Bio Inspired Methods for Intrusion Detection in Internet of Things: A Survey

IoT has evolved in last few years and have become part of our lives, and thus lot of data is generated through these IoT systems. This advancement has motivated attackers to process intrusion in the system and manipulate data and process for the same. Network has a major role in IoT systems and Network Intrusion Detection System (NIDS) is designed to protect it by identifying different kinds of attacks and unauthorized applications or users. To secure these IoT systems, various tools and techniques have been evolved, that ranges from basic securing algorithms to bio inspired algorithms, Usage of Bio Inspired algorithms has features selection process as an essential to create a successful network IDS. Different bio-inspired algorithms are employed to categorize features more precisely, quickly determine whether network traffic is odd or regular, and recognize various attack types. This paper attempts a survey on usage of some of the bio-inspired algorithms those can be used for Intrusion Detection in IoT environment and identifies how artificial Immune system can be better than other techniques for the feature selection or classification process.