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IJNRD
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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Impact Factor : 8.76

Issue per Year : 12

Volume Published : 8

Issue Published : 80

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Total Authors : 7078

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Published Paper Details
Paper Title: Cyber Bullying Detection on Social Media Using Machine Learning
Authors Name: S.Mani Arasi
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IJNRD_181487
Published Paper Id: IJNRD2205116
Published In: Volume 7 Issue 5, May-2022
DOI:
Abstract: Malicious software deliberately affects the computer systems. Malware are analyzed using static or dynamic analysis techniques. Using these techniques, unique patterns are classified and predicted to detect malware correctly. In the past decade, many malware detection techniques have been proposed using various techniques. Mostly network based, for example DDoS attacks are widely known network security risk. Typically, they involve overflowing network devices with more requests than they can handle, thus preventing the server from answering legitimate requests. The biggest security risks involve software. Software attacks can exploit entire systems, steal information, alter data, deny service and compromise or damage devices. We are particularly interested in dynamic analysis to develop the malware detection system using machine learning techniques. In this paper, a behavior-based malware detection technique has been proposed. For developing this technique, we setup the dynamic analysis environment and run malware samples using the classification algorithms. Then, various behavior artifacts like PSI, API calls, registry changes, file operations, etc. were extracted for malware detection system. For developing this technique, we setup the dynamic analysis environment and run malware samples using the classification algorithms.
Keywords: Cyber bullying, Social Media, BERT, NLP, Semi-supervised learning , Twitter API.
Cite Article: "Cyber Bullying Detection on Social Media Using Machine Learning", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.7, Issue 5, page no.975-981, May-2022, Available :http://www.ijnrd.org/papers/IJNRD2205116.pdf
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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
Publication Details: Published Paper ID:IJNRD2205116
Registration ID: 181487
Published In: Volume 7 Issue 5, May-2022
DOI (Digital Object Identifier):
Page No: 975-981
Country: Thoothukodu, Tamil nadu, India
Research Area: Science
Publisher : IJ Publication
Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2205116
Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2205116
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016

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