Digital Immune System

6Integrating GANs for Enhanced Phishing Detection in Digital Immune Systems

Sherwin Akshay J. G.¹, Hari Varshan S. R.², Radhika G.¹ and Radhika N.¹*

¹Department of Computer Science and Engineering, Amrita School of Computing, Coimbatore, Amrita Vishwa Vidyapeetham, India

²Department of Mathematics, Amrita School of Physical Sciences, Coimbatore, Amrita Vishwa Vidyapeetham, India

Abstract

Phishing attacks are becoming more complex and difficult to detect, posing a significant challenge to enterprises trying to protect sensitive information. Traditional security solutions, such as firewalls and antivirus, are ineffective against new and sophisticated phishing attacks. Due to this rising threat, digital immune systems (DIS) have been developed. The DIS are inspired by the human body’s innate immune system, which allows them to detect, learn from, and respond to cyber threats autonomously. However, even DIS require assistance when dealing with very sophisticated phishing attacks. This chapter discusses the potential of generative adversarial networks (GANs), a type of artificial intelligence, for improving phishing detection in digital information systems. Generative adversarial networks can generate massive amounts of realistic simulated phishing data for training security systems. By exposing the DIS to a diverse set of phishing samples, the system enhances its ability to recognize real threats, including new-in-type threats. This chapter uses real-life examples and case studies ...