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<p>The Internet of Things (IoT) refers to a network of digitally interconnected devices embedded with sensors, software, and other technologies that gather information and exchange it with each other over the internet. Meanwhile, generative artificial intelligence (AI) encompasses AI technologies that excel at producing new data outputs that closely resemble authentic data, thanks to advanced techniques such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). Because IoT systems process a lot of private data very often, and because of the danger of compromised data, there are fears that major privacy breaches could result from even a minor problem with their protection. While IoT opens up opportunities for comprehensive change, it also brings a lot of additional security and privacy challenges. These problems can be solved well with generative AI, which is a key part of making IoT systems more predictive by creating training sets and test data that protect privacy and make IoT networks stronger and more reliable wherever it has been used. Fusing generative AI with IoT in various industries, such as manufacturing and energy management, has led to increased efficiency and lower running costs. This combination also results in more intelligent systems that respond faster, thereby further deepening the technological landscape.</p>

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Emergent defenders: generative AI’s role in safeguarding IoT ecosystems

  • 期刊论文

  • 发表日期：

    2025年8月30日

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  • Poonam Rani,
  • Harkesh Sehrawat,
  • Amandeep Kaur,
  • Robertas Damaševičius

摘要

The Internet of Things (IoT) refers to a network of digitally interconnected devices embedded with sensors, software, and other technologies that gather information and exchange it with each other over the internet. Meanwhile, generative artificial intelligence (AI) encompasses AI technologies that excel at producing new data outputs that closely resemble authentic data, thanks to advanced techniques such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). Because IoT systems process a lot of private data very often, and because of the danger of compromised data, there are fears that major privacy breaches could result from even a minor problem with their protection. While IoT opens up opportunities for comprehensive change, it also brings a lot of additional security and privacy challenges. These problems can be solved well with generative AI, which is a key part of making IoT systems more predictive by creating training sets and test data that protect privacy and make IoT networks stronger and more reliable wherever it has been used. Fusing generative AI with IoT in various industries, such as manufacturing and energy management, has led to increased efficiency and lower running costs. This combination also results in more intelligent systems that respond faster, thereby further deepening the technological landscape.