Edge Intelligence Assisted Gateway Defense in Cyber Security
Shengjie Xu, Yi Qian, Rose Qingyang Hu
Abstract
Advanced persistent threat, network intrusions and anomalies, and invasions of location and data privacy are constantly violating edge networks, disturbing guaranteed services, and further destroying critical end devices and cyberinfrastructure. Edge gateway defense against malicious cyber threats and privacy leakage for a multitude of connected physical devices remains a significant problem. Edge computing empowered network intelligence will become a practical solution to tackle this challenge by building gateway-focused protection mechanisms, dynamically extending the edge network, and establishing a flexible and intelligent platform to perform rapid responses with the cloud and wide area network. In this article, we present the research in edge intelligence assisted gateway defense in cyber security. Specifically, we first provide the overview of edge computing, and then discuss the motivations of developing and deploying a robust and effective edge intelligence. We also present the details of edge intelligence assisted gateway defense, including major cyber threats and defense mechanisms at gateways. We further offer detailed descriptions of the emerging data-driven approaches for gateway defense. Finally, we perform an experimental study, and we demonstrate that robust edge intelligence achieves high detection accuracy and effective computational performance.