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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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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 : 23417
Article Published : 9054
Total Authors : 24024
Total Reviewer : 831
Total Countries : 162
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| Paper Title: | Anomaly-Based Intrusion Detection System Using Machine Learning for Network Security |
| Authors Name: | Snehal Nandkumar Dhaybar , Aishwarya Shivaji Naikare , Rohan Santosh Bankhele |
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IJRTI_209644
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| Published Paper Id: | IJRTI2603102 |
| Published In: | Volume 11 Issue 3, March-2026 |
| DOI: | |
| Abstract: | The increasing dependence on computer networks has made them vulnerable to a wide range of cyber-attacks. Traditional security mechanisms, such as signature-based Intrusion Detection Systems (IDS), often fail to detect new or unknown threats. To address this challenge, the proposed project “Anomaly-Based Intrusion Detection System Using Machine Learning for Network Security” focuses on developing an intelligent IDS that can identify abnormal patterns in network traffic and detect intrusions effectively. The system will be implemented using Python programming language along with libraries such as Scikit-learn, Pandas, NumPy, and TensorFlow for machine learning model development. Benchmark datasets like NSL-KDD and CICIDS2017 will be used for training and testing the system. Various algorithms including Decision Trees, Random Forest, Support Vector Machine (SVM), and Neural Networks will be applied and compared to determine the most efficient model. The project aims to create a robust anomaly-based IDS that provides real-time detection, higher accuracy, and reduced false positives compared to traditional methods, thereby strengthening overall network security. |
| Keywords: | Blockchain, Electronic Health Records (EHR), Privacy, Secure Data Sharing, Smart Contracts, Healthcare Security, Decentralized System, Interoperability, FHIR, Patient-Centric Control |
| Cite Article: | "Anomaly-Based Intrusion Detection System Using Machine Learning for Network Security", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 3, page no.b10-b13, March-2026, Available :http://www.ijrti.org/papers/IJRTI2603102.pdf |
| Downloads: | 00078 |
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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: IJRTI2603102
Registration ID:209644
Published In: Volume 11 Issue 3, March-2026
DOI (Digital Object Identifier):
Page No: b10-b13 Country: Rajgurunagar, pune, Maharashtra, India Research Area: Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2603102 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2603102 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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