A secure routing and black hole attack detection system using coot Chimp Optimization Algorithm-based Deep Q Network in MANET

Abstract

A Mobile Ad hoc Network (MANET) is a widely used and vibrant network, which is unevenly distributed in the environment. It is a set of self-organized independent mobile nodes interconnected without any centralized infrastructure. However, this topology nature makes the network prompt to various network security attacks. To address this issue, this paper proposes a Coot Chimp Optimization Algorithm- Deep Q-Network (CChOA-DQN) for detecting the black hole attacks in MANET. Here, the designed CChOA is used for the identification of the optimal route in the MANET for transmitting data, which takes into fitness parameters, such as energy, distance, neighbourhood quality, link quality, and trust. The features are extracted using the Fisher score and augmented using the over-sampling technique, which is further allowed for the detection process using DQN. Also, the weights of the DQN are enhanced using the CChOA algorithmic technique to enhance the detection performance. Additionally, the results gathered from the experiment revealed that CChOA attained high performance with a maximum of 0.983 Mbps throughput, 93.70 % Packet Delivery Ratio (PDR), and minimum end-end delay of 0.096Sec, Residual energy of 0.119 J, and Control overhead of 4473.11. Also, the CChOA-DQN technique achieved the minimum False Positive Rate (FPR) of 0.122, False Negative Rate (FNR) of 0.121, Computation time of 0.153 and Run time of 0.094.