A Secure and Privacy Preserving Partial Deterministic RWP Model to Reduce Overlapping in IoT Sensing Environment

Abstract

The idea of the Internet of Things (IoT) was developed in parallel to wireless sensor networks (WSNs). In a mobile WSN, a sensor node is generally assumed to move around randomly in direction and speed. Thus, a random waypoint is commonly used for node mobility modeling. Unfortunately, it does not consider the overlapping sensing coverage (OSC) at continuous moves or at a given time of sensor nodes. On top of this, there is no security mechanism to authenticate the sensor nodes and their privacy. Thus, results in a higher probability of occurring OSC in the network and the threats to the network through inside and outside attackers. To resolve these issues in 3D WSNs, this paper proposes a secure and privacy-preserving node mobility model that the nodes take part in periodic rounds securely. An ID-based authentication mechanism for joining nodes in the network and detection of the malicious node based on their survival strategies are proposed in the model. Moreover, the decision making of a next destination during a pause time in a round is three-folded. First, a set of member nodes are elected. Then, all nodes predict their prospective destinations randomly and the member nodes broadcast their prospective destinations' information to neighbors. Finally, the neighborhood nodes adjust their prospective destinations considering the broadcasted information, in order to reduce the OSC in the network. The simulation experiments show that the proposed model reduces the OSC in the network and detects the malicious nodes, thus, results in a higher effective sensing coverage rate of the network in a secure way.