Smart City Gnosys

Smart city article details

Title	Hybrid Machine Learning Techniques For Secure Iot Applications
ID_Doc	29775
Authors	Balasingam U.; Prathibha S.B.; Swetha K.R.; Muruganandam C.; Pol U.R.
Year	2023
Published	Pragmatic Internet of Everything (IOE) for Smart Cities: 360-Degree Perspective
DOI	http://dx.doi.org/10.2174/9789815136173123010012
Abstract	Web sensing devices capture and transmit data from the physical environment to a central place using rapid advances in software, hardware, and IoT technologies. Depending on the source, the overall count of web-connected devices is estimated to be between 50 and 100 billion by 2025. The amount of data released will increase as the population expands and technology improves, which is already happening. The Internet of Things (IoT) technology connects and interacts with the physical and virtual worlds. A gadget linked to the Internet is called an IoT. Intellectual data handling and investigation are required to construct smart IoT requests. This article gives knowledge about the Machine learning (ML) algorithms available for dealing with IoT data challenges, using smart cities as the primary use case. This article looks at common IoT diagnostic applications. This research compares and evaluates the predicted precision and understandability of supervised and unattended ML models. These technologies are briefly addressed in desktop, mobile, and cloud computing settings. © 2023, Bentham Books imprint.
Author Keywords	Cloud; Hybrid; Internet; Security; Supervised

Similar Articles

Id	Similarity	Authors	Title	Published
35963	0.913	Mahdavinejad M.S.; Rezvan M.; Barekatain M.; Adibi P.; Barnaghi P.; Sheth A.P.	Machine Learning For Internet Of Things Data Analysis: A Survey	Digital Communications and Networks, 4, 3 (2018)
56602	0.906	Mishra S.; Tyagi A.K.	The Role Of Machine Learning Techniques In Internet Of Things-Based Cloud Applications	Internet of Things (2022)
36006	0.898	Jindal M.; Gupta J.; Bhushan B.	Machine Learning Methods For Iot And Their Future Applications	Proceedings - 2019 International Conference on Computing, Communication, and Intelligent Systems, ICCCIS 2019, 2019-January (2019)
9931	0.898	Pradhan N.; Singh A.S.; Sagar S.; Singh A.; Elngar A.A.	Application Of Machine Learning And Iot For Smart Cities	Machine Learning Approaches for Convergence of IoT and Blockchain (2021)
4273	0.894	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)
36075	0.89	Bzai J.; Alam F.; Dhafer A.; Bojović M.; Altowaijri S.M.; Niazi I.K.; Mehmood R.	Machine Learning-Enabled Internet Of Things (Iot): Data, Applications, And Industry Perspective	Electronics (Switzerland), 11, 17 (2022)
35964	0.89	Gangal R.; Johri P.; Kumar A.	Machine Learning For Internet Of Things: A Recapitulation	2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions), ICRITO 2021 (2021)
35990	0.889	Chen Z.; Tian P.; Qian C.; Liao W.; Hussaini A.; Yu W.	Machine Learning Frameworks In Iot Systems: A Survey, Case Study, And Future Research Directions	Smart Spaces: a volume in Intelligent Data-Centric Systems (2024)
47748	0.889	Ghaffari A.; Jelodari N.; pouralish S.; derakhshanfard N.; Arasteh B.	Securing Internet Of Things Using Machine And Deep Learning Methods: A Survey	Cluster Computing, 27, 7 (2024)
37192	0.888	Mahor V.; Bijrothiya S.; Mishra R.; Rawat R.	Ml Techniques For Attack And Anomaly Detection In Internet Of Things Networks	Autonomous Vehicles, 1 (2022)