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@article{185562,
        author = {Daksh Srivastava and Atharv Mahesh Kulkarni and Omkar Sanjay Narkar},
        title = {Data Loss Prevention System for Securing Enterprise Networks},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {5},
        pages = {1845-1866},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=185562},
        abstract = {This research paper presents the design, implementation, and evaluation of an advanced Data Loss Prevention (DLP) system aimed at securing enterprise networks against data exfiltration and insider threats. Our system incorporates multiple layers of monitoring and control mechanisms including file encryption, real-time behavioral analysis, network traffic inspection, and external device monitoring. The proposed solution addresses critical gaps in contemporary DLP approaches by integrating traditional rule-based detection with more sophisticated behavioral analysis to mitigate evolving threats. Through extensive testing in simulated enterprise environments, we demonstrate the system's effectiveness in detecting and preventing unauthorized data access and exfiltration attempts with 94% accuracy while maintaining a false positive rate below 3%. This paper contributes to the field by providing a comprehensive framework for implementing robust DLP controls in modern enterprise settings where traditional perimeter security is increasingly insufficient.},
        keywords = {data loss prevention, cybersecurity, insider threats, network security, behavioral detection, file monitoring, encryption},
        month = {October},
        }