Security Threats and Promising Solutions Arising from the Intersection of AI and IoT: A Study of IoMT and IoET Applications

Future Internet Pub Date : 2024-02-29 DOI:10.3390/fi16030085
Hadeel Alrubayyi, Moudy Sharaf Alshareef, Zunaira Nadeem, A. Abdelmoniem, Mona Jaber
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Abstract

The hype of the Internet of Things as an enabler for intelligent applications and related promise for ushering accessibility, efficiency, and quality of service is met with hindering security and data privacy concerns. It follows that such IoT systems, which are empowered by artificial intelligence, need to be investigated with cognisance of security threats and mitigation schemes that are tailored to their specific constraints and requirements. In this work, we present a comprehensive review of security threats in IoT and emerging countermeasures with a particular focus on malware and man-in-the-middle attacks. Next, we elaborate on two use cases: the Internet of Energy Things and the Internet of Medical Things. Innovative artificial intelligence methods for automating energy theft detection and stress levels are first detailed, followed by an examination of contextual security threats and privacy breach concerns. An artificial immune system is employed to mitigate the risk of malware attacks, differential privacy is proposed for data protection, and federated learning is harnessed to reduce data exposure.
人工智能与物联网交汇带来的安全威胁和有前途的解决方案:IoMT 和 IoET 应用研究
物联网是智能应用的推动力,有望提高可访问性、效率和服务质量,但同时也存在安全和数据隐私方面的问题。因此,在研究这些由人工智能赋能的物联网系统时,需要认识到安全威胁,并根据其具体限制和要求制定缓解方案。在这项工作中,我们全面回顾了物联网中的安全威胁和新出现的应对措施,尤其关注恶意软件和中间人攻击。接下来,我们将阐述两个使用案例:能源物联网和医疗物联网。首先详细介绍了用于自动检测能源盗窃和压力水平的创新人工智能方法,然后探讨了上下文安全威胁和隐私泄露问题。采用人工免疫系统来降低恶意软件攻击的风险,提出了数据保护的差异隐私,并利用联合学习来减少数据暴露。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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