Читать книгу Artificial Intelligence and Data Mining Approaches in Security Frameworks - Группа авторов - Страница 12

Navani Siroya1* and Prof Manju Mandot2

¹ M.Tech Scholar, Computer Science, MDS University, Ajmer, India

² Director, Department of Computer Science and IT JRN Rajasthan Vidyapeeth University, Udaipur, Rajasthan

Abstract

Borderless cyberspace as a part of “global commons” does not exist. Information breaches, ID theft, cracking the captcha, and other such stories proliferate, more so in times of the pandemic era, affecting people at a global level.

Today where AI advancements, for example, deep learning, can be incorporated into cyber security to develop shrewd models for executing malware classification, intrusion detection and threatens intelligence sensing. The flip side of the coin shows how AI models have to confront different digital dangers, which upsets their sampling, learning models, and decision-making. The ever-expanding danger of digital assaults, cybercrimes, and malware attacks has grown exponentially with the evolution of artificial intelligence. Conventional ways of cyber-attacks have now taken a turning point; consequently, the attackers resort to more intelligent ways.

This chapter discusses the cyber security needs that can be addressed by AI techniques. It talks about the traditional approach and how AI can be used to modify the multilayered security mechanism used in companies today. Here we propose a system that adds an additional layer of security in order to detect any unwanted intrusion. The chapter ends with deliberations on the future extent of artificial intelligence and cyber security.

Keywords: Artificial intelligence, cyber security, machine learning, Botnet