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Cyber-Physical Systems (CPS) have emerged as a result of recent technological breakthroughs. These systems smoothly combine the digital and practical realms in a variety of areas, including autonomous devices, medical, and agriculture. With the use of artificial intelligence (AI) and machine learning (ML), the combination offers potential for increased efficiency and productivity. Even so, the intricacy of CPS raises issues with bias, accessibility, and confidence in auto- mated methods for making decisions. In addition to addressing the difficulties in understanding and putting faith in AI systems used in CPS, this study examines the importance of AI and ML in enabling CPS in these domains. In particular, it is explored how explainable AI (XAI) might improve the dependability and credibility of AI-enabled decisions. Important issues including security, privacy, and visibility are noted, as well as the requirement for developing trust via accountability, openness, and ethical factors.

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Toward Enhancing the Security of AI-Driven Intrusion Detection System in Cyber-Physical System

  • 章节

  • 发表日期：

    2026年

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  • Himani Bhatt,
  • Saurabh Rana,
  • Mandeep Mittal

摘要

Cyber-Physical Systems (CPS) have emerged as a result of recent technological breakthroughs. These systems smoothly combine the digital and practical realms in a variety of areas, including autonomous devices, medical, and agriculture. With the use of artificial intelligence (AI) and machine learning (ML), the combination offers potential for increased efficiency and productivity. Even so, the intricacy of CPS raises issues with bias, accessibility, and confidence in auto- mated methods for making decisions. In addition to addressing the difficulties in understanding and putting faith in AI systems used in CPS, this study examines the importance of AI and ML in enabling CPS in these domains. In particular, it is explored how explainable AI (XAI) might improve the dependability and credibility of AI-enabled decisions. Important issues including security, privacy, and visibility are noted, as well as the requirement for developing trust via accountability, openness, and ethical factors.