Intrusion Detection and Mitigation Using Machine Learning and ECC Algorithm

Abstract

Intrusion Detection System is a well-known term in the domain of Network and Information Security. It's one of the important components of the Network and Information Security infrastructure. Host Intrusion Detection System (HIDS) helps to detect unauthorized use, abnormal and malicious activities on the host, whereas Network Intrusion Detection System (NIDS) helps to detect attacks and intrusion on networks. This paper focuses on development security Data source agreement with identity verification and privacy Preservation scheme. The aim of the scheme is to realize device authentication in the security approaches is more energy-consuming. In the proposed approach elliptic curve, the cryptography approach used for more security with fewer key sizes with protocol enhancements to perform an efficient authentication process. The other solutions ML model using back propagation neural contributed in this work to detect the attack or for optimization of network and to reduce the overhead consumption as well as increase the network lifetime. Proposed system provides a secure network using the lightweight authentication protocol to mitigate the effect of the attack in the network environment. The MATLAB software has been used to show simulation performance. This simulation performance compare the system while attack taking and after mitigation.