Share these talks and lectures with your colleagues
Invite colleaguesPractice paper
Cyber security in smart home Internet of Things devices: Threat detection and prevention using artificial intelligence
Journal of AI, Robotics & Workplace Automation,
3
(4),
339-349
(2025)
Abstract
The Internet of Things (IoT) has permeated every element of life in this day and age of technology, including smart environments, smart homes and smart scenarios. Many IoT devices in smart homes operate non-stop and in big quantities. Living in such areas might be more serene with improved security and authentication of these smart gadgets. To ensure that smart IoT devices operate flawlessly, it is crucial to keep an eye on their actions. These devices are readily attacked by hackers because of their tiny size, low power and resource consumption and ease of use. It is essential to defend the smart home environment’s features and integrity against outside threats. Machine learning (ML) has been essential in recognising these kinds of harmful efforts and actions. There are several ML techniques available to identify both typical and anomalous IoT device traffic behaviour. This research suggested an anomaly detection method for smart homes based on ML and several classifiers. The BoT-IoT dataset from the University of New South Wales (UNSW) is used for testing and assessment. Using a dataset of IoT devices, ML models based on four classifiers are constructed. Random forest, decision tree and AdaBoost have weighted precision, recall and F1 score of 1 for the test dataset, but an artificial neural network (ANN) has 0.98, 0.96 and 0.96, accordingly. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: smart homes; IoT environment; cyber security; network anomaly detection; smart environments; machine learning
The full article is available to subscribers to the journal.
Author's Biography
Himmat Rathore is a distinguished Information Security expert specialising in network and communication, based in Austin, Texas. With over two decades of experience, he holds five Cisco Certified Interwork Expert (CCIE) certifications and is a Certified Informational Systems Security Professional (CISSP), demonstrating deep technical expertise. He serves as the Senior Regional Manager for Sales and Engineering at DISYS Solutions, Inc., overseeing multimillion-dollar projects in the Texas K12 sector. His leadership has driven over US$75m in technological advancements, including large-scale network infrastructure for Garland Independent School District. A Institution of Engineering and Technology (IET) Fellow IET and Senior Member of IEEE (SMIEEE), Himmat actively contributes to industry discourse, particularly in smart cities and Internet of Things (IoT). He established DISYS Solutions’ Managed Services vertical and played a key role in securing federal funding for critical projects. Recognised for his strategic vision and business acumen, he has influenced key decision making at the highest levels. Beyond his professional achievements, Himmat is dedicated to continuous learning and mentorship within the cyber security and networking communities.
Priyanka Singla is an Assistant Professor with over a decade of experience in academia. She has been actively engaged in teaching and research since 2014. Currently pursuing a PhD in job recommendation systems, her research interests encompass artificial intelligence (AI), deep learning (DL) and their applications across various domains. Priyanka has contributed to multiple research initiatives focused on leveraging AI-driven solutions to address real-world challenges. Her work emphasises the development of intelligent systems that enhance decision-making processes and optimise recommendations using advanced machine learning (ML) techniques. Priyanka has published several research papers in reputed journals and presented at international conferences, demonstrating her commitment to academic excellence and innovation. With a strong inclination toward interdisciplinary research, she continuously explores emerging AI technologies to drive impactful solutions. Through her work, she aims to bridge the gap between theoretical advancements and practical applications, fostering the adoption of AI in diverse fields.
