تشخیص ناهنجاری در ترافیک شبکه با استفاده از سامانه توزیع‌شده‌ مبتنی بر سیستم‌های چندعامله‌ خودسازمانده

[1] Fernandes, J.J. Rodrigues, L.F. Carvalho, J.F. Al-Muhtadi and M.L. Proença, “A comprehensive survey on network anomaly detection”, Telecommunication Systems, vol. 70, no. 3, pp. 447-489, 2019.

[2] Nisioti, A. Mylonas, P.D. Yoo and V. Katos, “From intrusion detection to attacker attribution: A comprehensive survey of unsupervised methods”, IEEE Communications Surveys & Tutorials, vol. 20, no. 4, pp. 3369-3388, 2018.

[3] H. Bhuyan, D.K. Bhattacharyya and J.K. Kalita, “Network anomaly detection: methods, systems and tools”, IEEE communications surveys & tutorials, vol. 16, no. 1, pp. 303-336, 2013.

[4] Kendrick, N. Criado, A. Hussain and M. Randles, “A self-organising multi-agent system for decentralised forensic investigations”, Expert Systems with Applications, vol. 102, pp. 12-26, 2018.

[5] Rothamsted, T. Lewis and V. Barnett, Outliers in statistical data, John Wiley & Sons, 1996.

[6] Hoque, M.H. Bhuyan, R.C. Baishya, D.K. Bhattacharyya and J.K. Kalita, “Network attacks: Taxonomy, tools and systems”, Journal of Network and Computer Applications,vol. 40, pp. 307-324, 2014.

[7] 2020 Cyber Security Statistics The Ultimate List Of Stats, Data & Trends, June 2020, https://purplesec.us/resources/cyber-security-statistics.

[8] Wooldridge, an Introduction to MultiAgent Systems. Second ed., John wiley & sons, 2009.

[9] Shakarian, G.I. Simari, G. Moores and S. Parsons, “Cyber attribution: An argumentation-based approach”, Cyber Warfare, Springer, pp. 151-171, 2015.

D. McKinnon, S.R. Thompson, R.A. Doroshchuk, G.A. Fink and E.W. Fulp, “Bio-inspired cyber security for smart grid deployments”, IEEE PES Innovative Smart Grid Technologies Conference (ISGT), pp. 1-6, 2013.

Jahanbin, A. Ghafarian, S.A. Hosseini Seno and S. Nikookar, “A computer forensics approach based on autonomous intelligent multi-agent system”, International Journal of Database Theory and Application, vol. 6, no.5, pp. 1-12, 2013.

Shanmugasundaram, N. Memon, A. Savant and H. Bronnimann, “ForNet: A distributed forensics network” International Workshop on Mathematical Methods, Models, and Architectures for Computer Network Security, Springer, 2003.

A. Baig, “Multi-agent systems for protecting critical infrastructures: A survey”, Journal of Network and Computer Applications, vol. 35, no. 3, pp. 1151-1161, 2012.

Kesavamoorthy and K.R. Soundar, “Swarm intelligence based autonomous DDoS attack detection and defense using multi agent system”, Cluster Computing, vol. 22, no. 4, pp. 9469-9476, 2019.

Mees, “Multi-agent anomaly-based APT detection”, Proceedings of Information Systems Technology Panel Symposium, 2012.

آمره­ای، بیگی، «یک سیستم تشخیص نفوذ چندلایه با رویکرد ترکیبی»، پانزدهمین کنفرانس بین‌المللی انجمن رمز ایران، تهران، انجمن رمز ایران, 1397.

Distributed Self-organizing Multi-agent System, July 2020, https://gitlab.com/N_shakiba/dsms/

NSL-KDD dataset, June 2020, https://www.unb.ca/cic/datasets/nsl.html.

Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann and I.H. Witten, “The WEKA data mining software: an update”, ACM SIGKDD explorations newsletter, vol. 11, no. 1, pp. 10-18, 2009.

Yin, Y. Zhu, J. Fei and X. He, “A deep learning approach for intrusion detection using recurrent neural networks” IEEE Access, vol. 5, pp. 21954-21961, 2017.

A.R. Ashfaq, X.Z. Wang, J.Z. Huang, H. Abbas and Y.L. He, “Fuzziness based semi-supervised learning approach for intrusion detection system”, Information Sciences, vol. 378, pp. 484-497, 2017.

Su, H. Sun, J. Zhu, S. Wang and Y. Li, “BAT: Deep learning methods on network intrusion detection using NSL-KDD dataset”. IEEE Access,vol. 8, pp. 29575-29585, 2020

Gao, Y. Liu, Y. Jin, J. Chen, and H. Wu, “A novel semi-supervised learning approach for network intrusion detection on cloud-based robotic system”, IEEE Access, vol. 6, pp. 50927-50938, 2018.

Naseer, Y. Saleem, S. Khalid, M.K. Bashir, J. Han, M.M. Iqbal and K. Han, “Enhanced network anomaly detection based on deep neural networks”. IEEE Access. Vol 6, pp. 48231- 48246, 2018.

A. Tama, M. Comuzzi and K.H. Rhee, “TSE-IDS: A two-stage classifier ensemble for intelligent anomaly-based intrusion detection system”. IEEE Access, vol. 7, pp. 94497-507, 2019.

Illy, G. Kaddoum, C.M. Moreira, K. Kaur and S. Garg, “Securing fog-to-things environment using intrusion detection system based on ensemble learning”. IEEE Wireless Communications and Networking Conference (WCNC), pp. 1-7, 2019.

Alsubhi, N. Bouabdallah and R. Boutaba, “Performance analysis in intrusion detection and prevention systems”, IFIP/IEEE International Symposium on Integrated Network Management (IM 2011) and Workshops, 2011.