Blockchain Based Privacy Preserving Authentication and Malicious Node Detection in Internet of Underwater Things (IoUT) Networks

Abstract

The usage of Internet of Underwater Things (IoUT) Networks allows for the detection of a variety of aquatic factors like temperature, pressure, pollution, etc. They are also used to forecast the ocean’s weather to collect information about natural disasters. However, they are easily compromised by attackers due to deployment in unattended environments. To overcome these issues, security is required in IoUT networks to avoid unauthorized access and ensure network credibility. This work proposes an authentication and a malicious node detection mechanism to restrict the unauthorized external nodes from accessing the network and the internal nodes from acting maliciously, respectively. Moreover, blockchain stores the hashes of sensor nodes’ credentials during the registration process to make the system secure and traceable. Meanwhile, for data aggregation and malicious nodes’ detection, a weighted trust evaluation mechanism is introduced. Moreover, an additive increase multiplicative decrease algorithm puts malicious nodes in an intensive observation queue to verify the data of malicious nodes before aggregating. Moreover, weights are assigned to sensor nodes based on their behaviour. If the weight of a sensor node becomes zero, it is revoked by the blockchain. Besides, the proposed malicious node detection mechanism’s enhanced efficiency is proved via extensive simulations.

Keywords

• Authentication
• blockchain
• Internet of Underwater Things
• malicious node detection
• privacy preservation