Security Considerations in AI-Robotics: A Survey of Current Methods, Challenges, and Opportunities

被引:2
|
作者
Neupane, Subash [1 ]
Mitra, Shaswata [1 ]
Fernandez, Ivan A. [1 ]
Saha, Swayamjit [1 ]
Mittal, Sudip [1 ]
Chen, Jingdao [1 ]
Pillai, Nisha [1 ]
Rahimi, Shahram [1 ]
机构
[1] Mississippi State Univ, Dept Comp Sci & Engn, Starkville, MS 39762 USA
基金
美国国家科学基金会;
关键词
AI-robotics; cybersecurity; attack surfaces; ethical and legal concerns; human-robot interaction (HRI) security; SYSTEMS; ATTACKS; PRIVACY; TRUST; LANDSCAPE;
D O I
10.1109/ACCESS.2024.3363657
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Robotics and Artificial Intelligence (AI) have been inextricably intertwined since their inception. Today, AI-Robotics systems have become an integral part of our daily lives, from robotic vacuum cleaners to semi-autonomous cars. These systems are built upon three fundamental architectural elements: perception, navigation and planning, and control. However, while the integration of AI in Robotics systems has enhanced the quality of our lives, it has also presented a serious problem - these systems are vulnerable to security attacks. The physical components, algorithms, and data that makeup AI-Robotics systems can be exploited by malicious actors, potentially leading to dire consequences. Motivated by the need to address the security concerns in AI-Robotics systems, this paper presents a comprehensive survey and taxonomy across three dimensions: attack surfaces, ethical and legal concerns, and Human-Robot Interaction (HRI) security. Our goal is to provide readers, developers and other stakeholders with a holistic understanding of these areas to enhance the overall AI-Robotics system security. We begin by identifying potential attack surfaces and provide mitigating defensive strategies. We then delve into ethical issues, such as dependency and psychological impact, as well as the legal concerns regarding accountability for these systems. Besides, emerging trends such as HRI are discussed, considering privacy, integrity, safety, trustworthiness, and explainability concerns. Finally, we present our vision for future research directions in this dynamic and promising field.
引用
收藏
页码:22072 / 22097
页数:26
相关论文
共 50 条
  • [31] AI Agents Under Threat: A Survey of Key Security Challenges and Future Pathways
    Deng, Zehang
    Guo, Yongjian
    Han, Changzhou
    Ma, Wanlun
    Xiong, Junwu
    Wen, Sheng
    Xiang, Yang
    ACM COMPUTING SURVEYS, 2025, 57 (07)
  • [32] A SURVEY OF THE CURRENT USE AND METHODS OF ANALYSIS OF BRONCHOPROVOCATIONAL CHALLENGES
    SCOTT, GC
    BRAUN, SR
    CHEST, 1991, 100 (02) : 322 - 328
  • [33] A survey on wireless body area networks: architecture, security challenges and research opportunities
    Hajar, Muhammad Shadi
    Al-Kadri, M. Omar
    Kalutarage, Harsha Kumara
    COMPUTERS & SECURITY, 2021, 104
  • [34] A survey on artificial intelligence techniques for security event correlation: models, challenges, and opportunities
    Diana Levshun
    Igor Kotenko
    Artificial Intelligence Review, 2023, 56 : 8547 - 8590
  • [35] A survey on artificial intelligence techniques for security event correlation: models, challenges, and opportunities
    Levshun, Diana
    Kotenko, Igor
    ARTIFICIAL INTELLIGENCE REVIEW, 2023, 56 (08) : 8547 - 8590
  • [36] Rumor Propagation: A State-of-the-art Survey of Current Challenges and Opportunities
    Roohani
    Rana, Tushar
    Meel, Priyanka
    2019 2ND INTERNATIONAL CONFERENCE ON INTELLIGENT COMMUNICATION AND COMPUTATIONAL TECHNIQUES (ICCT), 2019, : 64 - 69
  • [37] Anatomical considerations for inhaled aerosol deposition modeling: Methods, applications, challenges and opportunities
    Phalen, Robert F.
    Hoover, Mark D.
    Oldham, Michael J.
    Schmid, Otmar
    Golshahi, Laleh
    JOURNAL OF AEROSOL SCIENCE, 2021, 156
  • [38] Security and Privacy Considerations for IoT Application on Smart Grids: Survey and Research Challenges
    Dalipi, Fisnik
    Yayilgan, Sule Yildirim
    2016 IEEE 4TH INTERNATIONAL CONFERENCE ON FUTURE INTERNET OF THINGS AND CLOUD WORKSHOPS (FICLOUDW), 2016, : 63 - 68
  • [39] A survey on machine and deep learning in semiconductor industry: methods, opportunities, and challenges
    Huang, An Chi
    Meng, Sheng Hui
    Huang, Tian Jiun
    CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2023, 26 (06): : 3437 - 3472
  • [40] A survey on machine and deep learning in semiconductor industry: methods, opportunities, and challenges
    An Chi Huang
    Sheng Hui Meng
    Tian Jiun Huang
    Cluster Computing, 2023, 26 : 3437 - 3472