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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]

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]

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 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]

Background: Previous studies have found that psychological interventions have a positive effect on improving physical and psychological problems in colorectal cancer survivors. However, there is still a lack of high-quality evidence reviews that summarize and compare the impact of different psychological interventions. The aim of this study was to synthesize existing psychological interventions and use network meta-analysis to explore whether psychological interventions improve anxiety, depression, fatigue and quality of life in colorectal cancer (CRC) survivors. Methods: We will extract relevant randomized controlled trials of psychological interventions for CRC survivors from eight electronic databases, including PubMed, Embase, The Cochrane Library, Web of Science, CINAHL, PsycInFO, CNKI, and Wanfang database. Two reviewers will independently screen the literature and extract data. The risk of bias of the included studies will be assessed using the RoB2: Revised Cochrane Risk of Bias Tool. We will then conduct paired meta-analyses and network meta-analyses of the extracted data, using a frequency-based framework and random effects models. Discussion: To the best of our knowledge, this study is the first proposed qualitative and quantitative integration of existing evidence using systematic evaluation and network meta-analysis. This study will inform health policy makers, healthcare providers' clinical intervention choices and guideline revisions, and will help to reduce depression and anxiety in CRC survivors, reduce fatigue, improve quality of life. [ABSTRACT FROM AUTHOR]

Assessing the content of learners' compositions is a common practice in second language (L2) writing assessment. However, the construct definition of content in L2 writing assessment potentially underrepresents the target competence in content and language integrated learning (CLIL), which aims to foster not only L2 proficiency but also critical thinking skills and subject knowledge. This study aims to conceptualize the construct of content in CLIL by exploring subject specialists' perspectives on essays' content quality in a CLIL context. Eleven researchers of English as a lingua franca (ELF) rated the content quality of research-based argumentative essays on ELF submitted in a CLIL course and produced think-aloud protocols. This study explored some essay features that have not been considered relevant in language assessment but are essential in the CLIL context, including the accuracy of the content, presence and quality of research, and presence of elements required in academic essays. Furthermore, the findings of this study confirmed that the components of content often addressed in language assessment (e.g., elaboration and logicality) are pertinent to writing assessment in CLIL. The manner in which subject specialists construe the content quality of essays on their specialized discipline can deepen the current understanding of content in CLIL. [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]

Vehicle‐to‐grid (V2G) network has a clear advantage in terms of economic advantages, it has attracted the interest of electric vehicle (EV) and power grid users. However, numerous security concerns limit its further progress. In existing V2G protocols a trusted third party independently generates the master key of the system, so if the adversary compromises the third party, then the system may become vulnerable to system master key leakage attack. Recently, Su et al. presented a privacy‐preserving mutual authentication protocol for V2G networks. Firstly, we crypt‐analysis Su et al.'s protocol and show that their protocol is vulnerable to several security attacks such as the reveal of the master secret key, impersonation attacks and the incorrect notion of EV's anonymity and traceability and does not meet the security features they claimed in their paper. Secondly, we verify that Su et al.'s protocol is unsafe against impersonation attacks, system key leakage, and electrical vehicle anonymity attack using the AVISPA tool. [ABSTRACT FROM AUTHOR]

A botnet is a collection of Internet-connected computers that have been suborned and are controlled externally for malicious purposes. Concomitant with the growth of the Internet of Things (IoT), botnets have been expanding to use IoT devices as their attack vectors. IoT devices utilise specific protocols and network topologies distinct from conventional computers that may render detection techniques ineffective on compromised IoT devices. This paper describes experiments involving the acquisition of several traditional botnet detection techniques, BotMiner, BotProbe, and BotHunter, to evaluate their capabilities when applied to IoT-based botnets. Multiple simulation environments, using internally developed network traffic generation software, were created to test these techniques on traditional and IoT-based networks, with multiple scenarios differentiated by the total number of hosts, the total number of infected hosts, the botnet command and control (CnC) type, and the presence of aberrant activity. Externally acquired datasets were also used to further test and validate the capabilities of each botnet detection technique. The results indicated, contrary to expectations, that BotMiner and BotProbe were able to detect IoT-based botnets—though they exhibited certain limitations specific to their operation. The results show that traditional botnet detection techniques are capable of detecting IoT-based botnets and that the different techniques may offer capabilities that complement one another. [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]

Time synchronization is vital for accurate data collection and processing in sensor networks. Sensors in these networks often operate under fluctuating conditions. However, an accurate timekeeping mechanism is critical even in varying network conditions. Consequently, a synchronization method is required in sensor networks to ensure reliable timekeeping for correlating data accurately across the network. In this research, we present a novel dynamic NTP (Network Time Protocol) algorithm that significantly enhances the precision and reliability of the generalized NTP protocol. It incorporates a dynamic mechanism to determine the Round-Trip Time (RTT), which allows accurate timekeeping even in varying network conditions. The proposed approach has been implemented on an FPGA and a comprehensive performance analysis has been made, comparing three distinct NTP methods: dynamic NTP (DNTP), static NTP (SNTP), and GPS-based NTP (GNTP). As a result, key performance metrics such as variance, standard deviation, mean, and median accuracy have been evaluated. Our findings demonstrate that DNTP is markedly superior in dynamic network scenarios, a common characteristic in sensor networks. This adaptability is important for sensors installed in time-critical networks, such as real-time industrial IoTs, where precise and reliable time synchronization is necessary. [ABSTRACT FROM AUTHOR]

The industrial control and automation sector has invested in the development and standardization of new wireless (WirelessHART, ISA 100.11a, and WIA-PA) and wired (Profibus/Profinet, Modbus, and LonWORK) solutions aimed at automating processes to support standard monitoring and control functions from the perspective of addressing critical applications, as well as those integrated within the Building Internet of Things (BIoT) concept. Distributed data acquisition and control systems allow modern installations to monitor and control devices remotely. Various network protocols have been proposed to specify communication formats between a client/gateway and server devices, with Modbus being an example that has been widely implemented in the latest industrial electrical installations. The main contribution made in this paper concerns the completion of the Modbus Extension (ModbusE) specifications for the server station in the classical Modbus communication architecture, as well as their implementation and testing in an STM32F4 kit. A general-purpose control architecture is proposed for BIoT sector, comprising both intelligent touch switches and communication protocols of which the Modbus protocol is used extensively for the monitoring and control part, especially between clients, smart switches, and devices. The specific contributions concern the presentation of a scientific and practical implementation of improved specifications and their integration as software modules on ModbusE protocol server stations. A client station with a VirtualComm USB PC connection is also implemented in the lab to test the operation of the proposed server with specific Modbus applications. [ABSTRACT FROM AUTHOR]

With the development of IoT technology and the improvement of people's living standards, smart locks have become prevalent in ordinary households. However, for enterprises and institutions requiring unified management and control capabilities for networked smart locks, the technology has been relatively lagging, and there is a lack of established brands. Existing products are mostly based on wireless low-power network protocols, leading to common issues of low stability, limited network scalability, and high maintenance efforts. This paper addresses the problems existing in current networked lock systems and leverages the centralized office characteristics of enterprises and institutions. By integrating IoT technology and Power over Ethernet- (PoE-) centralized power supply, we have developed a networked smart lock system with unified management and control capabilities. This system is primarily designed for applications in offices, collective dormitories, and hotels of enterprises, institutions, and schools. The test results demonstrate that even with a scale of over tens of thousands of networked locks under unified control, the system maintains fast response times and low packet loss rates. It also incorporates energy-saving and environmentally friendly features, as well as easy automatic updates, facilitating convenient postdeployment maintenance. Thus, it effectively meets the requirements for centralized management and control in different application scenarios with centralized use of rooms. In conclusion, this research has led to the development of a unified management and control networked smart lock system, which is well suited for enterprises, institutions, and schools. Its scalability, speed, energy efficiency, and ease of maintenance make it an excellent solution for various application scenarios requiring centralized management and control of access. [ABSTRACT FROM AUTHOR]

Background: VCI is a severe public health problem facing the world today. In addition to pharmacological treatment, non-invasive neuromodulation techniques have also been effective. At this stage, non-invasive neuromodulation techniques combined with pharmacological treatment are the mainstay of clinical treatment, and clinical trials are continuing to be conducted, which is becoming the direction of treatment for VCI. Therefore, we outline this systematic review and network meta-analysis protocol to evaluate and rank clinical data in future studies which can develop optimal protocols for the clinical treatment of VCI with non-invasive neuromodulation techniques in combination with drugs. Methods: The network meta-analysis will search eight databases, including PubMed, Embase, Cochrane Library, Web of Science, China Knowledge Infrastructure Library (CNKI), China Biology Medicine disc (CBM)), Wanfang Data Knowledge Service Platform and Vipshop Journal Service Platform (VIP), for a period of from the establishment of the library to January 30 2022. The quality of the studies will be evaluated using the Cochrane Review's Handbook 5.1 and the PEDro scale to assess the evidence and quality of the included randomised controlled trials. Risk of bias assessment and heterogeneity tests will be performed using the Review Manager 5.4 program, and Bayesian network meta-analysis will be performed using the Stata 16.0 and WinBUGS 1.4.3 program. Results: The results of the network meta-analysis will be published in a peer-reviewed journal. Conclusions: Our study is expected to provide high quality evidence-based medical evidence for the treatment of VCI by clinicians. Trial registration: PROSPERO:CRD42022308580. [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]

Background Postoperative shunt infection is a nightmare in neurosurgical practice with additional morbidity and mortality. A lot of protocols have contributed to the reduction of ventriculoperitoneal shunt (VPS) infections but not eradication. The aim of the study was to evaluate the rigid application of a modified Hydrocephalus Clinical Research Network (HCRN) protocol in the prevention of postoperative shunt infection. Methods We retrospectively evaluated children with congenital hydrocephalus who underwent VPS insertion, and in whom the protocol was applied from June 2019 to January 2020. Follow-up ranged from 11 to 24 months. Results Thirty-seven procedures were performed including 35 primary shunt insertions and two revision surgeries. The median age was 5 months (range, 1–30 months), and 25 patients were males. The most common cause for VPS placement was congenital hydrocephalus without identifiable cause in 28 cases (80%). The endoscope-assisted technique was used in the insertion of the proximal end in six cases (17%). The mean follow-up was 19.4 months (11–24 months). The rate of shunt infection was 0% till the last follow-up. Conclusion The preliminary results showed an effective method for the prevention of postoperative shunt infections using the modified protocol. These initial findings need to be validated in a large prospective study before widespread application can be recommended. [ABSTRACT FROM AUTHOR]

The complexity and isomerization of communication networks have put forth new requirements for cryptographic schemes to ensure the operation of network security protocols. Robust cryptographic schemes have been gradually favored. The robust initialization vector (RIV) instead of the synthetic initialization vector (SIV) was first introduced to support strong security and robust authenticated encryption. This paper first introduces RIV to GCM-SIV1, proposes a robust variant, GCM-RIV1, and proves that it ensures birthday-bound subtle AE (SAE) security and nonce-misuse resistance. Then, to support beyond-birthday-bound (BBB) security with graceful degradation, we introduce another, stronger security variant, GCM-RIV2, and prove that it allows gracefully degrading BBB SAE security in the faulty nonce setting. Finally, the performance of GCM-RIV1 and GCM-RIV2 is discussed and compared. [ABSTRACT FROM AUTHOR]

Fifth-generation (5G) and beyond networks are expected to serve large numbers of user equipments (UEs). Grant-based random access (RA) protocols are efficient when serving human users, typically with large data volumes to transmit. The strongest user collision resolution (SUCRe) is the first protocol that effectively uses the many antennas at the 5G base station (BS) to improve connectivity performance. In this paper, our proposal involves substituting the retransmission rule of the SUCRe protocol with a neural network (NN) to enhance the identification of the strongest user and resolve collisions in a decentralized manner on the UEs' side. The proposed NN-based procedure is trained offline, admitting different congestion levels of the system, aiming to obtain a single setup able to operate with different numbers of UEs. The numerical results indicate that our method attains substantial connectivity performance improvements compared to other protocols without requiring additional complexity or overhead. In addition, the proposed approach is robust regarding variations in the number of BS antennas and transmission power while improving energy efficiency by requiring fewer attempts on the RA stage. [ABSTRACT FROM AUTHOR]

Address Resolution Protocol (ARP) is used to resolve a host’s MAC address, given its IP address. ARP is stateless, as there is no authentication when exchanging a MAC address between the hosts. Hacking tactics using ARP spoofing are constantly being abused differently; many previous studies have prevented such attacks. However, prevention requires modification of the underlying network protocol or additional expensive equipment, so applying these methods to the existing network can be challenging. In this paper, we examine the limitations of previous research in preventing ARP spoofing. In addition, we propose a defence mechanism that does not require network protocol changes or expensive equipment. Before sending or receiving a packet to or from any device on the network, our method checks the MAC and IP addresses to ensure they are correct. It protects users from ARP spoofing. The findings demonstrate that the proposed method is secure, efficient, and very efficient against various threat scenarios. It also makes authentication safe and easy and ensures data and users’ privacy, integrity, and anonymity through strong encryption techniques. [ABSTRACT FROM AUTHOR]

Background: Vitreous hemorrhage from proliferative diabetic retinopathy can cause severe vision loss. DRCR Retina Network Protocol AB was a randomized clinical trial comparing intravitreal aflibercept versus vitrectomy with panretinal photocoagulation and found no difference in the average rate of visual recovery over 104 weeks. Herein, we describe patient-reported outcome measures from Protocol AB. Methods: Secondary analysis of a multicenter (39 sites) randomized clinical trial. The Work Productivity and Activity Impairment Questionnaire was administered at 4, 12, 24, 36, 52, 68, 84, and 104 weeks. Main outcomes were mean change in activity impairment and work productivity loss over 24 and 104 weeks (area under the curve). Results: Mean (SD) activity impairment at baseline was 58% (27%) in the aflibercept group (N = 99) and 56% (30%) in the vitrectomy group (N = 105). The mean reduction in activity impairment from baseline over 24 weeks was 21% (25%) in the aflibercept group and 27% (31%) in the vitrectomy group (adjusted difference = -6.8% [95% CI, -12.7% to -0.9%], P =.02); over 104 weeks, the adjusted mean difference was -3.1% (95% CI, -9.2% to 3.0%, P =.31). Mean work productivity loss at baseline was 51% (28%) in the aflibercept group (N = 44) and 58% (30%) in the vitrectomy group (N = 43). The mean reduction in work productivity loss from baseline over 24 weeks (area under the curve) was 19% (23%) in the aflibercept group and 31% (24%) in the vitrectomy group (adjusted difference = -8.3% [95% CI, -16.8% to 0.2%], P =.06); over 104 weeks, the adjusted mean difference was -9.1% (95% CI, -18.4% to 0.2%, P =.05). Conclusions: Participants with vitreous hemorrhage from proliferative diabetic retinopathy had less activity impairment over 24 weeks when treated initially with vitrectomy and panretinal photocoagulation versus intravitreal aflibercept. The trend was similar for work productivity but not statistically significant. By 104 weeks, the improvements were similar in the two treatment groups. Trial registration: ClinicalTrials.gov NCT02858076. [ABSTRACT FROM AUTHOR]

Background: The purpose of this network meta-analysis (NMA) is to investigate the efficacy of pharmacological and non-pharmacological therapy on pain intensity and disability of older people with chronic nonspecific low back pain, providing comprehensive evidence for an informed decision-making. Methods: We will perform a systematic search to identify randomized controlled trials of pharmacological and non-pharmacological interventions for older people with chronic nonspecific low back pain. MEDLINE, Cochrane Library, Embase, AMED, PsycINFO, and PEDro will be searched without language or date restrictions. Our primary outcomes are pain intensity and disability. Risk of bias will be assessed for all studies using the revised Cochrane risk-of-bias (RoB) tool 2.0. For each pairwise comparison between the different interventions, estimated mean differences and their 95% confidence intervals will be presented. Standard pairwise meta-analyses will be performed using random effects models in STATA version 16. The competing interventions will be ranked using the surface under the cumulative ranking curve (SUCRA) for the outcomes of interest at short and long terms. The confidence in the results from NMA will be assessed using the Confidence in Network Meta‐Analysis (CINeMA) framework. Discussion: This NMA compares efficacy of interventions for nonspecific chronic low back pain in older people. It will provide reliable evidence for patients, clinicians, stakeholders, and researchers in this field where competing therapies, many of extraordinarily little value, are commonly used in clinical practice. Systematic review registration: PROSPERO CRD42022312565 [ABSTRACT FROM AUTHOR]

This survey presents various insights on the IoT system and its architecture used to implement a smart health-care system, along with the implementation of the latest technologies such as Cloud Computing for storing data, Machine Learning for predicting various diseases. These technologies are also used to improve the existing management and administration system in hospitals. Various solutions for tackling the health-care crisis have been proposed most of them sound promising but a practical low-cost implementation and feasibility of IoT and ML integrated system is yet to be designed. The present chapter also deals with the standard protocols designed for body area networks for health monitoring applications. The IEEE 802.15.6 standard is used for the body area network which provides high data rate and low-range communication. The integration of the standard body area network protocols with 5G technology can be used for high throughput real-time reliable operations. [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]

The user datagram protocol is the most widely used protocol for streaming multimedia data over the Internet. Like other protocols at the network and transport layers, it uses the Internet Checksum (IC) to detect channel errors. The consequence of this is that each corrupted packet is dropped, which can degrade the quality of service perceived by a user. In this paper, the authors present a solution to this problem based on integer codes capable of correcting single and double adjacent errors. The presented codes are a generalization of the IC, which makes them easy to implement in software. [ABSTRACT FROM AUTHOR]

A new series of transparent aerogels of biopolymer‐polysiloxane double networks is reported. Biopolymer aerogels have attracted much attention from green and sustainable aspects but suffered from strong hydrophilicity and difficulty to make homogeneous structures in nanoscale; these drawbacks are overcome by compositing with a polysiloxane network. Alginate‐polymethylsilsesquioxane aerogel has high optical transparency, water repellency, comparable superinsulation property and improved bending flexibility compared to pure polymethylsilsesquioxane aerogel. The nanoscale homogeneity is realized by separating the crosslinking steps for two networks in a sequential protocol: condensation of siloxane bonds and metal‐crosslinking of biopolymer. The crosslinking order, biopolymer‐first or siloxane‐first, and universality/limitation of biopolymer‐crosslinker pairs are discussed to construct fundamental chemistry of double network systems for their further application potentials. [ABSTRACT FROM AUTHOR]

A new series of transparent aerogels of biopolymer‐polysiloxane double networks is reported. Biopolymer aerogels have attracted much attention from green and sustainable aspects but suffered from strong hydrophilicity and difficulty to make homogeneous structures in nanoscale; these drawbacks are overcome by compositing with a polysiloxane network. Alginate‐polymethylsilsesquioxane aerogel has high optical transparency, water repellency, comparable superinsulation property and improved bending flexibility compared to pure polymethylsilsesquioxane aerogel. The nanoscale homogeneity is realized by separating the crosslinking steps for two networks in a sequential protocol: condensation of siloxane bonds and metal‐crosslinking of biopolymer. The crosslinking order, biopolymer‐first or siloxane‐first, and universality/limitation of biopolymer‐crosslinker pairs are discussed to construct fundamental chemistry of double network systems for their further application potentials. [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]

With the ability to transfer and process quantum information, large-scale quantum networks will enable a suite of fundamentally new applications, from quantum communications to distributed sensing, metrology, and computing. This Perspective reviews requirements for quantum network nodes and color centers in diamond as suitable node candidates. We give a brief overview of state-of-the-art quantum network experiments employing color centers in diamond and discuss future research directions, focusing, in particular, on the control and coherence of qubits that distribute and store entangled states, and on efficient spin–photon interfaces. We discuss a route toward large-scale integrated devices combining color centers in diamond with other photonic materials and give an outlook toward realistic future quantum network protocol implementations and applications. [ABSTRACT FROM AUTHOR]

Industry 4.0 has significantly improved the industrial manufacturing scenario in recent years. The Industrial Internet of Things (IIoT) enables the creation of globally interconnected smart factories, where constituent elements seamlessly exchange information. Industry 5.0 has further complemented these achievements, as it focuses on a human-centric approach where humans become part of this network of things, leading to a robust human–machine interaction. In this distributed, dynamic, and highly interconnected environment, functional safety is essential for adequately protecting people and machinery. The increasing availability of wireless networks makes it possible to implement distributed and flexible functional safety systems. However, such networks are known for introducing unwanted delays that can lead to safety performance degradation due to their inherent uncertainty. In this context, the Time-Sensitive Networking (TSN) standards present an attractive prospect for enhancing and ensuring acceptable behaviors. The research presented in this paper deals with the introduction of TSN to implement functional safety protocols for wireless networks. Among the available solutions, we selected Wi-Fi since it is a widespread network, often considered and deployed for industrial applications. The introduction of a reference functional safety protocol is detailed, along with an analysis of how TSN can enhance its behavior by evaluating relevant performance indexes. The evaluation pertains to a standard case study of an industrial warehouse, tested through practical simulations. The results demonstrate that TSN provides notable advantages, but it requires meticulous coordination with the Wi-Fi MAC layer protocol to guarantee improved performance. [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]

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]

Internet of Things (IoT) is a smart technology that allows communication between humans and all things that contain sensors, actuators, embedded electronics, software, or storage via the internet. As a result, IoT should be seen as a part of the overall Internet of the future, which is likely to be very different from what we are using today. Despite the advantages of IoT, energy efficiency is still considered one of the main challenges in IoT. There are many algorithms that have been proposed to solve the energy efficiency problem. Unfortunately, most of them have some drawbacks. As a result, an Enhanced Threshold Sensitive Distributed Energy-Efficient Clustering routing protocol (ETSDEEC) for WSN-based IoT was proposed in this paper. Hard and soft thresholds are used in the proposed protocol to determine whether nodes are allowed to send their sensed data. From the simulation, we found that the proposed ETSDEEC protocol performs better than EDEEC and TDEEC protocols in terms of network lifetime, energy dissipationand throughput. It is also found that the proposed ETSDEEC can improve the lifetime by 59.8% in comparison to EDEEC and about 37.7% in comparison to TDEEC protocols. [ABSTRACT FROM AUTHOR]

The rapid evolution of 5G and beyond technologies has sparked an unprecedented surge in the need for networking infrastructure that can deliver high speed, minimal latency, and remarkable flexibility. The programmable data plane, which enables the dynamic reconfiguration of network functions and protocols, is becoming increasingly important in meeting these requirements. This paper provides an overview of the current state of the art in programmable data planes implemented in 5G and beyond architectures. It proposes a classification of the reviewed studies based on system architecture and specific use cases. Furthermore, the article surveys the primary applications of programmable devices in emerging telecommunication networks, such as tunneling and forwarding, network slicing, cybersecurity, and in-band telemetry. Finally, this publication summarizes the open research challenges and future directions. In addition to offering a comprehensive review of programmable data plane applications in telecommunication networks, this article aims to guide further research in this promising field for network operators and researchers alike. [ABSTRACT FROM AUTHOR]

This paper investigates an observer-based state estimation issue for discrete-time semi-Markovian jump neural networks with Round-Robin protocol and cyber attacks. In order to avoid the network congestion and save the communication resources, the Round-Robin protocol is used to schedule the data transmissions over the networks. Specifically, the cyber attacks are modeled as a set of random variables satisfying the Bernoulli distribution. On the basis of the Lyapunov functional and the discrete Wirtinger-based inequality technique, some sufficient conditions are established to guarantee the dissipativity performance and mean square exponential stability of the argument system. In order to compute the estimator gain parameters, a linear matrix inequality approach is utilized. Finally, two illustrative examples are provided to demonstrate the effectiveness of the proposed state estimation algorithm. [ABSTRACT FROM AUTHOR]

Summary: Human‐centered Internet of things (IoT) systems enable human beings to enjoy the ubiquitous services and play more and more important roles in our life. A common application scenario in human‐centered IoT systems is that two distributed wireless devices from heterogeneous networks want to communicate with each other. However, key generation centers (KGCs) from different networks usually use independent security parameters. It is difficult for two users with different security parameters to establish a common session key. We propose a certificateless key exchange protocol for two different devices managed by different KGCs to address the issue. The security of the proposed protocol is conducted in the random oracle model with the hardness assumption of elliptic curve computational Diffie‐Hellman (ECDH) problem. The main merits of our protocol include the following: (a) it enables users from heterogeneous networks to establish upon a shared session key, (b) it can solve the key escrow problem, (c) it does not use bilinear pairings and obtains computational efficiency, and (d) it achieves stronger security compared with other related protocols. [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]

In the current research on data query for two-tiered WSN, the privacy-preservation range query is one of the hotspots. However, there are some problems in the existing researches in two-tiered wireless sensor networks such as high computational and communication costs for security comparison items and high energy consumption of sensing nodes. In this paper, a privacy-preservation range query protocol based on the integration reversal 0-1 encoding with Bloom filter is researched and designed. In the sensing data submission stage, the optimized reversal 0-1 encoding, HMAC algorithm, AES encryption algorithm and variable-length Bloom filter are used for generating the maximum–minimum comparison encoding and constructing a shorter verification index chain to reduce computational and communication costs of sensing nodes; in the private data range query stage, the base station uses the HMAC algorithm to convert the plaintext query range into the ciphertext query range and sends it to the storage node. In the storage node, the bitmap encoding information of the verification index chain is calculated with the comparison rule of the reversal 0-1 encoding and it is returned to the base station together with the verification index chain and the data ciphertext that compliance with the query rule; in the data integrity verification stage, the integrity of the query results using the verification index chain and bitmap encoding is verified at the base station. In the experimental section, the Cortex-M4 development board equipped with the Alios-Things operating system as sensing node and the Cortex-A9 development board equipped with the Linux operating system as storage node are implemented in this protocol, which is compared with the existing protocols in three aspects: the number of data collected in each cycle, the length of data and the number of data dimensions. The experimental results show that the energy consumption of this protocol is lower under the same experimental environment. [ABSTRACT FROM AUTHOR]

Summary: The Internet of Things (IoT) continues to expand the current Internet, opening the door to a wide range of novel applications. The increasing volume of the IoT requires effective strategies to overcome its challenges. Machine Learning (ML) has led to a growing technology that enables computers to solve problems without the need for knowledge of their intricate details. Over the past years, various ML techniques have been used to efficiently manage IoT networks. Clustering is a technique that has proven its performance in the networking domain. Many works in the literature have studied ML‐based clustering methods for IoT networks, including their main properties, characteristics, underlying technologies, and open issues. In this paper, we focus on topology‐centered ML‐based clustering protocols for IoT networks. Specifically, we investigate the potential benefits of adopting the clustering approach to address several IoT challenges. Moreover, we provide a comprehensive taxonomy of ML‐based clustering algorithms for IoT networks. Finally, we statistically analyze the incorporation of ML techniques for clustering in various IoT systems and highlight the related open issues. [ABSTRACT FROM AUTHOR]

Introduction-- Smart irrigation systems require reliable and energy-efficient communication between the sensors in a Wireless Sensor Network (WSN) and the control system. Objective-- To address this challenge, this paper presents several cluster-based selection protocols, based on the Stable Election Protocol (SEP) and Distributed Energy-Efficient Clustering (DEEC). Methodology-- The presented protocols divide the agriculture field into sub-fields to reduce energy consumption between far sensors and the Base Station (BS). Results-- Comparison with traditional protocols using evaluation metrics such as network throughput, stability, instability period, and lifetime, shows that the presented protocols outperform in terms of all metrics. Conclusions-- The results indicate the effectiveness of the proposed protocols in prolonging the network's lifetime and improving energy efficiency in heterogeneous WSNs, thus supporting the performance of smart irrigation systems. Numerically, using the proposed protocols, the network lifetime increased by 23% compared to conventional SEP. [ABSTRACT FROM AUTHOR]

Vehicle Ad-hoc network (VANET) can provide technical support and solutions for the construction of intelligent and efficient transportation systems, and the routing protocol directly affects the efficiency of VANET. The rapid movement of nodes and uneven density distribution affect the routing stability and data transmission efficiency in VANET. To improve the local optimality and routing loops of the path-aware greedy perimeter stateless routing protocol (PA-GPSR) in urban sparse networks, a weight-based path-aware greedy perimeter stateless routing protocol (W-PAGPSR) is proposed. The protocol is divided into two stages. Firstly, in the routing establishment stage, the node distance, reliable node density, cumulative communication duration, and node movement direction are integrated to indicate the communication reliability of the node, and the next hop node is selected using the weight greedy forwarding strategy to achieve reliable transmission of data packets. Secondly, in the routing maintenance stage, based on the data packet delivery angle and reliable node density, the next hop node is selected for forwarding using the weight perimeter forwarding strategy to achieve routing repair. The simulation results show that compared to the greedy peripheral stateless routing protocol (GPSR), for the maximum distance–minimum angle greedy peripheral stateless routing (MM-GPSR) and PA-GPSR protocols, the packet loss rate of the protocol is reduced by an average of 24.47%, 25.02%, and 14.12%, respectively; the average end-to-end delay is reduced by an average of 48.34%, 79.96%, and 21.45%, respectively; and the network throughput is increased by an average of 47.68%, 58.39%, and 20.33%, respectively. This protocol improves network throughput while reducing the average end-to-end delay and packet loss rate. [ABSTRACT FROM AUTHOR]

The current trends in 5G and 6G systems anticipate vast communication capabilities and the deployment of massive heterogeneous connectivity with more than a million internet of things (IoT) and other devices per square kilometer and up to ten million gadgets in 6G scenarios. In addition, the new generation of smart industries and the energy of things (EoT) context demand novel, reliable, energy-efficient network protocols involving massive sensor cooperation. Such scenarios impose new demands and opportunities to cope with the ever-growing cooperative dense ad hoc environments. Position location information (PLI) plays a crucial role as an enabler of several location-aware network protocols and applications. In this paper, we have proposed a novel context-aware statistical dead reckoning localization technique suitable for high dense cooperative sensor networks, where direct angle and distance estimations between peers are not required along the route, as in other dead reckoning-based localization approaches, but they are obtainable from the node's context information. Validation of the proposed technique was assessed in several scenarios through simulations, achieving localization errors as low as 0.072 m for the worst case analyzed. [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]

Recently, unmanned aerial vehicle (UAV) networks have been widely used in military and civilian scenarios; however, they suffer various attacks. Time-delay attacks maliciously delay the transmission of packets without tampering with the contents or significantly affecting the transmission pattern, making detection difficult. In this paper, a holistic cross-layer time-delay attack detection framework (HOTD) is proposed for UAV networks. A holistic selection of the delay-related features available at all layers is performed, before adopting supervised learning to build a consistency model between these features and the corresponding forwarding delay to calculate the degree of consistency of each node. Finally, the clustering method is used to distinguish malicious from benign nodes according to their degree of consistency. Experimental results show that the performance of HOTD is superior to that of state-of-the-art detection methods, and it achieves a detection accuracy higher than 85% with less than 2.5% additional overhead. • Time-delay attacks are modelled in UAV networks for the first time. • HOTD collects delay-related features at all layers in the UAV network protocol. • The relationship between the features and delay is used to identify malicious nodes. • Simulations show the method achieves over 85% detection accuracy. • HOTD is better than other available methods in detecting time-delay attack nodes. [ABSTRACT FROM AUTHOR]

As an emerging network paradigm, the space–air–ground integrated network (SAGIN) has garnered attention from academia and industry. That is because SAGIN can implement seamless global coverage and connections among electronic devices in space, air, and ground spaces. Additionally, the shortage of computing and storage resources in mobile devices greatly impacts the quality of experiences for intelligent applications. Hence, we plan to integrate SAGIN as an abundant resource pool into mobile edge computing environments (MECs). To facilitate efficient processing, we need to solve the optimal task offloading decisions. In contrast to existing MEC task offloading solutions, we have to face some new challenges, such as the fluctuation of processing capabilities for edge computing nodes, the uncertainty of transmission latency caused by heterogeneous network protocols, the uncertain amount of uploaded tasks during a period, and so on. In this paper, we first describe the task offloading decision problem in environments characterized by these new challenges. However, we cannot use standard robust optimization and stochastic optimization methods to obtain optimal results under uncertain network environments. In this paper, we propose the 'condition value at risk-aware distributionally robust optimization' algorithm for task offloading, denoted as RADROO, to solve the task offloading decision problem. RADROO combines the distributionally robust optimization and the condition value at risk model to achieve optimal results. We evaluated our approach in simulated SAGIN environments, considering confidence intervals, the number of mobile task offloading instances, and various parameters. We compare our proposed RADROO algorithm with state-of-the-art algorithms, such as the standard robust optimization algorithm, the stochastic optimization algorithm, the DRO algorithm, and the Brute algorithm. The experimental results show that RADROO can achieve a sub-optimal mobile task offloading decision. Overall, RADROO is more robust than others to the new challenges mentioned above in SAGIN. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) comprises a network of interconnected nodes constantly communicating, exchanging, and transferring data over various network protocols. Studies have shown that these protocols pose a severe threat (Cyber-attacks) to the security of data transmitted due to their ease of exploitation. In this research, we aim to contribute to the literature by improving the Intrusion Detection System (IDS) detection efficiency. In order to improve the efficiency of the IDS, a binary classification of normal and abnormal IoT traffic is constructed to enhance the IDS performance. Our method employs various supervised ML algorithms and ensemble classifiers. The proposed model was trained on TON-IoT network traffic datasets. Four of the trained ML-supervised models have achieved the highest accurate outcomes; Random Forest, Decision Tree, Logistic Regression, and K-Nearest Neighbor. These four classifiers are fed to two ensemble approaches: voting and stacking. The ensemble approaches were evaluated using the evaluation metrics and compared for their efficacy on this classification problem. The accuracy of the ensemble classifiers was higher than that of the individual models. This improvement can be attributed to ensemble learning strategies that leverage diverse learning mechanisms with varying capabilities. By combining these strategies, we were able to enhance the reliability of our predictions while reducing the occurrence of classification errors. The experimental results show that the framework can improve the efficiency of the Intrusion Detection System, achieving an accuracy rate of 0.9863. [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]

This research is a case study on bug bounty hunting as a successful approach to finding and uncovering vulnerabilities in software. The purpose of this study is to understand the effectiveness of bug bounty hunting and its benefits in improving company security. Qualitative research methods were used by analyzing data from bug bounty programs that were successful in finding significant vulnerabilities. The results showed that bug bounty hunting proved to be effective in capturing various types of vulnerabilities, including web application vulnerabilities, network protocol vulnerabilities, hardware security vulnerabilities, and mobile app vulnerabilities. Security researchers play a critical role in the success of the bug bounty hunt, with their expertise in bug hunting and deep understanding of the technology. The benefits of bug bounty hunting include increased software security, cost efficiency, and increased company reputation for security and credibility. However, challenges such as finding hidden vulnerabilities and coordinating with enterprises need to be overcome. Recommendations include strengthening collaboration between enterprises and security researchers, establishing effective communication channels, and proactively responding to vulnerability reports. [ABSTRACT FROM AUTHOR]

In order to improve the data monitoring and information management capabilities of membrane gas measure device indirect metering terminals, a sensor network based data monitoring method for membrane gas measure device indirect metering terminals was proposed. The distributed and centralized sensor network node deployment method is used to achieve data collection for membrane gas measure device indirect metering terminals, and the collected membrane gas measure device indirect metering terminal data is segmented, fused, and reorganized. The distributed energy storage and constant volume two-level optimal control method is used to analyze the operation status of gas measure device indirect metering terminal data. The ZigBee networking protocol is used to build a network structure model for gas measure device indirect metering terminals, an integrated high-precision temperature and pressure sensor arranged parallel to the inner wall of the valve body is used to detect the temperature and pressure at the outlet of the membrane gas measure device. The temperature information is stored in DSP, and the user's expenses, system operation and maintenance, and peak shaving and valley filling benefits are taken as the parameters of the energy storage and constant volume outer layer model. The output stability of the indirect metering terminal data of the membrane gas measure device is analyzed in the high switching frequency mode. Combined with adaptive parameter adjustment, the indirect metering terminal control and data dynamic collection of the membrane gas measure device are realized. Realize dynamic monitoring of metering terminal data in wireless sensor network networking control mode. The test results show that using this method for indirect metering terminal data monitoring of gas measure devices has good output stability, strong dynamic fusion of sensing information, reduced metering errors, and improved metering accuracy of gas measure devices. [ABSTRACT FROM AUTHOR]