Biblio

Underwater Wireless Sensor Networks (UWSNs) are liable to malicious attacks due to limited bandwidth, limited power, high propagation delay, path loss, and variable speed. The major differences between UWSNs and Terrestrial Wireless Sensor Networks (TWSNs) necessitate a new mechanism to secure UWSNs. The existing Media Access Control (MAC) and routing protocols have addressed the network performance of UWSNs, but are vulnerable to several attacks. The secure MAC and routing protocols must exist to detect Sybil, Blackhole, Wormhole, Hello Flooding, Acknowledgment Spoofing, Selective Forwarding, Sinkhole, and Exhaustion attacks. These attacks can disrupt or disable the network connection. Hence, these attacks can degrade the network performance and total loss can be catastrophic in some applications, like monitoring oil/gas spills. Several researchers have studied the security of UWSNs, but most of the works detect malicious attacks solely based on a certain predefined threshold. It is not optimal to detect malicious attacks after the threshold value is met. In this paper, we propose a multi-factor authentication model that is based on zero-knowledge proof to detect malicious activities and secure UWSNs from several attacks.

Trust management is a promising alternative solution to different complex security algorithms for Underwater Wireless Sensor Networks (UWSN) applications due to its several resource constraint behaviour. In this work, we have proposed a trust management model to improve location privacy of the UWSN. Adaptive Neuro Fuzzy Inference System (ANFIS) has been exploited to evaluate trustworthiness of a sensor node. Also Markov Decision Process (MDP) has been considered. At each state of the MDP, a sensor node evaluates trust behaviour of forwarding node utilizing the FIS learning rules and selects a trusted node. Simulation has been conducted in MATLAB and simulation results show that the detection accuracy of trustworthiness is 91.2% which is greater than Knowledge Discovery and Data Mining (KDD) 99 intrusion detection based dataset. So, in our model 91.2% trustworthiness is necessary to be a trusted node otherwise it will be treated as a malicious or compromised node. Our proposed model can successfully eliminate the possibility of occurring any compromised or malicious node in the network.

On account of large and inconsistent propagation delays during transmission in Underwater Wireless Sensor Networks (UWSNs), wormholes bring more destructive than many attacks to localization applications. As a localization algorithm, DV-hop is classic but without secure scheme. A secure localization algorithm for UWSNs- RDV-HOP is brought out, which is based on reputation values and the constraints of propagation distance in UWSNs. In RDV-HOP, the anchor nodes evaluate the reputation of paths to other anchor nodes and broadcast these reputation values to the network. Unknown nodes select credible anchors nodes with high reputation to locate. We analyze the influence of the location accuracy with some parameters in the simulation experiments. The results show that the proposed algorithm can reduce the location error under the wormhole attack.