Knowledge-Driven Cybersecurity Intelligence: Software Vulnerability Coexploitation Behavior Discovery

Yin, Jiao; Tang, MingJian; Cao, Tru H.; You, Mingshan; Wang, Hua; Alazab, Mamoun

doi:10.1109/tii.2022.3192027

Cited by 56 publications

(23 citation statements)

References 20 publications

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“…In addition, the simulation environment is the simulator in the Ubuntu operating system. By simulating the characteristics of the object, we can find that the system can use its special performance to solve the encryption problem at runtime [20][21][22][23][24][25][26][27][28][29]. The simulation parameters of the simulator are set as shown in Table 1.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

Lightweight Cryptographic Simulation of Power IoT Fused with Bayesian Network Algorithms

Zhu

et al. 2023

EAI Endorsed Scal Inf Syst

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In the power system, the transmission and processing of information is a very important link, and the core part of it is electronic data, and the transmission and processing of electronic data is the most important link in the power system. Because information is continuously passed between network nodes, the security requirements for information are high. With the development of Internet technology, its application field has been widely expanded to various industries. Therefore, to better ensure power quality and improve network operation efficiency, it is necessary to rationally and effectively manage the entire communication system. Power Internet of Things technology combines information transmission and processing links and realizes data sharing between various communication nodes in the entire network system through intelligent management, thereby improving overall information security. This paper first introduces the research of Bayesian network algorithm, then studies the process of lightweight encryption implementation of power Internet of Things, and then simulates and compares various encryption algorithms to obtain the best encryption scheme, and finally verifies through simulation that the algorithm can effectively ensure the safe transmission of information and improve the efficiency of network operation.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

Lightweight Cryptographic Simulation of Power IoT Fused with Bayesian Network Algorithms

Zhu

et al. 2023

EAI Endorsed Scal Inf Syst

View full text Add to dashboard Cite

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“…Finally, 55 submissions were selected as full papers (with an acceptance rate of 24% approximately), plus 29 as short papers. The research papers cover the areas of social network data analysis, recommender systems [1], topic modeling [2], data diversity, data similarity, context-aware recommendation, prediction [3,4], big data processing [5], cloud computing, event detection [6], data mining [7], sentiment analysis, ranking in social networks, microblog data analysis, query processing [8], spatial and temporal data, graph theory and non-traditional environments [9,10]. We are honored to have several of the world's leading experts in the field join us as distinguished keynote speakers and invited speakers.…”

Section: Wise2021mentioning

confidence: 99%

Guest Editorial: WWWJ Special Issue of the 22th International Conference on Web Information Systems Engineering (WISE 2021)

et al. 2022

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“…The third step entails using Web3 JS and Smart Contracts to develop a graphical interface for the IPFS bandwidth analysis for network file storage. Yin et al [28] introduced a Modality-Aware Graph Convolutional Network (MAGCN) module that integrates topological graph connectivity data and multimodality entity properties into a single lower-dimensional feature space in order to improve link prediction performance. A Graph Knowledge Transfer Learning (GKTL) strategy is also designed using this method to transfer knowledge between subgraphs taken from the same knowledge graph.…”

Section: Related Workmentioning

confidence: 99%

Design of Intrusion Detection and Prevention Model Using COOT Optimization and Hybrid LSTM-KNN Classifier for MANET

Madhu

2022

EAI Endorsed Scal Inf Syst

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INTRODUCTION: MANET is an emerging technology that has gained traction in a variety of applications due to its ability to analyze large amounts of data in a short period of time. Thus, these systems are facing a variety of security vulnerabilities and malware assaults. Therefore, it is essential to design an effective, proactive and accurate Intrusion Detection System (IDS) to mitigate these attacks present in the network. Most previous IDS faced challenges such as low detection accuracy, decreased efficiency in sensing novel forms of attacks, and a high false alarm rate. OBJECTIVES: To mitigate these concerns, the proposed model designed an efficient intrusion detection and prevention model using COOT optimization and a hybrid LSTM-KNN classifier for MANET to improve network security. METHODS: The proposed intrusion detection and prevention approach consist of four phases such as classifying normal node from attack node, predicting different types of attacks, finding the frequency of attack, and intrusion prevention mechanism. The initial phases are done through COOT optimization to find the optimal trust value for identifying attack nodes from normal nodes. In the second stage, a hybrid LSTM-KNN model is introduced for the detection of different kinds of attacks in the network. The third stage performs to classify the occurrence of attacks. RESULTS: The final stage is intended to limit the number of attack nodes present in the system. The proposed method's effectiveness is validated by some metrics, which achieved 96 per cent accuracy, 98 per cent specificity, and 35 seconds of execution time. CONCLUSION: This experimental analysis reveals that the proposed security approach effectively mitigates the malicious attack in MANET.

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Knowledge-Driven Cybersecurity Intelligence: Software Vulnerability Coexploitation Behavior Discovery

Cited by 56 publications

References 20 publications

Lightweight Cryptographic Simulation of Power IoT Fused with Bayesian Network Algorithms

Lightweight Cryptographic Simulation of Power IoT Fused with Bayesian Network Algorithms

Guest Editorial: WWWJ Special Issue of the 22th International Conference on Web Information Systems Engineering (WISE 2021)

Design of Intrusion Detection and Prevention Model Using COOT Optimization and Hybrid LSTM-KNN Classifier for MANET

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