International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 8, Issue 2 (March-April 2026) Submit your research before last 3 days of April to publish your research paper in the issue of March-April.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 8 Issue 2
March-April 2026

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

CYBERSECL: An AI-Based Cybersecurity Training and Threat Detection Platform

Author(s) Mr. MANJUNATHA G, Ms. SANJANA D D, Mr. SIDDHANT C NAGATHAN, Ms. SINCHANA G P, Ms. SINDHU B S
Country India
Abstract The rising frequency of cyberattacks has necessitated the integration of Artificial Intelligence (AI) into modern cybersecurity frameworks. This paper presents Cybersec, an interactive and intelligent platform designed to enhance cybersecurity awareness and defense readiness. The system integrates a web-based training dashboard, real-time network threat analysis, and AI-driven anomaly detection to simulate and identify cyber threats effectively. Developed using a hybrid architecture combining Next.js (frontend), Node.js (API gateway), and Flask (AI engine), the platform facilitates interactive learning and autonomous threat classification. Empirical testing demonstrated reliable detection accuracy using TensorFlow models, emphasizing its potential as a scalable educational and defense system. In the rapidly evolving digital landscape, cybersecurity threats have become increasingly sophisticated, demanding advanced solutions for detection and prevention. CyberSecL is an AI-based cybersecurity training and threat detection system designed to address these challenges by combining automated threat detection with interactive training modules. This system leverages machine learning and deep learning techniques to identify and mitigate cyber threats in real time while providing users with comprehensive cybersecurity training to enhance awareness and response capabilities. This report presents the design, implementation, experimental evaluation, and potential applications of CyberSecL , highlighting its effectiveness and contributions to the cybersecurity domain.
Keywords Cybersecurity, Artificial Intelligence, Flask, Node.js, Next.js, Deep Learning, Threat Detection.
Field Engineering
Published In Volume 7, Issue 6, November-December 2025
Published On 2025-12-11
DOI https://doi.org/10.36948/ijfmr.2025.v07i06.62741
View / Download PDF File

Share this



E-ISSN 2582-2160
CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 8 Isu 2Cover Page Vol 8 Isu 1Cover Page Vol 7 Isu 6

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJFMR
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +91-9687-828-838 editor@ijfmr.com
Powered by Sky Research Publication and Journals