ADVANCED THREAT INTELLIGENCE UTILIZING AI TO PREDICT AND PREVENT CYBER ATTACKS

Abstract

The Internet of Things (IoT), fog computing, cyberattacks, and computer security have all experienced exponential growth in the past few years, ushering in what is known as the fourth industrial revolution (Industry 4.0). Strict authentication and security measures are required due to the massive amounts of data produced by the ever-growing networks enabled by the Internet of Things (IoT). One of the most promising ways to guard against cyberattacks is with artificial intelligence (AI). This article follows a systematic literature review (SLR) format to organise and review the existing research on AI approaches for detecting cybersecurity vulnerabilities in an IoT environment. With an emphasis on the rapid prediction and mitigation of cyber-attacks, this research painstakingly investigates the possibilities of AI and ML to strengthen real-time cybersecurity. In response to a rapidly evolving threat landscape, this article spearheads research into cutting-edge cybersecurity solutions. Investigating the effectiveness of AI and ML in strengthening defence systems is urgently needed due to the limitations of existing approaches. An exhaustive examination of AI and ML's function in real-time cybersecurity is the goal of this article. Particularly highlighted is their ability to foresee and quickly foil cyberattacks. This investigation covers a wide range of topics, from the complexities of the models themselves to important issues of ethics, security, and new developments. The exploration covers all bases in terms of study directions, as it is built around a strong foundation. Enhancing explainability, addressing vulnerabilities to adversarial attacks, developing quantum-resistant cryptographic solutions, and fostering collaboration between humans and AI are all imperatives. Using AI and ML for real-time cybersecurity comes with a lot of complex technological, organisational, and ethical considerations, which this paper delves into. The results of this investigation shed light on the potential benefits and drawbacks of using AI and ML in cybersecurity. Crucial topics requiring nuanced attention and investigation include ethical considerations, vulnerabilities to adversarial assaults, and the urgency for quantum-resistant cryptography. This study imagines a future where cybersecurity ecosystems are built to last and adapt to new threats by combining human knowledge with AI and ML capabilities. To properly incorporate AI and ML in defending our digital environment against the ever-evolving cyber threat scenario, we need a clear roadmap for continued innovation, and the research directions laid forth here provide just that.