AI-Generated Deepfakes: The emerging cybersecurity threat and countermeasures - Aslam, Mohammad (ISTM Journal of Training Research and Governance)
We have been living in a world where artificial intelligence (AI) can see, recognise, understand, and synthesise objects, and it can also manipulate them and create text, images, and videos indistinguishable from reality. People can no longer rely on their sense organs to distinguish real text, speech, images, and videos from fake ones. Thus, the rise of AI has ushered in a new era of synthetic reality, where AI-generated content is intended to appear real. Consequently, AI-generated deepfakes pose a significant cybersecurity threat because they have the potential to spread disinformation, threaten national security, and undermine trust. AI-generated synthetic media is good enough to fool humans. It also increases the risk of industrial disruption and augments commercial disinformation. Therefore,no nation-state can afford to ignore these threats posed by synthetic media or deepfakes. This article explores how deepfakes significantly impact democracy, social trust, political stability, and market institutions. It also aims to explore the emergence and impact of deepfakes on democracy, society, political stability, and market institutions. Moreover, to examine the mechanisms used in generating deepfakes and their implications. Furthermore, to identify technological, legal, and policy-based countermeasures against deepfake threats. As technology continues to advance, it inevitably brings about new vulnerabilities and security risks across various computing platforms. For instance, personal computers face threats from viruses, credit cards are susceptible to identity theft, and email systems are plagued by spam. Similarly, as artificial intelligence becomes more prevalent, it will encounter its own set of vulnerabilities and potential attacks. Deepfakes, which involve the creation of highly realistic but deceptive media, represent just one of the many challenges that AI will face in this evolving landscape. In late 2017, AI-generated "deepfakes" videos began circulating online, in which deep learning was used to generate realistic-looking fake videos. Early deepfake videos consisted of face-swapping, in which a person's face was swapped onto the body of a different person in a video (Scharre, 2023). AI-generated videos were first used in pornography, in this case to swap the faces of celebrities such as Gal Gadot or Scarlett Johansson onto the bodies of porn stars (ibid). The videos did not only harm the celebrities whose faces Introduction. Reproduced
Keywords: Artificial intelligence, Deepfakes, Cybersecurity, Disinformation, Nationa