Intrusion Detection Model Using Chaotic MAP for Network Coding Enabled Mobile Small Cells

Wireless Network security management is difficult because of the ever-increasing number of wireless network malfunctions, vulnerabilities, and assaults. Complex security systems, such as Intrusion Detection Systems (IDS), are essential due to the limitations of simpler security measures, such as cryptography and firewalls. Due to their compact nature and low energy reserves, wireless networks present a significant challenge for security procedures. The features of small cells can cause threats to the network. Network Coding (NC) enabled small cells are vulnerable to various types of attacks. Avoiding attacks and performing secure “peer” to “peer” data transmission is a challenging task in small cells. Due to the low power and memory requirements of the proposed model, it is well suited to use with constrained small cells. An attacker cannot change the contents of data and generate a new Hashed Homomorphic Message Authentication Code (HHMAC) hash between transmissions since the HMAC function is generated using the shared secret. In this research, a chaotic sequence mapping based low overhead 1D Improved Logistic Map is used to secure “peer” to “peer” data transmission model using lightweight H-MAC (1D-LM-P2P-LHHMAC) is proposed with accurate intrusion detection. The proposed model is evaluated with the traditional models by considering various evaluation metrics like Vector Set Generation Accuracy Levels, Key Pair Generation Time Levels, Chaotic Map Accuracy Levels, Intrusion Detection Accuracy Levels, and the results represent that the proposed model performance in chaotic map accuracy level is 98% and intrusion detection is 98.2%. The proposed model is compared with the traditional models and the results represent that the proposed model secure data transmission levels are high.