谷歌浏览器插件
订阅小程序
在清言上使用

SCADvanceXP—an Intelligent Polish System for Threat Detection and Monitoring of Industrial Networks

Mateusz Twardawa, Marek Smolik, Franciszek Rakowski, Jakub Kwiatkowski,Norbert Meyer

Security and Defence Quarterly(2024)

引用 0|浏览0
暂无评分
摘要
SCADvanceXP is an industrial network intrusion detection system that scans and monitors data exchange between engineering stations, field divides, controllers, supervisory control and data acquisition (SCADA), and other elements of the operational technology network in detail. SCADvanceXP has the potential to detect advanced attacks on industrial infrastructures with the use of rulebased, signature-based, and behavioural detection methods, which are supported by sophisticated machine and deep learning models. As a system developed in Poland, it addresses the needs of industry in that region of Europe. The goal of this work was to assess SCADvanceXP’s potential to detect common industrial threats. In order to check SCADvanceXP’s potential, an effort was undertaken to evaluate its functionality on major industrial threats. For that purpose, twelve malware strains interfering with industrial systems were described. Later, the SCADvanceXP functionality was overlapped on malware behavioural and detection markers, pointing out exact mechanisms in SCADvanceXP that would detect analysed threats. The results show that SCADvanceXP is able to detect a wide range of attacks on industrial networks. SCADvanceXP’s rich functionality is able to provide a high standard of security. However, if a threat is affecting systems not directly connected with industrial networks, SCADvanceXP will not be able to detect it. SCADvanceXP only monitors industrial systems; hence, corporate networks must be protected by a different solution to provide the required level of security. Nonetheless, SCADvanceXP is dedicated to operating within industrial networks and does not have access to regular IT networks. It can be concluded that SCADvanceXP is a specialist tool providing desired security for industrial networks.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要