Using machine learning to detect vulnerabilities in Internet of Things (IoT) devices

• Main Author: Yong, Li Yao
• Other Authors: Chang Chip Hong
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2024
• Subjects: Engineering; IoT; Machine learning
• Online Access: https://hdl.handle.net/10356/176381
• Institution: Nanyang Technological University

Internet of Things (IoT) networks are playing a more pivotal role in the current technology landscape. They are increasingly utilized in applications where security is of paramount importance. However, they are vulnerable to exploitation due to security flaws. Current security evaluations face challenges due to fragmented and insufficient documentation. In this project we will explore leveraging Artificial Intelligence (AI) driven text mining using OpenAI’s ChatGPT4 to extract information from Xilinx 7 series Field Programmable Gate Array (FPGA) and Xilinx UltraScale documents. By transforming unstructured text into structured data, this approach aims to enhance vulnerability assessments and ethical hacking practices in IoT networks, bolstering their resilience against malicious threats.