOR]

The visual information processing technology based on deep learning can play many important yet assistant roles for unmanned aerial vehicles (UAV) navigation in complex environments. Traditional centralized architectures usually rely on a cloud server to perform model inference tasks, which can lead to long communication latency. Using transfer learning to unload deep neural networks to the edge-fog collaborative networks has become a new paradigm for dealing with the conflicts between computing resources and communication latency. However, ensuring the security of edge-fog collaborative networks entity remains challenging. For such, we propose an anonymous authentication and group key agreement scheme for the UAV-enabled edge-fog collaborative networks, consisting of the UAV authentication protocol and the collaborative networks authentication protocol. Utilizing the AVISPA assessment tool and security analysis, the security requirements and functional features of the proposed scheme are demonstrated. From the performance results of the proposed scheme, we show that it is superior to existing authentication schemes and promising. [ABSTRACT FROM AUTHOR]

Communication presents a critical challenge for emerging intermittently powered batteryless sensors. Batteryless devices that operate entirely on harvested energy often experience frequent, unpredictable power outages and have trouble keeping time accurately. Consequently, effective communication using today's low-power wireless network standards and protocols becomes difficult, particularly because existing standards are usually designed to support reliably powered devices with predictable node availability and accurate timekeeping capabilities for connection and congestion management. In this article, we present Greentooth, a robust and energy-efficient wireless communication protocol for intermittently powered sensor networks. It enables reliable communication between a receiver and multiple batteryless sensors using Time Division Multiple Access–style scheduling and low-power wake-up radios for synchronization. Greentooth employs lightweight and energy-efficient connections that are resilient to transient power outages, while significantly improving network reliability, throughput, and energy efficiency of both the battery-free sensor nodes and the receiver—which could be untethered and energy constrained. We evaluate Greentooth using a custom-built batteryless sensor prototype on synthetic and real-world energy traces recorded from different locations in a garden across different times of the day. Results show that Greentooth achieves 73% and 283% more throughput compared to Asynchronous Wake-up on Demand MAC and Receiver-Initiated Consecutive Packet Transmission Wake-up Radios, respectively, under intermittent ambient solar energy and over 2× longer receiver lifetime. [ABSTRACT FROM AUTHOR]

In a world where digitization is rapidly advancing, the security and privacy of intra-domain communication within organizations are of critical concern. The imperative to secure communication channels among physical systems has led to the deployment of various security approaches aimed at fortifying networking protocols. However, these approaches have typically been designed to secure protocols individually, lacking a holistic perspective on the broader challenge of intra-domain communication security. This omission raises fundamental concerns about the safety and integrity of intra-domain environments, where all communication occurs within a single domain. As a result, this paper introduces HSM4SSL, a comprehensive solution designed to address the evolving challenges of secure data transmission in intra-domain environments. By leveraging hardware security modules (HSMs), HSM4SSL aims to utilize the Secure Socket Layer (SSL) protocol within intra-domain environments to ensure data confidentiality, authentication, and integrity. In addition, solutions proposed by academic researchers and in the industry have not addressed the issue in a holistic and integrative manner, as they only apply to specific types of environments or servers and do not utilize all cryptographic operations for robust security. Thus, HSM4SSL bridges this gap by offering a unified and comprehensive solution that includes certificate management, key management practices, and various security services. HSM4SSL comprises three layers to provide a standardized interaction between software applications and HSMs. A performance evaluation was conducted comparing HSM4SSL with a benchmark tool for cryptographic operations. The results indicate that HSM4SSL achieved 33% higher requests per second (RPS) compared to OpenSSL, along with a 13% lower latency rate. Additionally, HSM4SSL efficiently utilizes CPU and network resources, outperforming OpenSSL in various aspects. These findings highlight the effectiveness and reliability of HSM4SSL in providing secure communication within intra-domain environments, thus addressing the pressing need for enhanced security mechanisms. [ABSTRACT FROM AUTHOR]

FIDO2 authentication is starting to be applied in numerous web authentication services, aiming to replace passwords and their known vulnerabilities. However, this new authentication method has not been integrated yet with network authentication systems. In this paper, we introduce FIDO2CAP: FIDO2 Captive-portal Authentication Protocol. Our proposal describes a novel protocol for captive-portal network authentication using FIDO2 Authenticators as security keys and passkeys. For validating our proposal, we have developed a prototype of FIDO2CAP authentication in a mock scenario. Using this prototype, we performed a usability experiment with 15 real users. This work makes the first systematic approach for adapting network authentication to the new authentication paradigm relying on FIDO2 authentication. [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]

The rapid development of mobile communication devices has brought challenges to wireless networks, where data packets are able to organize and maintain local area networks more freely without the constraints of wired devices. Scholars have developed diverse network protocols on how to ensure data transmission while maintaining its self-organizational nature. However, it is difficult for traditional network protocols to meet the needs of increasingly complex networks. In order to solve the problem that the better node set may not be selected when selecting the node set responsible for forwarding in the traditional OLSR protocol, a multi-objective optimized OLSR algorithm is proposed in this paper, which incorporating a new MPR mechanism and an improved NSGA-II algorithm. In the process of route discovery, the intermediate nodes responsible for forwarding packets are determined by the new MPR mechanism, and then the main parameters in the OLSR protocol are provided by the multi-objective optimization algorithm. Matlab was used to build a self-organizing network in this study. In addition, the conventional OLSR protocol, NSGA-II algorithm and multi-objective simulated annealing algorithm are selected to compare with the proposed algorithm. Simulation results show that the proposed algorithm can effectively reduce packet loss and end-to-end delay while obtaining better results in HV and Spacing, two multi-objective optimization result evaluation metrics. [ABSTRACT FROM AUTHOR]

It is well known that control effort is the key factor considered in formation control of a multi‐agent system (MAS). To reduce the controller effort, an economic event‐triggered super twisting control (STC) protocol for the formation tracking of a nonlinear MAS, which avoids the unnecessary computations and transmission of control inputs among agents. Specifically, a distributed leader‐follower control framework, combing the multi‐input STC with event‐triggered strategy, is proposed to ensure that the followers' states reach an agreement on the leaders state. Then, the sufficient conditions for the selection of controller parameters are formulated in terms of linear matrix inequalities (LMIs). On this basis, the event‐triggered conditions for implementing the STC protocol in the network environment are obtained using Lyapunov stability theory. Simulation study is carried out to demonstrate the effectiveness and merits of the STC in terms of formation construction, trajectory tracking, and robustness to system uncertainties. [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]