Current - Issue

1. M. Such, A. Orozco, and J. Standard, "A layered decomposition methodology for HTTP-over-TLS transactions in post-quantum
architectures," arXiv preprint arXiv:2603.11006, 2026.
2. D. Varcasia and M. Amoretti, "Automated configuration profiling and hybrid PQC deployment in enterprise infrastructure," CEUR
Workshop Proceedings / arXiv:2605.17955, 2026.
3. National Institute of Standards and Technology (NIST), "FIPS 203: Module-Lattice-Based Key-Encapsulation Mechanism Standard,"
U.S. Department of Commerce, 2024.
4. National Institute of Standards and Technology (NIST), "FIPS 204: Module-Lattice-Based Digital Signature Standard," U.S. Department
of Commerce, 2024.
5. N. Bindel, J. Brendel, M. Fischlin, F. Günther, and D. Stebila, "Hybrid key encapsulation mechanisms and transport layer security,"
International Journal of Information Security, vol. 18, no. 6, pp. 759–787, 2019.
6. S. Panja, S. Sharifian, S. Jiang, and R. Safavi-Naini, "CCA-secure hybrid encryption in correlated randomness model and KEM
combiners," arXiv preprint arXiv:2401.00983, 2024.
7. P. W. Shor, "Algorithms for quantum computation: Discrete logarithms and factoring," in Proceedings of the 35th Annual Symposium
on Foundations of Computer Science, 1994, pp. 124–134.
8. L. K. Grover, "A fast quantum mechanical algorithm for database search," in Proceedings of the 28th Annual ACM Symposium on Theory
of Computing, 1996, pp. 212–219.
9. J. Hekkala, K. Halunen, and V. Vallivaara, "Implementing post-quantum cryptography for developers: Usability and performance
challenges," in Proceedings of the 8th International Conference on Information Systems Security and Privacy, 2022, pp. 73–83.
10. P. Kampanakis, P. Panburana, M. Curcio, and C. Fernandes, "Performance of hybrid post-quantum TLS handshakes," Computer
Standards & Interfaces, vol. 76, p. 103503, 2021.
11. D. Sikeridis, P. Kampanakis, and M. Devetsikiotis, "Benchmarking post-quantum cryptography in TLS," IEEE Transactions on
Dependable and Secure Computing, vol. 17, no. 6, pp. 1311–1324, 2020.
12. A. Shaw, "Bridging the post-quantum production gap with hybrid-by-default cryptography libraries," arXiv preprint arXiv:2605.17061,
2026.
13. T. Carrier, P. Victor, A. Tekeoglu, and A. H. Lashkari, "Malware memory analysis (CIC-MalMem-2022 dataset)," Canadian Institute
for Cybersecurity (CIC), 2022.
14. M. Abualhaj and M. Al-Khatib, "Evaluating machine learning and decision tree classifiers on the CIC-MalMem-2022 dataset," Journal
of Computer Security and Forensics, 2024.
15. Y. Chen, X. Zhao, and H. Wang, "Scalable memory forensics: Fast detection of obfuscated malware using histogram-based gradient
boosting," IEEE Transactions on Dependable and Secure Computing, 2025.
16. A. Gupta, Y. Zhang, and F. Martinez, "Interpretable machine learning in memory forensics: Applying SHAP and tree-based ensembles
for malware attribution," Computers & Security, 2025.
17. M. Jumaah, A. A. Yassin, Z. A. Abduljabbar, and M. Jawad, "Amalgamating ensemble machine learning soft voting classifier for
malware detection," Engineering, Technology & Applied Science Research (ETASR), 2025.
18. M. Toğaçar, "A novel approach to malware detection: Converting hardware memory data to 2D barcodes using mobile networks,"
Journal of Network and Systems Management, 2026.19. M. Ring, S. Wunderlich, D. Scheuring, D. Landes, and A. Hotho, "A survey of network-based intrusion detection systems using machine
learning," ACM Computing Surveys (CSUR), vol. 52, no. 6, pp. 1–39, 2019.
20. A. Anderson, S. Schrittwieser, and J. Morales, "Detecting command and control channels in encrypted network traffic," IEEE
Transactions on Information Forensics and Security, vol. 14, no. 6, pp. 1452–1465, 2019.
21. T. Van Ede et al., "Flowprint: Semi-supervised mobile-app fingerprinting on encrypted network traffic," in 29th USENIX Security
Symposium, 2020, pp. 915–932.
22. M. Woodbridge, H. S. Anderson, A. Ahuja, and D. Grant, "Predicting domain generation algorithms with long short-term memory
networks," arXiv preprint arXiv:1611.00791, 2016.
23. J. Sterling and K. Sundaram, "Encrypted traffic classification using deep learning: A comparative survey," Computers & Security, vol.
112, p. 102512, 2022.
24. Q. Liu, Y. Li, and Z. Qu, "TADDAG: Translating and detecting domain generation algorithms via attention mechanisms," Computers &
Security, vol. 120, p. 102810, 2022.