Applications of spiking neural P systems in cybersecurity

被引:0
|
作者
Plesa, Mihail-Iulian [1 ]
Gheorghe, Marian [2 ]
Ipate, Florentin [1 ]
Zhang, Gexiang [3 ]
机构
[1] Univ Bucharest, Dept Comp Sci, Bucharest, Romania
[2] Univ Bradford, Sch Elect Engn & Comp Sci, Bradford, England
[3] Chengdu Univ Informat Technol, Sch Automat, Chengdu 610225, Peoples R China
基金
中国国家自然科学基金;
关键词
Cybersecurity; Spiking neural P systems; Machine learning;
D O I
10.1007/s41965-024-00166-9
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Spiking neural P systems are third-generation neural networks that are much more energy efficient than the current ones. In this paper, we investigate for the first time the possibility of using spiking neural P systems to solve cybersecurity-related problems. We proposed a new architecture called cyber spiking neural P systems (Cyber-SN P systems for short), which is designed especially for cybersecurity data and problems. We trained multiple Cyber-SN P systems to detect malware on the Android platform, phishing websites, and spam e-mails. We show through experiments that these networks can efficiently classify cybersecurity-related data with much fewer training epochs than perceptron-based artificial neural networks.
引用
收藏
页码:310 / 317
页数:8
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