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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
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (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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Issue: April 2026
Volume 11 | Issue 4
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 119
Article Submitted : 23421
Article Published : 9054
Total Authors : 24024
Total Reviewer : 831
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| Paper Title: | ML-Based Cyber Attack Detection with Endpoint Deception and Secure Node-Scoped Intelligence Architecture |
| Authors Name: | Bhavanari Shiva Satwik , Challa Yogendra , Jayasurya M , Kadapala Abhijith Reddy , Fenita |
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IJRTI_210635
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| Published Paper Id: | IJRTI2603144 |
| Published In: | Volume 11 Issue 3, March-2026 |
| DOI: | |
| Abstract: | Adaptive, multi-step assaults that usually get past conventional, signature-based defenses make modern cybersecurity a shifting target. This study introduces a hybrid cybersecurity framework that combines proactive endpoint deception, anomaly analysis, and machine learning-based detection to overcome the shortcomings of static security models. The architecture uses two layers: an Isolation Forest model detects latent behavioral anomalies, and a Random Forest classifier detects known attack patterns. The architecture uses honeytokens strategic digital tripwires positioned throughout the network to aggressively expose illegal exploration. A secure, multi-node backend with segregated APIs is used to expose all detection signals, which are combined into a consolidated risk score. With an inference delay of <10ms, experimental results on a dataset of 15,000 behavioral samples show near perfect accuracy. |
| Keywords: | Cybersecurity, Machine Learning, Intrusion Detection, Anomaly Detection, Honeytokens |
| Cite Article: | "ML-Based Cyber Attack Detection with Endpoint Deception and Secure Node-Scoped Intelligence Architecture", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 3, page no.b381-b388, March-2026, Available :http://www.ijrti.org/papers/IJRTI2603144.pdf |
| Downloads: | 00068 |
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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: IJRTI2603144
Registration ID:210635
Published In: Volume 11 Issue 3, March-2026
DOI (Digital Object Identifier):
Page No: b381-b388 Country: Bengaluru, Karnataka, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2603144 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2603144 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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