Vinothkumar Kolluru, Sudeep Mungara, Advaitha Naidu Chintakunta

Abstract

As smart gadgets become more common in our lives through the Internet of Things (IoT) there's a balance, between convenience and the potential cybersecurity risks involved. This research focuses on enhancing security measures by looking into intrusion detection systems (IDS) and ensuring data privacy. By analyzing the UNSW NB15 dataset we investigate machine learning models to identify weaknesses and evaluate their effectiveness, in detecting threats. The aim is to develop security frameworks that can seamlessly merge with platforms using machine learning techniques. This study seeks to strengthen cybersecurity protocols while giving importance to user privacy and data security. The findings obtained are intended to benefit cybersecurity professionals, researchers and the general public by emphasizing the necessity of security systems to safeguard the expanding network.

Keywords

Cybersecurity, IoT, Intrusion Detection Systems (IDS), Machine Learning, IoT Security, AI, Data Science