Metaheuristic optimization algorithm based intrusion detection strategies for heterogeneous iot environments

Abstract

Recently, Internet of Things (IoT) becomes a hot research topic due to newlineapplicability in several domains such as healthcare, smart cities, newlinegovernment bodies, etc. The integration of the IoT devices to the real time newlineenvironment remains a difficult process. Since IoT nodes restricted to energy newlineand computational abilities, energy efficiency needs to be maximized. newlineHeterogeneous IoT environment consists of different hardware and sensing newlinecapabilities. The IoT mainly work with Wireless infrastructure and are more newlineprone to security issues. As IoT technology becomes more pervasive, the newlineamalgamation of diverse hardware and sensing capabilities within the newlinenetwork introduces complexities, particularly in the realms of security and newlineenergy efficiency. The reliance on wireless infrastructure in IoT networks newlineaccentuates security concerns, as these systems are more susceptible to newlinevarious types of attacks. The current state of IoT architecture lacks energy newlineefficient and secure routing algorithms, and the specific issue of uncertain newlineknowledge about residual energy during Cluster Head (CH) selection poses a newlinesignificant obstacle. At the same time, security susceptibilities in IoT based newlinesystems generate security threats that affect smart environment applications. newlineInternet of Things (IoT) undergoes various forms of attacks because of the newlinevulnerabilities presented in devices. Owing to several IoT network traffic newlinefeatures, the Machine Learning (ML) methods consume more time for newlinedetecting attacks. Intrusion Detection Systems (IDSs) becomes vital self newlineprotective tools towards several cyber-attacks. But, IoT IDS system newlineencounters important difficulties because of physical and functional diversity. newlineSuch IoT features use all attributes and features for IDS self-protection newlinedifficult and unrealistic. newline