Application of network security penetration technology in power internet of things security vulnerability detection

Abstract

The emergence of network penetration attacks makes network security problems more and more prominent. To better detect network penetration attacks, this article first proposes an attack detection method based on ant colony classification rules mining algorithm based on swarm intelligence theory. Classification rules perform pattern matching to detect attack behavior. Second, the quantitative problem in the evaluation mechanism of power internet security vulnerability is analyzed. The addition and deletion of power internet of things (IoT) security assessment elements introduces a probabilistic computing model, improves the vulnerability assessment mechanism of power object networks, and solves the problem of power object network security and quantitative computing. Finally, after performing a series of preprocessing on the dataset, using the above method to find the classification rule or classification center, respectively, perform pattern matching or similarity calculation, and finally obtain the attack detection result. A series of evaluation functions are established in the experiment, and the experimental results are compared with other related algorithms. The results show that the method can effectively detect network penetration attacks and IoT security vulnerabilities, and the effectiveness of attack detection methods is greatly improved.

Research on Computer Network Security Vulnerabilities and Encryption Technology in Cloud Computing Environment

“…To ensure network security and prevent network hacking or other network supply, effective vulnerability detection scanning is crucial in the entire network data information security management system. Chen, Z. and other scholars aim at better-detecting network penetration attacks and propose an attack detection method based on the ant colony classification rule mining algorithm of group intelligence theory, which is tested in simulated experiments and corroborated that the method can effectively identify network vulnerabilities and network penetration attacks, and the recognition rate accuracy is high [13]. Zhang, J. scholars took the intrusion detection system (IDS) as the research object, established the intrusion detection model based on data mining and the traditional IDS method for comparison experiments, and the results of the research show that the intrusion system based on data mining is better in the network vulnerability intrusion detection and network security protection realizations [14].…”

“…Peng Peng. Applied Mathematics and Nonlinear Sciences, 9(1) (2024)[1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17] …”

Multipath TCP security over different attacks

“…To our best knowledge, no much work has been done on MPTCP security. The network security is an important issue in network communication 24‐26 . Since the MPTCP uses multiple paths, it opens many doors to an adversary get into its session.…”