In this paper, we describe a intrusion detection algorithm based on deep learning for
industrial control networks, aiming at the security problem of industrial control network. Deep …

现今计算机网络安全问题已越来越受人们关注, 网络入侵的手段越来越复杂多样化.
由于传统的网络安全防护技术的具有局限性, 使入侵检测系统成为了目前网络安全技术的研究 …

Abstract Machine-type communication (MTC) senses our environment througfh connecting
millions of devices to one another, and becomes an enabler for context-aware and …

In this paper, the problem of designing the worst-case ϵ-stealthy false data injection attacks
in cyber-physical systems is investigated. The attacker attempts to degrade the remote state …

In the era of the rapid development of the Internet, network security issues are receiving
increasing attention. Aiming at the shortcomings of extreme learning machines in network …

Federated learning (FL) can push the limitation of “Data Island” while protecting data privacy
has been a broad concern. However, the centralised FL is vulnerable to a single-point …

This paper proposes a game learning approach for system identification with binary data
against piecewise constant DoS (Denial-of-Service) attacks. First, the game model of attack …

Industrial Internet of Things (IIoT) systems are key enabling infrastructures that sustain the
functioning of production and manufacturing. To satisfy the intelligence demands, federated …

Intrusion detection systems play an important role in computer security. To make intrusion
detection systems adaptive to changing environments, supervised learning techniques had …