Attack and Defense Strategies for Intrusion Detection in Autonomous Distributed IoT Systems

In this paper, we develop a methodology to capture and analyze the interplay of attack-defense strategies for intrusion detection in an autonomous distributed Internet of Things (IoT) system. In our formulation, every node must participate in lightweight intrusion detection of a neighbor target node. Consequently, every good node would play a set of defense strategies to faithfully defend the system while every bad node would play a set of attack strategies for achieving their own goals. We develop an analytical model based on Stochastic Petri Net (SPN) modeling techniques. Our methodology allows the optimal defense strategies to be played by good nodes to maximize the system lifetime when given a set of parameter values characterizing the distributed IoT system operational environment. We conduct a detailed performance evaluation based on an experiment dataset deriving from a reference autonomous distributed IoT system comprising 128 sensor-carrying mobile nodes and show how IDS defense mechanisms can counter malicious attack mechanisms under the ADIoTS system while considering multiple failure conditions.