Detecting and Preventing for Performance Assessment of IoT Devices Under Dodag Information Solicitation (dis) Attacks

Abstract

The Internet of Things (IoT) is an important area of research as the ever-increasing number of connected devices permeate every aspect of our daily lives. The main characteristic of IoT devices is that they tend to be low resource devices, that are incapable of sustaining high power consumption activity for a long time, and they also tend to operate on lossy networks. Therefore, the term (Low Power and Lossy Networks - LLNs) is used in reference to such networks. The routing protocol used on IoT networks is typically RPL (Routing Protocol for Low-Power and Lossy Networks). These characteristics make IoT devices vulnerable to a variety of attacks; the most common of which are (DIS-DODAG Information Solicitation) attacks. This is a routing protocol attack that targets IoT resources, especially the battery of devices. This paper proposes a simulation and analysis of the DIS attack impact on the network performance in terms of energy consumption, as well as study the relationship between the number of attacker nodes and the IoT lifetime. We analyze number of attack scenarios to figure out the relationship between the number of attacker nodes and the power consumption among the IOT device and the reflect on its lifetime. We found that the power consumption inversely proportional with the number of attacker nodes as the power consumption increased by 212.374% with four attack nodes and by 650% with one attacker node and so the IOT life time decreased 2.21 times and 6.5 times respectively. We also proposed two novel algorithms for detecting and mitigating the DIS-attacks, and we simulate and evaluate them finding that they are very effective in stopping both slow/fast attacks and minimizing the false positives, as we simulated six attack scenarios with different attack rates and by studding the Attack Discover Performance we found that The system is Robust Enough to discover/stop high wave of Security intrusions.