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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: July 2026
Volume 11 | Issue 7
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 122
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| Paper Title: | AI-Powered Intrusion Detection System Using Machine Learning |
| Authors Name: | Gandham Rohan , Ch Harsha Vardhan Rao , Dr. D. Koteswara Rao , Dr. D. Deepika |
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IJRTI_212745
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| Published Paper Id: | IJRTI2606100 |
| Published In: | Volume 11 Issue 6, June-2026 |
| DOI: | |
| Abstract: | Cybersecurity is a worry today because digital communication systems, cloud platforms and network-based services are growing really fast. Old Intrusion Detection Systems (IDS) mostly use -defined signatures and static rules which makes them not very good at stopping new and changing cyber threats like DDoS attacks, probing attacks and people trying to get in without permission. These old systems have some limitations so we need smarter and more flexible security solutions. This paper talks about an AI-Powered Intrusion Detection System that uses Machine Learning to spot network traffic in real time. The system we propose uses Random Forest and Decision Tree algorithms to look at network traffic features and figure out if an attack is happening. We also have a web-based dashboard that lets you monitor traffic do batch analysis with CSV files see attack visualizations and get reports on predictions. We trained our system using known datasets like NSL-KDD, UNSW-NB15 and CIC-IDS2017. Our test results show that our system can detect attacks accurately with fewer false alarms and classify attacks more efficiently. The way our system is set up is modular and scalable which makes it good, for cybersecurity applications. |
| Keywords: | Intrusion Detection System, Machine Learning, Random Forest, Decision Tree, Cybersecurity, Network Traffic Analysis, DDoS Detection, Anomaly Detection, Real-Time Monitoring. |
| Cite Article: | "AI-Powered Intrusion Detection System Using Machine Learning", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 6, page no.a941-a945, June-2026, Available :http://www.ijrti.org/papers/IJRTI2606100.pdf |
| Downloads: | 00094 |
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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: IJRTI2606100
Registration ID:212745
Published In: Volume 11 Issue 6, June-2026
DOI (Digital Object Identifier):
Page No: a941-a945 Country: kumuram bheem, Telangana, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2606100 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2606100 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
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