Smart City Gnosys

Smart city article details

Title	Securing Internet Of Things Using Machine And Deep Learning Methods: A Survey
ID_Doc	47748
Authors	Ghaffari A.; Jelodari N.; pouralish S.; derakhshanfard N.; Arasteh B.
Year	2024
Published	Cluster Computing, 27, 7
DOI	http://dx.doi.org/10.1007/s10586-024-04509-0
Abstract	The Internet of Things (IoT) is a vast network of devices with sensors or actuators connected through wired or wireless networks. It has a transformative effect on integrating technology into people’s daily lives. IoT covers essential areas such as smart cities, smart homes, and health-based industries. However, security and privacy challenges arise with the rapid growth of IoT devices and applications. Vulnerabilities such as node spoofing, unauthorized access to data, and cyberattacks such as denial of service (DoS), eavesdropping, and intrusion detection have emerged as significant concerns. Recently, machine learning (ML) and deep learning (DL) methods have significantly progressed and are robust solutions to address these security issues in IoT devices. This paper comprehensively reviews IoT security research focusing on ML/DL approaches. It also categorizes recent studies on security issues based on ML/DL solutions and highlights their opportunities, advantages, and limitations. These insights provide potential directions for future research challenges. © The Author(s) 2024.
Author Keywords	Deep learning; Internet of things; Machine learning; Security

Similar Articles

Id	Similarity	Authors	Title	Published
33508	0.944	Saini K.S.; Chaudhary S.	Investigation On Attack Detection In Iot Networks: A Study And Analysis Of The Existing Machine Learning And Deep Learning Techniques	3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025 (2025)
34139	0.941	Selvam R.; Velliangiri S.	Iotsdl: Internet Of Things Security For Deep Learning Techniques-A Research Perspectives	2023 International Conference on Computer Communication and Informatics, ICCCI 2023 (2023)
32899	0.939	Sarker I.H.; Khan A.I.; Abushark Y.B.; Alsolami F.	Internet Of Things (Iot) Security Intelligence: A Comprehensive Overview, Machine Learning Solutions And Research Directions	Mobile Networks and Applications, 28, 1 (2023)
9199	0.939	Mazhar T.; Talpur D.B.; Shloul T.A.; Ghadi Y.Y.; Haq I.; Ullah I.; Ouahada K.; Hamam H.	Analysis Of Iot Security Challenges And Its Solutions Using Artificial Intelligence	Brain Sciences, 13, 4 (2023)
36064	0.936	Alfahaid A.; Alalwany E.; Almars A.M.; Alharbi F.; Atlam E.; Mahgoub I.	Machine Learning-Based Security Solutions For Iot Networks: A Comprehensive Survey	Sensors, 25, 11 (2025)
5172	0.929	Rodríguez E.; Otero B.; Canal R.	A Survey Of Machine And Deep Learning Methods For Privacy Protection In The Internet Of Things	Sensors, 23, 3 (2023)
55462	0.927	Abdulla H.; Al-Raweshidy H.; Awad W.	The Era Of Internet Of Things: Towards Better Security Using Machine Learning	2023 International Conference on IT Innovation and Knowledge Discovery, ITIKD 2023 (2023)
30732	0.925	Amine M.S.; Nada F.A.; Hosny K.M.	Improved Model For Intrusion Detection In The Internet Of Things	Scientific Reports, 15, 1 (2025)
4273	0.925	Qureshi A.; Qureshi M.A.; Haider H.A.; Khawaja R.	A Review On Machine Learning Techniques For Secure Iot Networks	Proceedings - 2020 23rd IEEE International Multi-Topic Conference, INMIC 2020 (2020)
23845	0.923	Mishra K.; Dutta T.	Enhancing Iot Security Through Deep Learning: A Comprehensive Study	Lecture Notes in Electrical Engineering, 1194 (2024)