Static Code Analysis for IoT Security: A Systematic Literature Review

What is it about?

The Internet of Things (IoT) connects billions of devices, from smart home sensors to industrial systems, but many suffer from serious software security flaws. Our study systematically reviews how static code analysis helps detect these vulnerabilities early by examining device code without execution. We analyzed nearly 100 studies to understand prevalent IoT security problems, the techniques used to identify them, and how the field is advancing. This comprehensive overview aims to equip researchers and developers with optimal tools and strategies for building safer IoT devices.

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Photo by Jakub Żerdzicki on Unsplash

Photo by Jakub Żerdzicki on Unsplash

Why is it important?

The escalating prevalence of smart devices makes IoT security a critical global concern, with cyberattacks on the rise. Traditional security analysis methods often fall short due to the unique complexities and resource constraints of IoT systems. Our review critically assesses where static code analysis excels, its current limitations, and how its integration with emerging technologies like machine learning (ML) and natural language processing (NLP) can bridge existing gaps. By synthesizing this complex landscape, our work offers crucial guidance for both researchers and practitioners, accelerating the development of robust IoT security solutions in an era of increasing regulations and evolving threats

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