Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
@article{198481,
author = {Kosana Manohar and Kuridi dwaraka sai ganesh and Kommisetti Sai Surya Manikanta and Kuracha Sri Satya Murali Raghava and Dr.P.Thamarai},
title = {BEHAVIOR BASED CONTINUOUS AUTHENTICATION AND REMOTE SECURITY MANAGEMENT SYSTEM},
journal = {International Journal of Innovative Research in Technology},
year = {2026},
volume = {12},
number = {11},
pages = {9485-9495},
issn = {2349-6002},
url = {https://ijirt.org/article?manuscript=198481},
abstract = {The Behavioral Biometrics Security Control System is a comprehensive security framework designed to enhance intrusion detection and user authentication through continuous behavioral analysis. Unlike traditional authentication methods that rely on passwords or PINs, which can be stolen or shared, this system introduces an additional layer of security by monitoring how a user interacts with a device. By tracking mouse movements, clicks, and scrolling patterns, it builds a unique behavioral profile that reflects natural interaction style, making it difficult for unauthorized users to replicate. At the core of the system is a One-Class Support Vector Machine model suited for anomaly detection. It is trained only on legitimate user data to learn normal behavior patterns. During real-time usage, incoming mouse activity is continuously analyzed and compared with this profile. If deviations exceed a defined threshold, the behavior is classified as suspicious, enabling detection even after login and ensuring continuous authentication. When suspicious activity is identified, the system responds by capturing webcam images with timestamps and generating alerts. These records are displayed on a web dashboard, providing visual evidence and improving accountability and traceability. The framework uses a multi-component architecture integrating a Python backend, Linux service, and web interface. The backend manages data processing, feature extraction, and model execution, while the Linux service ensures uninterrupted background monitoring. The dashboard centralizes system status and intrusion events. An Android application extends remote access, allowing users to view system metrics and detected anomalies. It also enables remote actions such as locking, logging out, or shutting down the system. Overall, the system delivers adaptive, continuous, and user-friendly security. This approach strengthens protection against unauthorized access while maintaining simplicity and efficiency. It is suitable for personal computers, enterprise systems, and secure environments where continuous verification and rapid response are essential for modern cybersecurity needs and future authentication systems.},
keywords = {},
month = {April},
}
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