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

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 chall...

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