A CRYPTOGRAPHY-ENHANCED DATA LOSS PREVENTION SYSTEM FOR OUTBOUND DATA PROTECTION IN CRITICAL INFRASTRUCTURE
Authors: Seitkali Gaziz, Berdibayev Rat, Tynymbayev Sakhybay, Gnatyuk Sergiy
Affiliation: Al-Farabi Kazakh National University, Almaty University of Power Engineering and Telecommunications named after Gumarbek Daukeev, International Information Technology University, Kyiv Aviation Institute
Category:
Keywords: Data Loss Prevention (DLP), Outbound Traffic Security, Searchable Symmetric Encryption (SSE), Encrypted Traffic Inspection, Document Fingerprinting, Privacy-Preserving Networks
ABSTRACT. Modern Data Loss Prevention (DLP) systems face a significant challenge: balancing data privacy with inspection capabilities. As outbound traffic increasingly utilizes end-to-end encryption, traditional deep packet inspection (DPI) often requires intrusive decryption, which creates security vulnerabilities. This paper proposes a cryptography-enhanced DLP framework designed to monitor outbound traffic without compromising data integrity. By leveraging Searchable Symmetric Encryption (SSE) and Robust Hashing, the system identifies sensitive data patterns within encrypted streams. Experimental results demonstrate that our approach maintains high detection precision while reducing the computational overhead typically associated with full traffic decryption.
References:
L. Zhang, M. Wang, and J. Liu, "Challenges and Countermeasures in Modern Data Loss Prevention: A Survey on Encrypted Traffic Inspection," IEEE Communications Surveys & Tutorials, vol. 25, no. 3, pp. 1540-1568, 2023.
A. Rahaman, T. Holz, and K. Lee, "Privacy-Preserving Deep Packet Inspection over Encrypted Traffic: A Comprehensive Review," IEEE Transactions on Information Forensics and Security, vol. 19, pp. 210-225, 2024.
J. Smith, E. Carter, and R. Chen, "The Privacy Paradox: Mitigating Man-in-the-Middle Vulnerabilities in Corporate Security Gateways," in Proceedings of the IEEE International Conference on Network Protocols (ICNP), 2024, pp. 112-125.
S. Kamara and C. Papamanthou, "Efficient Searchable Symmetric Encryption for High-Speed Network Applications," ACM Transactions on Privacy and Security, vol. 26, no. 1, pp. 1-32, 2023.
M. Al-Fares, D. Anderson, and H. Kim, "Robust Document Fingerprinting using Content-Defined Chunking for Data Exfiltration Prevention," Journal of Network and Computer Applications, vol. 215, 103645, 2024.
K. Zheng, Y. Wu, and X. Lin, "A Lightweight Cryptographic Framework for Outbound Traffic Monitoring in Zero-Trust Architectures," IEEE Internet of Things Journal, vol. 12, no. 5, pp. 4120-4135, 2025.
T. Miller and P. Desai, "Dynamic Risk Assessment Models for Insider Threat Detection in Enterprise Networks," in Proceedings of the 2025 IEEE Symposium on Security and Privacy (SP), 2025, pp. 450-466.
D. Boneh and V. Shoup, A Graduate Course in Applied Cryptography. Stanford University, 2023. [Online]. Available: http://toc.cryptobook.us/
R. Ivanov and S. Patel, "Evaluating the Performance of Searchable Encryption Protocols in Real-Time 1Gbps Network Environments," IEEE Networking Letters, vol. 8, no. 2, pp. 77-81, 2026.
O. Garcia, "Addressing the Blind Spots of TLS 1.3 in Corporate Data Loss Prevention Systems," Computers & Security, vol. 138, 103600, 2024.
Menu