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Security and Privacy Concerns in ChatGPT

In: Beyond AI

Author

Listed:
  • Ken Huang

    (DistributedApps.ai)

  • Fan Zhang

    (Yale University)

  • Yale Li

    (United Nations Digital Security Alliance)

  • Sean Wright

    (Universal Music Group)

  • Vasan Kidambi

    (AISecHub)

  • Vishwas Manral

    (McAfee Enterprise)

Abstract

This chapter provides a comprehensive analysis of the security and privacy concerns in AI models, specifically ChatGPT. It explores potential security threats such as cyberattacks, deep fake creation, model poisoning, API, and prompt injection attacks. Privacy issues, including data leakage, misuse, and unauthorized access, are investigated. User perspectives, including public trust issues, privacy demands, and the need for balancing security with innovation, are also assessed. The chapter concludes by proposing mitigation strategies for these concerns. These involve safeguards against security risks, mitigation measures for deepfakes and model poison attacks, and steps to counter API and prompt injection attacks. Furthermore, it suggests techniques for addressing privacy concerns and strategies to prevent data leakage and unauthorized access.

Suggested Citation

Handle: RePEc:spr:fuobcp:978-3-031-45282-6_11
DOI: 10.1007/978-3-031-45282-6_11
as

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