Machine Learning and APTs

References

[1]A. Alshamrani, S. Myneni, A. Chowdhary, and D. Huang, “A survey on Advanced persistent threats: Techniques, solutions, challenges, and research opportunities,” IEEE Communications Surveys & Tutorials, vol. 21, no. 2, pp. 1851–1877, Jan. 2019.[2]R. S. Ross, “Managing information security risk: Organization, mission, and information system view,” Special Publication (NIST SP)- 800-39, 2011.[3]P. Chen, L. Desmet, and C. Huygens, “A study on advanced persistent threats,” in IFIP International Conference on Communications and Multimedia Security. Springer, 2014, pp. 63–72.[4] E. M. Hutchins, M. J. Cloppert, R. M. Amin, and others, “Intelligence-driven computer network defense informed by analysis of adversary campaigns and intrusion kill chains,” Leading Issues in Information Warfare & Security Research, vol. 1, no. 1, p. 80, 2011.[5] A. K. Sood and R. J. Enbody, “Targeted cyberattacks: a superset of advanced persistent threats,” IEEE security & privacy, vol. 11, no. 1, pp. 54–61, 2013.[6] O. S. V. D. (OSVDB), “Open source vulnerability database (osvdb),” 2012.[7] P. Mell, K. Scarfone, and S. Romanosky, “Common vulnerability scoring system,” IEEE Security & Privacy, vol. 4, no. 6, 2006.[8] M. Motoyama, D. McCoy, K. Levchenko, S. Savage, and G. M. Voelker, “An analysis of underground forums,” in Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference. ACM, 2011, pp. 71–80.[9] M. Ussath, D. Jaeger, F. Cheng, and C. Meinel, “Advanced persistent threats: Behind the scenes,” in Information Science and Systems (CISS), 2016 Annual Conference on. IEEE, 2016, pp. 181–186.[10]A. TrendLabsSM, “Spear-Phishing Email: Most Favored APT Attack Bait”, 2012.[11]G. O’Gorman and G. McDonald, “The elderwood project”. Symantec Corporation, 2012.[12]W. Gragido, “Lions at the watering hole: The voho affair,” RSA blog, vol. 20, 2012.[13]D. Kindlund, D. Caselden, X. Chen, N. Moran, and M. Scott, “Operation SnowMan: DeputyDog Actor Compromises US Veterans of Foreign Wars Website,” FireEye, 13-Feb-2014. [Online]. Available: https://www.fireeye.com/blog/threat-research/2014/02/operation-snowman-deputydog-actor-compromises-us-veterans-of-foreign-wars-website.html. [Accessed: 13-Jul-2022].[14]S. McClure et al., “Protecting your critical assets-lessons learned from operation aurora,” Tech. Rep., 2010.[15]RSA FraudAction Research Labs, “The anatomy of the RSA attack,” RSA blog, 01-Apr-2011. [Online]. Available: http://blogs.rsa.com/anatomy-of-an-attack/. [Accessed: 13-Jul-2022].[16]X. Wang, K. Zheng, X. Niu, B. Wu, and C. Wu, “Detection of command and control in advanced persistent threat based on independent access,” in Communications (ICC), 2016 IEEE International Conference on. IEEE, 2016, pp. 1–6.[17]B. Harris, “Shadows in the cloud: An investigation of cyber espionage 2.0,” GovTech, 02-Aug-2010. [Online]. Available: https://www.govtech.com/dc/articles/shadows-in-the-cloud-an-investigation.html. [Accessed: 13-Jul-2022].[18]M. Z. Rafique, P. Chen, C. Huygens, and W. Joosen, “Evolutionary algorithms for classification of malware families through different network behaviors,” in Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation, 2014, pp. 1167–1174.[19]E. Rajalakshmi, N. Asik Ibrahim, and V. Subramaniyaswamy, “A survey of machine learning techniques used to combat against the advanced persistent threat,” Applications and Techniques in Information Security, pp. 159–172, Nov. 2019.[20]I. Ghafir, M. Hammoudeh, V. Prenosil, L. Han, R. Hegarty, K. Rabie, and F. J. Aparicio-Navarro, “Detection of advanced persistent threat using machine-learning correlation analysis,” Future Generation Computer Systems, vol. 89, pp. 349–359, Jul. 2018.[21]H. HaddadPajouh, A. Dehghantanha, R. Khayami, and K.-K. R. Choo, “A deep recurrent neural network based approach for internet of things malware threat hunting,” Future Generation Computer Systems, vol. 85, pp. 88–96, Mar. 2018.[22]F. J. Aparicio-Navarro, K. G. Kyriakopoulos, Y. Gong, D. J. Parish, and J. A. Chambers, “Using Pattern-of-Life as Contextual Information for Anomaly-Based Intrusion Detection Systems,” IEEE Access, vol. 5, pp. 22177–22193, 2017, doi: 10.1109/ACCESS.2017.2762162.[23]S.-T. Liu, Y.-M. Chen, and S.-J. Lin, “A novel search engine to uncover potential victims for apt investigations,” in IFIP International Conference on Network and Parallel Computing, 2013, pp. 405–416.[24]G. E. Hinton, “Deep belief networks,” Scholarpedia, vol. 4, no. 5, p. 5947, 2009.[25]M. Moradi and M. Zulkernine, “A neural network based system for intrusion detection and classification of attacks,” in Proceedings of the IEEE international conference on advances in intelligent systems-theory and applications, 2004, pp. 15–18.[26]M. Balduzzi, V. Ciangaglini, and R. McArdle, “Targeted attacks detection with spunge,” in 2013 Eleventh Annual Conference on Privacy, Security and Trust, 2013, pp. 185–194.[27]A. Azmoodeh, A. Dehghantanha, and K.-K. R. Choo, “Robust malware detection for internet of (battlefield) things devices using deep eigenspace learning,” IEEE transactions on sustainable computing, vol. 4, no. 1, pp. 88–95, 2018.