Parallel security:generative adversarial systems for intelligent security in CPSS - Yidong LI; Jun ZHANG; Yaodong TAO; Wei WANG; Yuanxiang GU; Fei-Yue WANG (智能科学与技术学报)
Developing technologies such as AI and big data are changing the landscape of cybercrime for both attackers and defenders.Traditional defense technology mainly use the passive detect-then-defend model,which is hard to meet the security protection requirements brought by new attack characteristics.A novel security framework,named parallel security was proposed,which aimed at providing a comprehensive solution with descriptive security,predictive security and prescriptive security.The main idea was based on the ACP theory of parallel intelligent,and integrated new methods such as generative adversarial leaning model,parallel blockchain.Human elements,sociology and psychology were taken as an important component in the framework,in order to enhance the immunity of the system.In addition,a parallel security based platform was design and developed for several typical scenarios in the field of industrial internet as a proof of concept.