• Lathies Bhasker T
• Dr.B. Ben Sujitha

The Internet of Things (IoT) is upcoming research platform in science and technology which has quickly become more widespread in recent years. With greater numbers of day-to-day objects being connected to the internet, many different new methods have been presented to make our everyday lives more straightforward. Pattern recognition is extremely prevalent in IoT devices because of the many applications and benefits that can come from it. A multitude of studies have been conducted with the intention of improving speed and accuracy, decreasing complexity, and reducing the overall required processing power of pattern recognition algorithms in IoT devices. In this paper we did a details survey about IoT networks, Machine Learning (ML) algorithms and how the Machine Learning algorithms are used in the IoT networks for real time applications and we analysed about different types of attacks in IoT and how can we detect those attacks by using Machine Learning methods.

Internet of Things (IoT), Anomaly Detection (AD), Supervised algorithms, Reinforcement algorithm, Attacks

"ANOMALY DETECTION TECHNIQUES IN INTERNET OF THINGS: A SURVEY", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 10, page no.c95-c102, October-2024, Available :http://www.jetir.org/papers/JETIR2410312.pdf

"ANOMALY DETECTION TECHNIQUES IN INTERNET OF THINGS: A SURVEY", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 10, page no. ppc95-c102, October-2024, Available at : http://www.jetir.org/papers/JETIR2410312.pdf