International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Intelligent Behavioral Cyber Lock – Securing Apps through user Behavior |
|---|---|
| ABSTRACT | Behavioral biometrics offers a compelling solution for strengthening authentication on personal devices by continuously verifying user identity during active sessions. Existing security mechanisms, such as passwords, personal identification numbers (PINs), and single-use biometric checks, perform authentication only at the moment of access, thereby creating a security gap once the device is unlocked. To address this limitation, this study presents an intelligent cyber-lock system that continuously analyzes user behavior using multiple interaction-based traits, including typing patterns, touch interaction behavior, and motion sensor data. The proposed system employs a lightweight machine-learning model that operates entirely on the device, enabling real-time authentication while preserving user privacy by avoiding the transmission or storage of raw behavioral data on external servers. A dynamic risk assessment module evaluates ongoing interactions and categorizes them into different trust levels, enabling appropriate responses such as alerts, restricted access, or additional verification when abnormal behavior is detected. Experimental evaluation demonstrates that the system achieves high authentication accuracy with low false acceptance and false rejection rates, while maintaining minimal computational and energy overhead. These results confirm that continuous behavioral authentication can significantly enhance device security without compromising usability or user experience. |
| AUTHOR | SNEHA Y M, RAKSHITA MATHAD, PAVITHRA M K, RANJITA F SANNAGOUDRA, SAHANA K A Department of Information Science and Engineering, Jain Institute of Technology, (VTU), Davangere, Karnataka, India |
| VOLUME | 180 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1401018 |
| pdf/18_Intelligent Behavioral Cyber Lock – Securing Apps through user Behavior.pdf | |
| KEYWORDS | |
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