AI Techniques for Software Vulnerability Detection and Mitigation

The growth of the Internet of Things (IoT) is leading to some restructuring and transformation of everyday lives. The number and diversity of IoT devices have increased rapidly, enabling the vision of a smarter environment and opening the door to further automation, accompanied by the generation and collection of enormous amounts of data. The automation and ongoing proliferation of personal and professional data in the IoT have resulted in countless cyber-attacks enabled by the growing security vulnerabilities of IoT devices. Therefore, it is crucial to detect and patch vulnerabilities before attacks happen in order to secure IoT environments. One of the most promising approaches for combating cybersecurity vulnerabilities and ensuring security is through the use of artificial intelligence (AI). In this paper, we provide a review in which we classify, map, and summarize the available literature on AI techniques used to recognize and reduce cybersecurity software vulnerabilities in the IoT. We present a thorough analysis of the majority of AI trends in cybersecurity, as well as cutting-edge solutions.