Investigating the Impact of Generative AI on Cybersecurity of Digital Marketing; A Solution-based Approach to Counter Threats

Abstract

It discusses the role of generative AI in the cybersecurity of digital marketing: it demonstrates the possible threats and assesses the effectiveness of defensive algorithms. The generative AI technology applied was Generative Adversarial Networks (GANs). GANs were used in simulations of various cyber threats, including fake ad campaigns, phishing emails, and spreading disinformation. The simulations proved how effective AI-generated attacks can be successful-good engagement can lead to significant financial and data losses. Fake ads accounted for significant losses in terms of ROI, phishing emails contributed towards several data breaches, and false information campaigns spread widely. The algorithms were advanced enough to resist such threats, which were tested. The algorithms could offer high accuracy and precision, recall, and F1 scores in the identification and mitigation of AI-driven threats. Success rates of AI-based cyber-attacks and robust performance of the algorithms in the defence against disinformation diffusion and fake ad and phishing email detection. Recommendations include strengthening AI-based detection systems, training employees, making them aware, putting in multi-layered security measures, and promoting collaboration between industry and academia. Future research directions include exploring cutting-edge AI defence mechanisms, studying the impact of AI on all marketing channels, designing real-time threat detection systems, and analyzing the ethical and legal aspects of AI in cybersecurity. The paper throws light on the need for perpetual innovation and interdisciplinary research to combat the developing threats from generative AI in digital marketing. The digital marketing environment will have a stronger security and resilience profile with holistic measures of security and digital literacy.