Embedded system security analysis based on machine learning: Challenges, techniques
Neha Bathla, Amanpreet Kaur · 2024
The Internet of Things (IoT) is a network of interconnected devices and systems linked to the cloud, facilitating the extensive collection and analysis of data. Despite its benefits, the widespread adoption of IoT devices has led to notable security concerns, such as unauthorized access, data breaches, and device tampering. This paper delves into these security challenges and explores mitigation strategies, including encryption, access control, and user authentication.In addition to security issues, IoT encounters challenges related to interoperability, scalability, and resource constraints. The paper thoroughly examines these challenges and proposes solutions to overcome them. Moreover, it discusses IoT parameters like data volume, velocity, and variety, emphasizing the role of machine learning in processing and analyzing the copious amounts of data generated by IoT devices.In conclusion, the paper provides an overview of the critical challenges confronting IoT and suggests measures to enhance security and address various issues. By implementing robust security measures, ensuring interoperability and scalability, and leveraging machine learning, IoT can persist in its evolution, driving innovation across diverse industries.