Open AccessResearch on Network Data Security Based on RS-PS Support Vector Machine (SVM)
Author(s) -
Li Su,
Yu Liu,
Ting Li,
Xinxin Liu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1748/3/032057
Subject(s) - particle swarm optimization , support vector machine , rough set , computer science , intrusion detection system , the internet , network security , data mining , set (abstract data type) , field (mathematics) , information security , computer security , artificial intelligence , machine learning , world wide web , mathematics , pure mathematics , programming language
In the era of rapid development of digital information, resource sharing under the Internet environment, convenient access to information has brought us great convenience. However, as a new independent variable, the Internet itself has many unknown vulnerabilities, which provide an attack entrance for attackers and cause serious security risks. In this paper, intrusion detection research based on rough vector set and particle swarm optimization mainly involves particle swarm optimization (PSO), learning of rough function, etc. Based on some shortcomings of the algorithm optimization in the field of intrusion detection, a rough set(RS)-particle swarm(PS) SVM network data security detection method is proposed to provide security guarantee for information services.