https://journals.bohrpub.com/index.php/bijiam <p><strong>BOHR International Journal of Internet of things, Artificial Intelligence and Machine Learning (BIJIAM)</strong> is an open access peer-reviewed journal that publishes articles which contribute new results in all the areas of Internet of things, Artificial Intelligence and Machine Learning. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in this area.</p> en-US <p>Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a <a href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</a> that allows others to share the work with an acknowledgment of the work’s authorship and initial publication in this journal.</p> editor@bohrpub.com (Jayanthi Roselin) bijiam@bohrpub.com (Abinaya) Fri, 10 Jul 2026 05:59:55 +0000 OJS 3.3.0.11 http://blogs.law.harvard.edu/tech/rss 60 https://journals.bohrpub.com/index.php/bijiam/article/view/1035 <p>Generative artificial intelligence is one of the frameworks that help to make safe and rational decisions and analyze complex information to foresee risky behaviors. Now the internet of things (IoT) has spread all over the world, and cyberattacks are used to ensure real-time integration of huge amounts of data. But coordinating with threats and attacks, as well as dealing with hackers and using networks, is an important challenge for the security of the classic IoT. Some of them include rule-based detection, rule-based intrusion detection, and signature-based intrusion detection. There are countless possibilities for generative AI (Gen AI), such as advanced anomaly detection, realistic attack simulation, production of artificially generated data to facilitate the prediction of writers, and automated incident management. Besides, there are a few challenges with Gen AI integration to IoT applications. Problems with competitive management, the computing and technological constraints of IoT devices, ethics issues, and numerous ways for hackers to extract false information from sensors using Gen AI are major challenges. In addition, it could be held responsible for publicizing sensitive information from fake datasets and could have problems with the privacy of sensitive data being trained with Gen AI. The main objective of this research work is to do a detailed analysis of IoT security Gen AI technology. The information, in this report for the 2018–2025 periods, was obtained from the current literature. The paper discusses and addresses some key concepts, and based on that, there are opportunities, challenges, and innovative approaches that are crucial for Gen AI utilization. The next generation thinks that Gen AI will be one of the most important technologies that will affect the next generation of IoT cybersecurity solutions. It is important for them to thoroughly analyze the advantages and disadvantages of this technology.</p> S. L. Fathima Ruksana Copyright (c) 2026 Ruksana ruk https://creativecommons.org/licenses/by/4.0 https://journals.bohrpub.com/index.php/bijiam/article/view/1035 Fri, 10 Jul 2026 00:00:00 +0000