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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 118
Article Submitted : 21686
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Total Authors : 22487
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| Paper Title: | FAKE IDENTITY DETECTION AMONG HUMAN VS BOT USING MACHINE LEARNING |
| Authors Name: | DR.V.SARANYA , Santhiya B , Shreenithi S , Sruthikka S , Thrisha S |
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IJRTI_203748
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| Published Paper Id: | IJRTI2505134 |
| Published In: | Volume 10 Issue 5, May-2025 |
| DOI: | |
| Abstract: | Fake identity detection has become a critical challenge in cybersecurity, fraud prevention, and maintaining online authenticity. With the growing use of social media, banking, and e-commerce platforms, distinguishing between human users and bots has gained immense importance. This study focuses on applying Machine Learning (ML) techniques to identify fake identities efficiently. Natural Language Processing (NLP) techniques like Term Frequency-Inverse Document Frequency (TF-IDF) and Word Embeddings are used to extract meaningful patterns from user interactions. These features help in understanding the subtle behavioral differences between bots and humans. Publicly available datasets containing labeled human and bot accounts were used for training and testing. Multiple ML models, including Support Vector Machine (SVM), Random Forest, Gradient Boosting, and Deep Neural Networks (DNN), were evaluated. Among them, Gradient Boosting and DNN achieved the highest accuracy and reliability in detecting bots. Performance metrics like precision, recall, F1-score, and accuracy were used to evaluate the models comprehensively. |
| Keywords: | Fake identity detection, bot detection, Random Forest, Support Vector Machine, XGBoost, Deep Neural Network, human-bot classification. |
| Cite Article: | "FAKE IDENTITY DETECTION AMONG HUMAN VS BOT USING MACHINE LEARNING", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 5, page no.b279-b284, May-2025, Available :http://www.ijrti.org/papers/IJRTI2505134.pdf |
| Downloads: | 000489 |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 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: IJRTI2505134
Registration ID:203748
Published In: Volume 10 Issue 5, May-2025
DOI (Digital Object Identifier):
Page No: b279-b284 Country: Kaniyur coimbatore , Tamilnadu , India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2505134 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2505134 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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