Antibody Concentration Based Method for Network Security Situation Awareness

被引：0

作者：

Sun, Feixian ^{[1
]}

Xu, Feng ^{[1
]}

机构：

[1] Zhongyuan Univ Technol, Sch Comp Sci, Zhengzhou 450007, Peoples R China

来源：

2009 3RD INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICAL ENGINEERING, VOLS 1-11 | 2009年

关键词：

immunity; network security; situation awareness; ARTIFICIAL IMMUNE-SYSTEMS; OPTIMIZATION;

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Inspired by the principles of biological immune system, an antibody concentration based method for network security situation awareness, referred to as ACnssa, is proposed in this paper. With the concepts and formal definitions of self, non-self, antibody and antigen presented, the principles and framework of ACnssa is described. Following that, the mathematical models of the lifecycle of mature and memory lymphocyte which are used for security situation awareness are established. Experiment results show that a network system can learn what attacks it suffers, where the intrusions occur, whether the intrusions are serious or not. In addition, the system learns what the current attacks are, and where the most serious disastrous area is. Thus, it provides a good solution to the situation awareness of network security.

引用

下载

页码：130 / 133

页数：4

共 50 条

[31] RESEARCH ON NETWORK SECURITY SITUATION AWARENESS TECHNOLOGY BASED ON SECURITY INTELLIGENT MONITORING TECHNOLOGY
Yang, Bingyu
[J]. SCALABLE COMPUTING-PRACTICE AND EXPERIENCE, 2024, 25 (02): : 1107 - 1116
[32] Research on Network Security Situation Awareness System Based on Machine Learning
Yang Ye-ling
[J]. PROCEEDINGS OF THE 2016 2ND WORKSHOP ON ADVANCED RESEARCH AND TECHNOLOGY IN INDUSTRY APPLICATIONS, 2016, 81 : 122 - 125
[33] The computer network security situation awareness based on decision tree algorithm
Kong D.
Lu L.
Xiao N.
[J]. International Journal of Reasoning-based Intelligent Systems, 2024, 16 (02) : 125 - 136
[34] Situation awareness model of network security based on grey Verhulst model
School of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China
不详
[J]. Harbin Gongye Daxue Xuebao, 2008, 5 (798-801):
[35] Stealing complex network attack detection method considering security situation awareness
Xi, Bo
Liu, Huiying
Hou, Botao
Wang, Ying
Guo, Yuling
[J]. PLOS ONE, 2024, 19 (03):
[36] Prediction of network security situation awareness based on an improved model combined with neural network
Yuan, Li
[J]. SECURITY AND PRIVACY, 2021, 4 (06)
[37] A Security Situation Assessment Method Based on Neural Network
Tang, Xiangyan
Chen, Meizhu
Cheng, Jieren
Xu, Jinying
Li, Hui
[J]. CYBERSPACE SAFETY AND SECURITY, PT II, 2019, 11983 : 579 - 587
[38] RETRACTED: Distribution Network Security Situation Awareness Method Based on the Distribution Network Topology Layered Model (Retracted Article)
Ouyang, Yuhong
Li, Man
Kang, Wenqian
Che, Xiangbei
Ye, Ruixian
[J]. JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING, 2023, 2023
[39] APPLICATION OF FRACTAL NEURAL NETWORK IN NETWORK SECURITY SITUATION AWARENESS
Ding, Caichang
Chen, Yiqin
Algarni, Abdullah M.
Zhang, Guojun
Peng, Honghui
[J]. FRACTALS-COMPLEX GEOMETRY PATTERNS AND SCALING IN NATURE AND SOCIETY, 2022, 30 (02)
[40] Power Grid Security Situation Awareness Method based on Deep Learning
Zhang, Hongfeng
Jie, Suo Lang Bu Duo
Yang, Yuxin
Zhang, Rui
Lang, Qiong
Zhu, La Ba Dun
Ren, Mi Ma Ci
[J]. 2023 IEEE INTERNATIONAL CONFERENCES ON INTERNET OF THINGS, ITHINGS IEEE GREEN COMPUTING AND COMMUNICATIONS, GREENCOM IEEE CYBER, PHYSICAL AND SOCIAL COMPUTING, CPSCOM IEEE SMART DATA, SMARTDATA AND IEEE CONGRESS ON CYBERMATICS,CYBERMATICS, 2024, : 776 - 780

← 1 2 3 4 5 →