首页 /研究 /Fold on Fold Surveillance and Detection Against Non-Biased Penetrations in Layered Complex Infrastructures
OTHER

Fold on Fold Surveillance and Detection Against Non-Biased Penetrations in Layered Complex Infrastructures

Sooeon Lee, Seungheyon Lee, Hyunbum Kim, Sherali Zeadally

发表年份
2024
引用次数
2

摘要

We propose a fold on fold surveillance framework to detect non-biased penetrations into complex infrastructures with 6G and 5G beyond communications. The proposed framework provides reinforced surveillance and valid detection based on virtual emotion security against non-biased penetrations into the connected layered complex architecture including mobile robots, Unmanned Aerial Vehicles (UAVs), autonomous ground vehicles and smart devices. Then, we formally define a problem whose goal is to maximize the detection ratio so that we can conduct the required number of non-biased penetrations into the layered complex infrastructure. We also developed two different methods to solve the problem defined and we evaluate their implementations using extensive simulations with critical scenarios. We also analyzed the complexity of the proposed algorithms. Finally, we discuss promising research issues which must be addressed in the future for the applications of virtual emotion surveillance in advanced smart cities.

关键词

Fold (higher-order function)Computer scienceComputer securityComputer network

相关论文

查看 OTHER 分类全部论文