THE ROLE OF INTRUSION DETECTION SYSTEM (IDS) IN INTERNET OF THINGS (IOT) -ITS FRAMEWORK OF WORKING AND CHALLENGES
A Kalaivani, R. Pugazendi · 2023
IOT is a new emerging and modern prototype that has merged several components, internet connected to various day-to-day physical objects. IoT has become a rapidly evolving technology making a great impact on the digital world, starting from everyday home appliances to a large industrial system. It has imposed a heavy duty on the data communication through internet, high risk on information and computational complexity. Devices are affiliated with a variety of smart fields like hospital, industries and home. Devices capture more valuable information. This has led to the attention of cybercriminals to get attracted towards the IoT for exploitation of the security and gain access to the devices and the data. Despite of being trending and promising technology of the present and for the future, IoT still faces security challenges as they IoT devices increase. The attacks on the IoT devices are increasing, because of the few drawbacks of the IoT devices like resource constraint, limited memory, low energy storage and lack in running the existing security software vulnerabilities. Cyberattacks has become very common in the IoT environment. If the attacks on the IoT devices goes unnoticed for a long time it creates many issues like inaccuracy, delay, service interruption and a huge loss. Intrusion Detection System plays an important role in detecting any attacks on the system. It helps in preventing our system from intruders. The goal of the IDS is to monitor the entire network activity, detect for any malicious or suspicious activity and trigger an alarm to the user about the attack. IDS is also undergoing so many advancements in its implementation strategies and techniques. In the last few years, the AI techniques like deep learning and machine learning has been implemented in all fields. This paper details about the Artificial Intelligence approaches (Machine learning and Deep learning) for Intrusion detection system (IDS) in Internet of Things (IoT). The complete taxonomy of IDS working, methods and the very strong datasets used are analyzed for identifying the weakness, features and to find the lacking facilities to meet the current technologies. IDS has many methods of implementing. But the anomaly –based intrusion detection system is very familiarly used in IoT. The implementation for the datasets like feature extraction, filtration, training, testing has to be performed as per the IoT environment.