From Phishing to Deepfake: The Rapid Evolution of Cybercrime Tactics
Keywords:
Cybercrime; Phishing; Deepfake; Artificial Intelligence (AI); Digital Evidence.Abstract
This study analyzes the fundamental shift in cybercrime tactics, moving from conventional Phishing, which exploits human vulnerabilities, toward sophisticated Artificial Intelligence (AI)-based attacks like Deepfake. Phishing, though simple, remains a dominant attack vector ; however, Deepfake, powered by Generative Adversarial Networks (GANs), creates false "digital evidence" with near-perfect credibility. This transition escalates the risk of catastrophic losses, threatening the integrity of digital evidence and institutional stability. Employing the Normative Legal Research method, this study evaluates the defense gap. Current cybersecurity strategies, focused on malware mitigation and user education, are proven ineffective against AI-based threats. The conclusion emphasizes the urgent need for a paradigm shift toward proactive, integrity-based defense and recommends revising criminal and civil procedural law for digital evidence authentication, alongside clear regulations on Deepfake accountability
References
Akyazi, U., van Eeten, M., & Gañán, C. H. (2021). Measuring cybercrime as a service (caas) offerings in a cybercrime forum. Workshop on the Economics of Information Security, 1–15.
Alkhalil, Z., Hewage, C., Nawaf, L., & Khan, I. (2021). Phishing attacks: A recent comprehensive study and a new anatomy. Frontiers in Computer Science, 3, 563060.
Casey, E. (2011). Digital evidence and computer crime: Forensic science, computers, and the internet. Academic press.
Collier, B., & Clayton, R. (2022). A “sophisticated attack”? innovation technical sophistication and creativity in the cybercrime ecosystem. 21st Workshop on the Economics of Information.
Cuganesan, S., & Lacey, D. (2011). Developments in public sector performance measurement: a project on producing return on investment metrics for law enforcement. Financial Accountability & Management, 27(4), 458–479.
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., & Bengio, Y. (2020). Generative adversarial networks. Communications of the ACM, 63(11), 139–144.
Manky, D. (2013). Cybercrime as a service: a very modern business. Computer Fraud & Security, 2013(6), 9–13.
Schmitt, M., & Flechais, I. (2024). Digital deception: Generative artificial intelligence in social engineering and phishing. Artificial Intelligence Review, 57(12), 324.
Sharma, P., Kumar, M., & Sharma, H. K. (2024). GAN-CNN ensemble: a robust deepfake detection model of social media images using minimized catastrophic forgetting and generative replay technique. Procedia Computer Science, 235, 948–960.
Wall, D. S. (2024). Cybercrime: The transformation of crime in the information age. John Wiley & Sons.
Westerlund, M. (2019). The emergence of deepfake technology: A review. Technology Innovation Management Review, 9(11).
