Cyber Security Challenges in Generative AI Technology
Keywords:
Adversarial attacks, Data privacy, Cybersecurity, Generative Adversarial Networks (GANs), Generative Artificial Intelligence (GAI), Mitigation Strategies, Variational Autoencoders (VAE)Abstract
The rise of Generative AI has catalyzed a paradigm shift across various domains, offering groundbreaking advancements in text, image, video, audio, and code generation. However, this technological progress has also ushered in heightened cybersecurity risks, as cybercriminals increasingly leverage Generative AI in their malicious activities. This paper endeavours to delineate the diverse security threats emanating from Generative AI, pinpointing their manifestations across different application domains. By dissecting the specific vulnerabilities inherent in text, image, video, audio, and code generation, the paper aims to elucidate the unique challenges posed by each modality. Furthermore, it undertakes an exploration of requisite safeguards and mitigation strategies essential for fostering secure Generative AI creation and deployment. Through this comprehensive analysis, the paper seeks to illuminate the urgent imperative for proactive measures to safeguard against emerging threats and ensure the responsible and safe utilization of Generative AI technologies, thereby fortifying the technological landscape against malicious exploitation.
