A Fuzzy-based approach to Enhance Cyber Defence Security for Next-generation IoT

Journal article


Makkar, A., Ghosh, U., Sharma, P.K. and Javed, A. 2023. A Fuzzy-based approach to Enhance Cyber Defence Security for Next-generation IoT. IEEE Internet of Things Journal. Vol 10 (Issue 3), pp. 2079-2086. https://doi.org/10.1109/jiot.2021.3053326
AuthorsMakkar, A., Ghosh, U., Sharma, P.K. and Javed, A.
Abstract

In the modern era, the Cognitive Internet of Things (CIoT) in conjunction with IoT evolves which provides the intelligence power of sensing and computation for next-generation IoT (Nx-IoT) networks. The data scientists have discovered a large amount of techniques for knowledge discovery from processed data in CIoT. This task is accomplished successfully and data proceeds for further processing. The major cause for the failure of IoT devices is due to the attacks, in which Web spam is more prominent. There seems a requirement of a technique which can detect the Web spam before it enters into a device. Motivated from these issues, in this article, a cognitive spammer framework (CSF) for Web spam detection is proposed. CSF detects the Web spam by fuzzy rule-based classifiers along with machine learning classifiers. Each classifier produces the quality score of the webpage. These quality scores are then ensembled to generate a single score, which predicts the spamicity of the webpage. For ensembling, the fuzzy voting approach is used in CSF. The experiments were performed using a standard data set WEBSPAM-UK 2007 with respect to accuracy and overhead generated. From the results obtained, it has been demonstrated that CSF improves the accuracy by 97.3%, which is comparatively high in comparison to the other existing approaches in the literature.

KeywordsCognitive; ensemble; fuzzy; Web spam
Year2023
JournalIEEE Internet of Things Journal
Journal citationVol 10 (Issue 3), pp. 2079-2086
PublisherIEEE
ISSN2327-4662
Digital Object Identifier (DOI)https://doi.org/10.1109/jiot.2021.3053326
Web address (URL)http://www.scopus.com/inward/record.url?eid=2-s2.0-85100488959&partnerID=MN8TOARS
Accepted author manuscript
File Access Level
Open
Output statusPublished
Publication dates
Online21 Jan 2021
01 Feb 2023
Publication process dates
Deposited22 May 2023
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