Abstract :

Ai-Based Cyber Threat Detection And Prevention Platform Is An Intelligent Cybersecurity System Developed To Detect And Prevent Cyber Threats In Computer Networks Using Artificial Intelligence (AI) And Machine Learning (ML). With The Rapid Growth Of Internet Services, Cloud Computing, And Digital Communication, Cyber Attacks Such As Malware, Phishing, Ransomware, And Network Intrusions Have Increased Significantly, Making Network Security A Major Challenge For Organizations And Individuals.Traditional Cybersecurity Systems Mainly Depend On Signature-based Detection Methods, Firewalls, And Antivirus Software. These Systems Are Effective Only Against Known Attacks And Often Fail To Detect New Or Unknown Threats, Resulting In Delayed Detection, High False Alarm Rates, Unauthorized Access, And Data Breaches. To Overcome These Limitations, The Proposed System Uses Machine Learning To Analyze Network Traffic And Identify Suspicious Activities Automatically.The Proposed Platform Is Developed Using Python, Flask, Scikitlearn, Pandas, NumPy, And HTML, CSS, And Bootstrap For The Web Interface. The System Is Trained Using The NSL-KDD Dataset, And The Random Forest Machine Learning Algorithm Is Used To Classify Network Traffic As Normal Or Anomalous With High Accuracy. The Platform Also Provides Suitable Prevention Recommendations For Detected Threats, Enabling Users To Take Immediate Security Measures. Keywords: Artificial Intelligence, Machine Learning, Cybersecurity, Intrusion Detection System (IDS), NSLKDD Dataset, Network Security, Threat Detection, Cyber Attack Prevention.

Published:

05-8-2026

Issue:

Vol. 26 No. 8 (2026)

Page Nos:

630 - 638

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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