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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Exploring the Integration of Edge Computing and Machine Learning in Enhancing Security for IoT Systems: Opportunities and Challenges in Intrusion Detection |
| Authors Name: | Mr. Ramani K , Dr. N Chandrakala , Mr. G Binu |
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IJNRD_213359
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| Published Paper Id: | IJNRD2402072 |
| Published In: | Volume 9 Issue 2, February-2024 |
| DOI: | |
| Abstract: | The key elements of current cybersecurity approaches involve Intrusion Detection Systems (IDSs), which employ various techniques and architectures for intrusion detection. IDSs can utilize either a signature-based approach, involving cross-checking monitored events with a database of known intrusion patterns, or an anomaly-based approach, where the system learns normal behavior and detects deviations. This study focuses on surveying the utilization of IDSs in Internet of Things (IoT) networks, particularly in conjunction with edge computing to support IDS implementation. The paper identifies emerging challenges in deploying IDS in edge scenarios and proposes solutions. Emphasis is placed on anomaly-based IDSs, highlighting primary techniques for anomaly detection. Additionally, machine learning techniques and their application in the IDS context are explored, along with an analysis of the anticipated advantages and disadvantages associated with specific techniques. |
| Keywords: | Intrusion Detection Systems, Internet of Things, Anomaly Detection, Machine Learning |
| Cite Article: | "Exploring the Integration of Edge Computing and Machine Learning in Enhancing Security for IoT Systems: Opportunities and Challenges in Intrusion Detection", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 2, page no.a620-a646, February-2024, Available :http://www.ijnrd.org/papers/IJNRD2402072.pdf |
| Downloads: | 000118759 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2402072 Registration ID: 213359 Published In: Volume 9 Issue 2, February-2024 DOI (Digital Object Identifier): Page No: a620-a646 Country: Erode, Tamilnadu, India Research Area: Science Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2402072 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2402072 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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