Securing IoT Devices Using Generative AI Techniques

Author:

Khan Azeem1ORCID,Jhanjhi Noor2ORCID,Abdulhabeb Ghassan Ahmed Ali1,Ray Sayan Kumar2,Ghazanfar Mustansar Ali3,Humayun Mamoona4

Affiliation:

1. University Islam Sultan Sharif Ali, Brunei

2. TUSB, Malaysia

3. University of East London, UK

4. Independent Researcher, UK

Abstract

Generative artificial intelligence (GenAI) is a part of artificial intelligence which has the ability to generate content in various formats ranging from text to videos and images to audio formats. GenAI has the ability to inherently learn from large datasets and can produce results that can be of optimal use in case of cybersecurity. In the current digital landscape, we see a plethora of electronic gadgets connected to this seamless network of devices connected online. These seamless network of devices which were earlier unable to connect due to lack of ip addresses are now able to connect and are improving the quality of human life ranging from home appliances to health domain. From here we see emergence of smart networks which at one side is a boon but at the same time they have the risk of exploitation with unexpected cyberattacks. Hence, this chapter is an effort to highlight the issues concerning cyberthreats and advice on how GenAI can be utilized to mitigate these risks. This chapter focused on applying generative AI to secured IoT devices. By discussing the core concepts of IoT security, such as device authentication and access control, the chapter demonstrated how the next-generation generative AI models, including GANs and VAEs, can boost anomaly detection for device security. The chapter also provided examples of real-life use cases to illustrate how generative AI can be used to optimize the energy grid, protect data privacy, and strengthen cybersecurity efforts. Additionally, this chapter presented the key issues related to ethical considerations pertaining to privacy, bias, and accountability in the development and deployment of responsible AI. Moreover, it introduced the legal aspects of privacy legislation, data protection, and cybersecurity compliance. Finally, the chapter outlined some of the future trends in generative AI for IoT security to name a few are enhanced threat detection, privacy-preserving multimedia processing, and secure communications. The chapter then encourages organizations to start using generative AI to enable systems to become proactive about IoT security and reduce the massive onslaught of cyber threats while navigating an ever-evolving digital landscape.

Publisher

IGI Global

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3