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Different Attack and Defense Types for AI Cybersecurity

  • Jing Zou,
  • Shungeng Zhang,
  • Meikang Qiu

摘要

Artificial Intelligence emerged as a field of study in the mid-20th century, driven by the ambition to develop machines capable of emulating human intelligence and reasoning. However, its rapid advancement has brought forth many cybersecurity challenges, encompassing data security, privacy preservation, and model resilience. Consequently, the field of AI necessitates tailored cybersecurity defense mechanisms and protective technologies to safeguard its integrity. In this paper, we delve into the realm of AI cybersecurity, exploring its prominent areas and delineating various attacks occurring across different phases of the Artificial Intelligence lifecycle. Furthermore, we elucidate defensive strategies against adversarial attacks, encompassing preprocessing techniques, adversarial training methodologies, and distillation methods.