International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | A Comparative Survey of Intrusion Detection Systems in IOT Environment with Machine Learning Frameworks |
|---|---|
| ABSTRACT | In the era we live in, the Internet is used by everyone. People, devices and smart things are connected to it. The Internet has made the world a smaller place. It is easier to converse with persons living at far distance and to share data in a moment. However, over the period of its usage, we have also learnt that the Internet is not a safe place for our information. People with bad intentions try to steal or misuse our information every day. We therefore need a system that can stop these people from doing such things. People use ways to make Intrusion Detection Systems. These systems use Machine Learning and Deep Learning to find people on the Internet. This paper will look at the Machine Learning and Deep Learning ways that are used to find identify such activities in cloud environments and IoT-based systems. We will look at how these ways work and how they can help keep our information safe. We shall also compare the Machine Learning and Deep Learning ways to see which ones are the best options. Further we will compare them based on how accurate they are. We will use things like accuracy and precision and sensitivity to compare them. We need to use them in a way that helps us and keeps our information safe. |
| AUTHOR | SNEHAL P. CHINCHOLKAR, DR.AJAY P. THAKARE Research Scholar, PRMCEAM Bandera, Sant Gadge Baba Amravati University, Amravati, India Principal, Prof. Ram Meghe College of Engineering and Management Bandera, Amravati, India |
| VOLUME | 186 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1407039 |
| pdf/39_A Comparative Survey of Intrusion Detection Systems in IOT Environment with Machine Learning Frameworks.pdf | |
| KEYWORDS | |
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