Privacy-Driven Webpage Fingerprinting Using Encrypted Traffic Packet Lengths

Sahlah Abd Ali and Ielaf Osamah Abdulmajeed

References:

1. M. Shen, Y. Liu, S. Chen, L. Zhu, and Y. Zhang, "Webpage Fingerprinting using Only Packet Length Information," in Proc. IEEE International Conference on Communications (ICC), Shanghai, China, May 2019, pp. 1-6, doi: 10.1109/ICC.2019.8761167.
2. G. Ansari, P. Rani, and V. Kumar, "A novel technique of mixed gas identification based on the group method of data handling (GMDH) on time-dependent MOX gas sensor data," in Proc. International Conference on Recent Trends in Computing (ICRTC), 2022, pp. 641-654.
3. D. Lazar, H. Chen, X. Wang, and N. Zeldovich, "Why does cryptographic software fail?: a case study and open problems," in Proc. 5th Asia-Pacific Workshop on Systems, Beijing, China, Jun. 2014, pp. 1-7, doi: 10.1145/2637166.2637237.
4. A. Yip, X. Wang, N. Zeldovich, and M. F. Kaashoek, "Improving application security with data flow assertions," in Proc. ACM SIGOPS 22nd Symposium on Operating Systems Principles, Big Sky, MT, USA, Oct. 2009, pp. 291-304, doi: 10.1145/1629575.1629604.
5. T. B. Lee, "NSA-Proof Encryption Exists. Why Doesn’t Anyone Use It?," Washington Post, p. 14, 2013.
6. D. Mayers, "Unconditional security in quantum cryptography," Journal of the ACM, vol. 48, no. 3, pp. 351-406, May 2001, doi: 10.1145/382780.382781.
7. A. Singh et al., "Blockchain-Based Lightweight Authentication Protocol for Next-Generation Trustworthy Internet of Vehicles Communication," IEEE Transactions on Consumer Electronics, vol. 70, no. 2, pp. 4898-4907, May 2024, doi: 10.1109/TCE.2024.3351221.
8. N. P. Smart and F. Vercauteren, "Fully Homomorphic Encryption with Relatively Small Key and Ciphertext Sizes," in Public Key Cryptography – PKC 2010, P. Q. Nguyen and D. Pointcheval, Eds., Lecture Notes in Computer Science, vol. 6056, Berlin, Germany: Springer, 2010, pp. 420-443, doi: 10.1007/978-3-642-13013-7_25.
9. C. Gentry, A. Sahai, and B. Waters, "Homomorphic Encryption from Learning with Errors: Conceptually-Simpler, Asymptotically-Faster, Attribute-Based," in Advances in Cryptology – CRYPTO 2013, R. Canetti and J. A. Garay, Eds., Lecture Notes in Computer Science, vol. 8042, Berlin, Germany: Springer, 2013, pp. 75-92, doi: 10.1007/978-3-642-40041-4_5.
10. M. Naehrig, K. Lauter, and V. Vaikuntanathan, "Can homomorphic encryption be practical?," in Proc. ACM Workshop on Cloud Computing Security, Chicago, IL, USA, Oct. 2011, pp. 113-124, doi: 10.1145/2046660.2046682.
11. L. Sweeney, "Weaving Technology and Policy Together to Maintain Confidentiality," Journal of Law, Medicine & Ethics, vol. 25, no. 2-3, pp. 98-110, 1997, doi: 10.1111/j.1748-720X.1997.tb01885.x.
12. A. Panchenko et al., "Website Fingerprinting at Internet Scale," in Proc. Network and Distributed System Security Symposium (NDSS), San Diego, CA, USA, 2016, doi: 10.14722/ndss.2016.23477.
13. P. Rani, K. Ur Rehman, S. P. Yadav, and L. Hussein, "Deep Learning and AI in Behavioral Analysis for Revolutionizing Mental Healthcare," in Demystifying the Role of Natural Language Processing (NLP) in Mental Health, A. Mishra et al., Eds., IGI Global, 2025, pp. 263-282, doi: 10.4018/979-8-3693-4203-9.ch014.
14. A. Panchenko, L. Niessen, A. Zinnen, and T. Engel, "Website fingerprinting in onion routing based anonymization networks," in Proc. ACM Workshop on Privacy in the Electronic Society, Chicago, IL, USA, Oct. 2011, pp. 103-114, doi: 10.1145/2046556.2046570.
15. M. S. Rahman, N. Matthews, and M. Wright, "Poster: Video Fingerprinting in Tor," in Proc. ACM SIGSAC Conference on Computer and Communications Security, London, UK, Nov. 2019, pp. 2629-2631, doi: 10.1145/3319535.3363273.
16. J. Lu et al., "GAP-WF: Graph Attention Pooling Network for Fine-grained SSL/TLS Website Fingerprinting," in Proc. International Joint Conference on Neural Networks (IJCNN), Shenzhen, China, Jul. 2021, pp. 1-8, doi: 10.1109/IJCNN52387.2021.9533543.
17. M. Shen et al., "Machine Learning-Powered Encrypted Network Traffic Analysis: A Comprehensive Survey," IEEE Communications Surveys & Tutorials, vol. 25, no. 1, pp. 791-824, 2023, doi: 10.1109/COMST.2022.3208196.
18. P. Rani and R. Sharma, "IMFOCA-IOV: Intelligent Moth Flame Optimization based Clustering Algorithm for Internet of Vehicle," in Proc. 14th International Conference on Computing Communication and Networking Technologies (ICCCNT), 2023, pp. 1-6.
19. P. Rani, P. N. Singh, S. Verma, N. Ali, P. K. Shukla, and M. Alhassan, "An implementation of modified blowfish technique with honey bee behavior optimization for load balancing in cloud system environment," Wireless Communications and Mobile Computing, vol. 2022, pp. 1-14, 2022.
20. V. Rimmer, D. Preuveneers, M. Juarez, T. V. Goethem, and W. Joosen, "Automated Website Fingerprinting through Deep Learning," in Proc. Network and Distributed System Security Symposium (NDSS), San Diego, CA, USA, 2018, doi: 10.14722/ndss.2018.23105.
21. L. Swarup, "Encrypted Traffic Analysis for Malware Detection Using Deep Learning," in Proc. IEEE International Conference on ICT in Business Industry & Government (ICTBIG), Indore, India, Dec. 2023, pp. 1-7, doi: 10.1109/ICTBIG59752.2023.10456001.
22. X. Tan et al., "Inter-Flow Spatio-Temporal Correlation Analysis Based Website Fingerprinting Using Graph Neural Network," IEEE Transactions on Information Forensics and Security, vol. 19, pp. 7619-7632, 2024, doi: 10.1109/TIFS.2024.3441935.
23. I.-S. Jung et al., "Enhanced Encrypted Traffic Analysis Leveraging Graph Neural Networks and Optimized Feature Dimensionality Reduction," Symmetry, vol. 16, no. 6, p. 733, Jun. 2024, doi: 10.3390/sym16060733.
24. H. Kong et al., "A Novel Method with Transformers for Fine-grained Encrypted Traffic Classification," in Proc. IEEE International Conference on High Performance Computing & Communications, Data Science & Systems, Smart City & Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys), Melbourne, Australia, Dec. 2023, pp. 74-81, doi: 10.1109/HPCC-DSS-SmartCity-DependSys60770.2023.00020.
25. N. K. Agrawal et al., "TFL-IHOA: Three-Layer Federated Learning-Based Intelligent Hybrid Optimization Algorithm for Internet of Vehicle," IEEE Transactions on Consumer Electronics, vol. 70, no. 3, pp. 5818-5828, Aug. 2024, doi: 10.1109/TCE.2023.3344129.
26. M. Shen, Y. Liu, L. Zhu, X. Du, and J. Hu, "Fine-Grained Webpage Fingerprinting Using Only Packet Length Information of Encrypted Traffic," IEEE Transactions on Information Forensics and Security, vol. 16, pp. 2046-2059, 2021, doi: 10.1109/TIFS.2020.3046876.
27. P. Rani, U. C. Garjola, and H. Abbas, "A Predictive IoT and Cloud Framework for Smart Healthcare Monitoring Using Integrated Deep Learning Model," NJF Intelligent Engineering Journal, vol. 1, no. 1, pp. 53-65, 2024.
28. D. Wagner and B. Schneier, "Analysis of the SSL 3.0 protocol," in Proc. 2nd USENIX Workshop on Electronic Commerce, 1996, pp. 29-40, [Online]. Available: https://www.usenix.org/publications/library/proceedings/ec96/full_papers/wagner/wagner.pdf
29. H. Cheng and R. Avnur, "Traffic analysis of SSL encrypted web browsing," Project Paper, University of California, Berkeley, 1998, [Online]. Available: https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=1a987c4fe65fa347a863dece665955ee7e01791b
30. A. Hintz, "Fingerprinting Websites Using Traffic Analysis," in Privacy Enhancing Technologies, R. Dingledine and P. Syverson, Eds., Lecture Notes in Computer Science, vol. 2482, Berlin, Germany: Springer, 2003, pp. 171-178, doi: 10.1007/3-540-36467-6_13.
31. Q. Sun, D. R. Simon, Y.-M. Wang, W. Russell, V. N. Padmanabhan, and L. Qiu, "Statistical identification of encrypted web browsing traffic," in Proc. IEEE Symposium on Security and Privacy, 2002, pp. 19-30, [Online]. Available: https://ieeexplore.ieee.org/abstract/document/1004359/