UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 9 Issue 2
February-2022
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2202057


Registration ID:
319823

Page Number

a447-a452

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Title

COLLABORATIVE INTRUSION DETECTION SYSTEM FOR IOT DEVICES USING DEEP LEARNING TECHNIQUES

Abstract

Numerous researchers are deeply focused in the Internet of Things (IoT) and its applications because they render life become simple. Based on its widespread recognition, attacks targeting those devices including denial of service attacks as well as sybil attacks, have increased dramatically, potentially causing the system to become unavailable. Thus, it has become mandatory that the technique for identification of malware in the IoT is essential. This research proposes CNN-IoT a collaborative intrusion detection system (IDS) that monitors IoT devices regarding malicious activity. The NSW-NB15 dataset was utilised to evaluate the proposed system. An accuracy of 98.54% has been achieved with lower type II error rate around 0.01. The performance evaluations show that the proposed method outperforms the other existing techniques available in the literatures.

Key Words

IoT; edge computing; collaborative; malware

Cite This Article

"COLLABORATIVE INTRUSION DETECTION SYSTEM FOR IOT DEVICES USING DEEP LEARNING TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 2, page no.a447-a452, February-2022, Available :http://www.jetir.org/papers/JETIR2202057.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"COLLABORATIVE INTRUSION DETECTION SYSTEM FOR IOT DEVICES USING DEEP LEARNING TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 2, page no. ppa447-a452, February-2022, Available at : http://www.jetir.org/papers/JETIR2202057.pdf

Publication Details

Published Paper ID: JETIR2202057
Registration ID: 319823
Published In: Volume 9 | Issue 2 | Year February-2022
DOI (Digital Object Identifier):
Page No: a447-a452
Country: Thiruvattaru, Tamilnadu, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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