Cryptanalysis of ultralightweight mutual authentication protocol for radio frequency identification enabled Internet of Things networks by Madiha Khalid, Umar Mujahid, Muhammad Najam-ul-Islam

“…To reduce the overall cost of radio frequency identification enabled Internet of Thing network security, the researchers use simple bitwise logical operations such as XOR , AND , OR , and Rot and have proposed many ultralightweight mutual authentication protocols. …”
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GMTBLC: a deep learning-based bi-modal network traffic classification method by WEI Debin, JIANG Qinlong, WEN Jinglong, WANG Xinrui

“…Network traffic classification is crucial for network security maintenance and management, and it has been widely applied in tasks, such as quality of service (QoS) assurance and intrusion detection. …”
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Automotive ethernet controller authentication method based on national cryptographic algorithms by Hui GUO, Yong LUO, Xiaolu GUO

“…With the development of intelligent and connected cars, cyber security of automotive ethernet becomes the focus of automotive industry.Authentication is one of the key technologies for automotive ethernet security.The existing authentication methods have shortcomings to meet the requirements of both safety and electronic controllers’ performance.Besides, national cryptographic algorithms are becoming a trend for automotive network security, while the related research in automotive ethernet area is still in starting phase.In order to balance the limited computing performance of electronic controllers and high security requirements of automotive ethernet, a two-stage trust chain authentication method based on national cryptographic algorithms was proposed.The method can be used in different automotive ethernet topologies.A trust chain was built up based on authentication credentials, which linked the two authentication stages, namely the initial stage and the vehicle using stage.The initial stage was triggered by diagnosis instrument at end of line or controller replacement.It deployed complete authentication based on SM2 algorithm and certificates in the initial stage.The vehicle using stage was triggered by ethernet gateway at vehicle power-on or network wakeup.In this stage, the method deployed fast authentication based on SM4 algorithm and authentication credential trust chain.The authentication credentials for trust chain were generated by credential functions.In order to ensure security, each credential was generated based on last successful authentication parameters dynamically.The test results on automotive ethernet controllers show that the method has lower computing cost and higher security level, and it can guarantee both performance and security.…”
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Automated vulnerability discovery method for 5G core network protocol by Peixiang WU, Zhilong ZHANG, Libo CHEN, Yijun WANG, Zhi XUE

“…With the widespread development of fifth-generation (5G) mobile communication technology, concerns regarding 5G network security have also increased.Blackbox fuzzing is a commonly used method for automated vulnerability discovery in software security.However, applying dynamic approaches like fuzzing to discover vulnerabilities in the complex design of 5G core network protocols poses challenges such as low efficiency, poor versatility, and lack of scalability.Therefore, a novel static method to examine the open-source solution of the 5G core network was proposed.Through this method, a series of memory leak security issues caused by improper variable life cycle management were identified, which can lead to denial-of-service attacks on the 5G core network.To summarize these weaknesses, a general vulnerability model and an automated vulnerability discovery method called HoI were presented, which utilized hybrid analysis based on control and data flow.By successfully discovering five zero-day bugs in Open5GS, an open-source solution for the 5G core network, vulnerabilities that cover practical application scenarios of multiple interface protocols in the 5G core network were identified.These vulnerabilities have wide-ranging impact, are highly detrimental, and can be easily exploited.They have been reported to the vendor and assigned four Common Vulnerabilities and Exposures (CVE) numbers, demonstrating the effectiveness of this automated vulnerability discovery method.…”
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Dual Attention Dual-Resolution Networks for Real-Time Semantic Segmentation of Street Scenes by Baofeng Ye, Renzheng Xue

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Traffic Anomaly Detection Algorithm for Wireless Sensor Networks Based on Improved Exploitation of the GM(1,1) Model by Qin Yu, Jibin Lyu, Lirui Jiang, Longjiang Li

“…Because worms, attacks, intrusions, and other kinds of malicious behaviors can be recognized by traffic analysis and anomaly detection, WSN traffic anomaly detection provides useful tools for timely reaction and appropriate prevention in network security. In the paper, we improve exploitation of GM(1,1) model to make traffic prediction and judge the traffic anomaly in WSNs. …”
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Cutting-Edge Intrusion Detection in IoT Networks: A Focus on Ensemble Models by Najm Us Sama, Saeed Ullah, S. M. Ahsan Kazmi, Manuel Mazzara

“…As the Internet of Things (IoT) landscape rapidly evolves, robust network security measures are imperative. In particular, Intrusion Detection Systems play a very important role in the preservation of an IoT environment from malicious activities. …”
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Elevated few-shot network intrusion detection via self-attention mechanisms and iterative refinement. by Congyuan Xu, Yong Zhan, Guanghui Chen, Zhiqiang Wang, Siqing Liu, Weichen Hu

“…The network intrusion detection system (NIDS) plays a critical role in maintaining network security. However, traditional NIDS relies on a large volume of samples for training, which exhibits insufficient adaptability in rapidly changing network environments and complex attack methods, especially when facing novel and rare attacks. …”
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Hybrid quantum enhanced federated learning for cyber attack detection by G. Subramanian, M. Chinnadurai

“…Abstract Cyber-attack brings significant threat and become a critical issue in the digital world network security. The conventional procedures developed to detects are centralized and often struggles with concerns like data privacy and communication overheads. …”
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LKM: A LDA-Based -Means Clustering Algorithm for Data Analysis of Intrusion Detection in Mobile Sensor Networks by Yuhua Zhang, Kun Wang, Min Gao, Zhiyou Ouyang, Siguang Chen

“…Intrusion detection system (IDS) is a kind of active network security technology to protect network from attacks. …”
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An Enhanced LSTM Approach for Detecting IoT-Based DDoS Attacks Using Honeypot Data by Arjun Kumar Bose Arnob, M. F. Mridha, Mejdl Safran, Md Amiruzzaman, Md. Rajibul Islam

“…Abstract One of the widening perils in network security is the Distributed Denial of Service (DDoS) attacks on the Internet of Things (IoT) ecosystem. …”
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Wireless body area network: Architecture and security mechanism for healthcare using internet of things by Arun Kumar, Ritu Dewan, Wisam Subhi Al-Dayyeni, Bharat Bhushan, Jayant Giri, Sardar MN Islam, Ahmed Elaraby

“…The data generated by small sensor devices need strong security methods for secure transmission over a public network. Security of the data sent from source to destination is handled by transport layer security (TLS) protocol and prevent message loss or reordering. …”
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Support Vector Machine (SVM) based Detection for Volumetric Bandwidth Distributed Denial of Service (DVB-DDOS) attack within gigabit Passive Optical Network by Sumayya Bibi, Nadiatulhuda Zulkifli, Ghazanfar Ali Safdar, Sajid Iqbal

“…The dynamic bandwidth allocation (DBA) algorithm is highly impactful in improving the network performance of gigabit passive optical networks (GPON). Network security is an important component of today’s networks to combat security attacks, including GPON. …”
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A Comprehensive Investigation of Anomaly Detection Methods in Deep Learning and Machine Learning: 2019–2023 by Shalini Kumari, Chander Prabha, Asif Karim, Md. Mehedi Hassan, Sami Azam

“…AD is crucial for various applications, including network security, fraud detection, predictive maintenance, fault diagnosis, and industrial and healthcare monitoring. …”
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A two-stage flexible scheduling method for power systems with wind power considering the coordination of multiple resources by Aoyu Lei, Ligang Zhao, Yong Mei, Hongyue Zhen, Yongqiang Gao, Tinghui Zhou

“…To accommodate a high penetration of renewable energy, it is vital to coordinate multiple flexible resources to deal with the intermittency and uncertainty of renewable energy and ensure the network security. In this paper, we propose a two-stage stochastic flexible dispatching method for power systems with large-scale wind power, which considers the coordination of unit commitment, optimal transmission switching, and optimal control of phase-shifting transformers within a unified framework. …”
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A Modified WASPAS Method for the Evaluation of E-Commerce Websites Based on Pythagorean Fuzzy Information by Xiufang Ou, Bingbin Chen

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Generative adversarial synthetic neighbors-based unsupervised anomaly detection by Lan Chen, Hong Jiang, Lizhong Wang, Jun Li, Manhua Yu, Yong Shen, Xusheng Du

“…Abstract Anomaly detection is crucial for the stable operation of mechanical systems, securing financial transactions, and ensuring network security, among other critical areas. Presently, Generative Adversarial Networks (GANs)-based anomaly detection methods either require labeled data for semi-supervised learning or face challenges with low computational efficiency and poor generalization when dealing with complex distributions. …”
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Global randomized consensus algorithm resist collusion attack based on game theory by Bao ZHANG, Youliang TIAN, Sheng GAO

“…As the cornerstone of blockchain technology, consensus technology has received more attention with the continuous development of blockchain technology.The development of consensus technology has become more and more rapid, but there are still related problems.Nowadays, fault-tolerant consensus algorithms, as one of the representative blockchain consensus technologies, still have many problems to be studied.The problem of node randomness and node collusion attacks in fault-tolerant consensus algorithms had been studied, and a game-theoretic-based anti-corruption algorithm was proposed.The global randomization consensus algorithm of collusion attack improved the security and throughput of the blockchain network by realizing the randomization of nodes and solving related security problems.In the process of selecting nodes participating in the fault-tolerant consensus algorithm, the global randomization of the initiator and verifier nodes was realized by using the mapping function and the weighted random function, thereby ensuring the identity anonymity of the initiator and verifier nodes and improving the blockchain network security accordingly.The reputation update model was used to realize the dynamic update of the reputation, and the game theory was used to analyze the security problems of the fault-tolerant consensus algorithm.A more correct and efficient algorithm model was constructed to improve the throughput of the algorithm and analyze the problem of collusion attack of more than one third of the nodes in this kind of algorithm, the refined Bayesian game was used to construct a collusion contract and analyze the collusion The Nash equilibrium point between the two nodes was adopted to solve the collusion attack problem of more than one third of the nodes.The security analysis and experiments show that the global randomization consensus algorithm based on the game theory anti-collusion attack is better than PoW、PoS and PBFT.The consensus algorithm is not only effective to improve throughput and reduce computing resource consumption, but also resistant to DDoS, Eclipse attacks and collusion attacks by more than one third of nodes.…”
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Research review of network defense decision-making methods based on attack and defense game by Xiaohu LIU, Hengwei ZHANG, Junqiang MA, Yuchen ZHANG, Jinglei TAN

“…Game theory studies the optimal decision-making problem under the condition of conflict confrontation.It is one of the basic theories of cyberspace security, and can provide a theoretical basis for solving the problem of network defense decision-making.The six game characteristics of network attack and defense were defined, such as goal opposition, strategy dependence, non-cooperative relationship, incomplete information, dynamic evolution and interest drive.Based on the hypothesis of rational player and limited resources, a 5-tuple network attack and defense game model was formally defined by using player, attack and defense strategy set, attack and defense action set, attack and defense information set and attack and defense income.The existing conditions of game equilibrium were analyzed, and the general process of network defense decision-making based on attack and defense game model was summarized.The applicable scenarios of network defense decision-making methods based on eight different types of game models were analyzed, such as complete information static game, complete information dynamic game, incomplete information static game, incomplete information dynamic game, evolutionary game, differential game, time game and random game, and summarizes their research ideas.The advantages and disadvantages of network defense decision-making methods based on different types of game models were given.The development process of network defense decision-making method based on attack defense game was summarized, and the advantages and characteristics of defense decision-making method was explained.It were pointed out that there were three problems in the research process, such as the relationship between the number of factors considered in game modeling and the complexity of the model, the dependence of game reasoning on information and data, and the generalization and migration of game model.It also looked forward to the next research direction from the description mechanism of normative strategy, the calculation method of optimizing revenue and the integration with other network security technologies.And the problems that should be solved were explained.…”
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Finding influential nodes in complex networks based on Kullback–Leibler model within the neighborhood by Guan Wang, Zejun Sun, Tianqin Wang, Yuanzhe Li, Haifeng Hu

“…Abstract As a research hot topic in the field of network security, the implementation of machine learning, such as federated learning, involves information interactions among a large number of distributed network devices. …”
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