A Secure Protocol against Selfish and Pollution Attacker Misbehavior in Clustered WSNs

Abstract

Wireless sensor networks (WSNs) have been widely used for applications in numerous fields. One of the main challenges is the limited energy resources when designing secure routing in such networks. Hierarchical organization of nodes in the network can make efficient use of their resources. In this case, a subset of nodes, the cluster heads (CHs), is entrusted with transmitting messages from cluster nodes to the base station (BS). However, the existence of selfish or pollution attacker nodes in the network causes data transmission failure and damages the network availability and integrity. Mainly, when critical nodes like CH nodes misbehave by refusing to forward data to the BS, by modifying data in transit or by injecting polluted data, the whole network becomes defective. This paper presents a secure protocol against selfish and pollution attacker misbehavior in clustered WSNs, known as (SSP). It aims to thwart both selfish and pollution attacker misbehaviors, the former being a form of a Denial of Service (DoS) attack. In addition, it maintains a level of confidentiality against eavesdroppers. Based on a random linear network coding (NC) technique, the protocol uses pre-loaded matrices within sensor nodes to conceive a larger number of new packets from a set of initial data packets, thus creating data redundancy. Then, it transmits them through separate paths to the BS. Furthermore, it detects misbehaving nodes among CHs and executes a punishment mechanism using a control counter. The security analysis and simulation results demonstrate that the proposed solution is not only capable of preventing and detecting DoS attacks as well as pollution attacks, but can also maintain scalable and stable routing for large networks. The protocol means 100% of messages are successfully recovered and received at the BS when the percentage of lost packets is around 20%. Moreover, when the number of misbehaving nodes executing pollution attacks reaches a certain threshold, SSP scores a reception rate of correctly reconstructed messages equal to 100%. If the SSP protocol is not applied, the rate of reception of correctly reconstructed messages is reduced by 90% at the same case.

A Comprehensive Analysis of Security Challenges and Countermeasures in Wireless Sensor Networks Enhanced by Machine Learning and Deep Learning Technologies

“…WSNs may filter out unwanted nodes throughout the authentication process. All packets sent between a management node and a sensor must remain unaltered to prevent eavesdroppers from modifying or decoding them and gaining access to potentially helpful information in WSNs [28]. In addition to the characteristics and elements previously addressed, concerns about and the implementation of security are also critical for a variety of sensor network applications.…”