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@article{201184,
        author = {Ramkumar B and Rathin N and Mrs.Abarnaswara R},
        title = {Automatic Attack Eradication System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {4595-4598},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=201184},
        abstract = {Distributed Denial-of-Service (DDoS) attacks and intrusions overwhelm traditional firewalls. This paper presents AAES, a MERN-stack cybersecurity system automating detection, classification, and eradication. Using CICIDS2017 dataset and Random Forest (RF) classifier, AAES achieves 98.2% accuracy with 45ms response time. Node.js orchestrates real-time traffic analysis; React dashboard visualizes threats; MongoDB logs eradications. AWS Lambda auto-blocks malicious IPs. Experiments show 28% latency improvement over Snort.},
        keywords = {Cybersecurity, Anomaly Detection, MERN Stack, Random Forest, DDoS Mitigation.},
        month = {May},
        }