BASIC IOT NETWORK AND INTRUSION DETECTION

The burgeoning integration of Internet of Things (IoT) technologies into everyday life has been met with a parallel increase in security vulnerabilities, prompting the necessity for robust intrusion detection systems (IDS) tailored for IoT networks. This research presents an exploration into the establishment of a fundamental IoT network framework, alongside the development and implementation of an effective IDS designed to mitigate the unique security challenges faced by such network. The paper begins by delineating the architecture of a basic IoT network, highlighting its components, communication models, and the typical interactions between various IoT devices. Given the diverse and often resource-constrained nature of these devices, the network architecture is designed to support scalability, interoperability, and efficient data exchange.Subsequently, the focus shifts to the realm of security, underlining the paramount importance of safeguarding these interconnected systems against malicious intrusions. The paper introduces a novel IDS specifically engineered for IoT environments, leveraging cutting-edge techniques such as machine learning algorithms and behavioral analysis to identify and respond to anomalous activities indicative of potential security breaches

Keywords: lineardiscriminantanalysis, mlpclassifier, k-nearestneighbours, logisticRegression, Decisiontree