Intrusion detection in wireless sensor networks by an ensemble of artificial neural networks

Abstract

Wireless sensor and actuator networks are essential components of modern technologies and infrastructures for smart homes and cities, intelligent transportation systems, advanced manufacturing, Internet of things and, for example, fog and edge computing. Cybersecurity of such massively distributed systems is becoming a major issue, and advanced methods to improve their safety and reliability are needed. Intrusion detection systems automatically identifymalicious network traffic, uncover cybernetic attacks and notify network users and operators. In this work, a novel strategy for intrusion detection in wireless sensor networks based on accurate neural models of specific attacks learned from network traffic data is proposed and evaluated.