Security of Distributed Intelligence in Edge Computing: Threats and Countermeasures
Mohd. Samar Ansari, Saeed Hamood Alsamhi, Yuansong Qiao, Yuhang Ye, Brian Lee
Abstract
Rapid growth in the amount of data produced by IoT sensors and devices has led to the advent of edge computing wherein the data is processed at a point at or near to its origin. This facilitates lower latency, as well as data security and privacy by keeping the data localized to the edge node. However, due to the issues of resource-constrained hardware and software heterogeneities, most edge computing systems are prone to a large variety of attacks. Furthermore, the recent trend of incorporating intelligence in edge computing systems has led to its own security issues such as data and model poisoning, and evasion attacks. This chapter presents a discussion on the most pertinent threats to edge intelligence. Countermeasures to deal with the threats are then discussed. Lastly, avenues for future research are highlighted.