Artificial Intelligence Powered Cyberattacks
S. Jayachitra, Vijendra Pratap Singh, V. J. Chakravarthy, Mohammed Abdul Matheen, Y. R. Sampath Kumar · 2025
In recent years, the growth of cyberattacks leads the fostering of Artificial Intelligence (AI) techniques, specifically Machine Learning (ML), Deep Learning (DL) becomes crucial in the field of cybersecurity. These approaches play a significant role in detecting and alleviating cyberattacks that cause harms to individuals, institutions, organizations and in some countries. ML approaches utilize statistical techniques to determine patterns and anomalies. The DL algorithm shows greater potential in enhancing the accuracy and efficacy of cybersecurity models, specifically in image recognition process. This chapter provides an overview of how AI models are deployed in cybersecurity models which in holds the utilization in malware detection, phishing and spam detection, botnet detection, assessing vulnerability, cryptojacking, and intrusion detection. It delineates the challenges, technologies used, constraints, that includes transparency, interpretability, and adversarial attacks. Hence, the AI, ML, DL in cybersecurity provides promising techniques for enhancing the efficaciousness of security models and instigate the capability to defend against cyberattacks.