NIASHPT: a novel intelligent agent-based strategy using hello packet table (HPT) function for trust Internet of Things

Abstract

Internet of Things (IoTs) is a new concept in computer science that connects the objects with limited resources to unreliable internet through different technologies. The fundamental components of IoT (e.g., the wireless sensor networks and the internet) have an unsecured foundation that leads to different vulnerabilities such as vulnerability against a blackhole attack. In a blackhole attack, the attacker fakes itself as the shortest path to the destination, which is a node here. This causes the routing packets to not reach the destination. In this study, we offer a novel intelligent agent-based strategy using the hello packet table (NIASHPT) to deal with these problems by discovering the blackhole attacks. The proposed NIASHPT method provides an intrusion detection system scheme to defend against blackhole attacks and reduce or eliminate such attacks. This method consists of three phases: In the first phase, each node listens to its adjacent nodes and then applies a pre-routing process. In the stages of adjacent node listening and pre-routing, we attempt to find the blackhole attacks. In the second phase of the proposed method, the malicious nodes are detected and separated from the IoT network to avoid emerging attacks along the route from the source to the destination. In the third phase, the selected route from the source to the destination is checked. The method is evaluated here via extensive simulations carried out in the NS-3 environment. The experimental results of four scenarios demonstrated that the NIASHPT method can achieve a false positive rate of 19.453%, a false negative rate of 22.19%, a detection rate of 80.5%, a PDR of 89.56%, and a packet loss rate of 10.04% in the case of launching a blackhole attack.