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IITM Journal of Information Technology

ISSN (P) 2395-5457 | Single Blind Peer Reviewed Journal

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INSTITUTE OF INNOVATION IN TECHNOLOGY & MANAGEMENT
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An Analytical Survey of Various Learning Methods for IoT Based Privacy Preservation.

Pardeep Singh
Author
 Gaurav Aggarwal
Author

Keywords: cloud computing, Machine Learning, Internet of Things,, Intrusion Detection, PSO

DOI:https://doi.org/10.48165/iitmjit.2025.11.1.4

Abstract: The Internet of Things (IoT) involves a network of Internet-connected gadgets that can detect, communicate, and respond to changes in their surroundings. Billions of these computer devices are linked to the Internet in order to share data with one another and/or with their infrastructure. The Internet of Things (IoT) aims to enable a multitude of smart services in practically every facet of our everyday interactions while also improving our general level of life. However, as IoT becomes more widely adopted, there are serious privacy worries about losing control over how our data is gathered and distributed with others. As a result, privacy is an essential prerequisite for every IoT ecosystem and a major barrier to mainstream consumer adoption. The ultimate source of consumer annoyance is the inability to regulate personal information in raw form that is directly transmitted.

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