مدل ترکیبی تشخیص ناهنجاری با استفاده از خوشه بندی وزنی معکوس و یادگیری ماشین در بستر محیط‌های ابری

[1]            H. F. Atlam, A. Alenezi, R. J. Walters, G. B. Wills, and J. Daniel, "Developing an adaptive Risk-based access control model for the Internet of Things," in 2017 IEEE international conference on internet of things (iThings) and IEEE green computing and communications (GreenCom) and IEEE cyber, physical and social computing (CPSCom) and ieee smart data (SmartData), 2017: IEEE, pp. 655-661. 

[2]     S. Iqbal et al., "On cloud security attacks: A taxonomy and intrusion detection and prevention as a service," Journal of Network and Computer Applications, vol. 74, pp. 98-120, 2016.

[3]     G. Somani, M. S. Gaur, D. Sanghi, M. Conti, and R. Buyya, "DDoS attacks in cloud computing: Issues, taxonomy, and future directions," Computer Communications, vol. 107, pp. 30-48, 2017.

[4]     G. Somani, M. S. Gaur, D. Sanghi, M. Conti, M. Rajarajan, and R. Buyya, "Combating DDoS attacks in the cloud: requirements, trends", and future directions  IEEE Cloud Computing, vol. 4, no. 1, pp. 22-32, 2017. 

[5]     M. A. Lawal, R. A. Shaikh, and S. R. Hassan, "An anomaly mitigation framework for iot using fog computing," Electronics, vol. 9, no. 10, p. 1565, 2020.

[6]     S. Na, L. Xumin, and G. Yong, "Research on k-means clustering algorithm: An improved k-means clustering algorithm," in 2010 Third International Symposium on intelligent information technology and security informatics, 2010: Ieee, pp. 63-67. 

[7]     Barbakh, W., & Fyfe, C. (2007). Inverse weighted clustering algorithm. Computing and Information Systems, 11(2).

[8]     H. Neuschmied, M. Winter, K. Hofer-Schmitz, B. Stojanovic, and U. Kleb, "Two Stage Anomaly Detection for Network Intrusion Detection," in ICISSP, 2021, pp. 450-457. 

[9]     S. Weisong, Z. Xingzhou, W. Yifan, and Z. Qingyang, "Edge computing: State-of-the-art and future directions," Journal of Computer Research and Development, vol. 56, no. 1, p. 69, 2019.

[10]         F. M. Ramos, D. Kreutz, and P. Verissimo, "Software-defined networks: On the road to the softwarization of networking," Cutter IT journal, 2015.

[11]   M. Mirzaei, A. Mehabadi,” Hybrid Anomaly Detection Method Using Community Detection in Graph and Feature Selection,” Journal of  Electronical & Cyber Defence Vol. 8, No. 1, 2020. (in persion)

[12]   K. Shoushian , A. J. Rashidi, M. Dehghani,” Modeling of Cyber-Attacks Obfuscation, Based on   Alteration Technique of Attack,” Journal of  Electronical & Cyber Defence Vol. 8, No. 1, 2020. (in persion)

[13]  V. Yadegari, A. Matinfar, “Detect Web Denial of Service Attacks Using Entropy and Support Vector Machine Algorithm,” Journal of Electronical & Cyber Defence Vol. 6, No. 4, 2019. (in persion)

[14]  C. Modi, D. Patel, B. Borisanya, A. Patel, M. Rajarajan, A novel framework for intrusion detection in cloud, in: Proceedings of the Fifth International Conference on Security of Information and Networks, ACM, pp. 67–74, 2012.

[15]  S. Teng, C. Zheng, H. Zhu, D. Liu, and W. Zhang, “A cooperative intrusion detection model for cloud computing networks,” International Journal of Security and its applications, vol. 8, no. 3, 
pp. 107–118, 2014.

[16]  S. Weisong, Z. Xingzhou, W. Yifan, and Z. Qingyang, "Edge computing: State-of-the-art and future directions," Journal of Computer Research and Development, vol. 56, no. 1, p. 69, 2019.

[17]  M. Idhammad, K. Afdel, M. Belouch, “Dos detection method based on artificial neural networks,” International Journal of Advanced Computer Science and Applications (ijacsa), vol 10, pp 14569, 2017.

[18]  L. Liu and Y. Zhai, "A Survey on MapReduce Scheduling in Cloud Computing,"  Fifth International Conference on Instrumentation and Measurement, Computer, Communication and Control,  pp. 1710-1715, 2015.

[19]  M. M. Rashid, J. Kamruzzaman, M. M. Hassan, T. Imam, and S. Gordon, "Cyberattacks Detection in IoT-Based Smart City Applications Using Machine Learning Techniques," International Journal of Environmental Research and Public Health, vol. 17, no. 24, p. 9347, 2020.

[20]  M. Idhammad, K. Afdel, M. Belouch, Distributed Intrusion Detection System for Cloud Environments based on Data Mining techniques, Procedia Computer Science, Vol 127,pp35-41, 2018.

[21]  R. Beghdad, “Efficient deterministic method for detecting new U2R attacks,” Computer Communications, Vol 32, pp1104-1110, 2009.

[22]  E .Kim, and S. Kim, “A Novel Anomaly Detection System Based on HFR-MLR Method”, in Mobile, Ubiquitous, and Intelligent Computing, p p. 279-286, 2014.

[23]  C.A. Charu, and K.R. Chandan, “Data clustering: algorithms and applications,” In: Chapman and Hall/CRC Boston, MA. 2013.

[24]  H. Pajouh, G. Dastghaibyfard, and S. Hashemi,” Two-tier network anomaly detection model,” a machine learning approach. Journal of Intelligent Information Systems, Vol 48, pp. 61-74, 2017.

[25]  S. Mishra and A. Tripathi, "IoT platform business model for innovative management systems," International Journal of Financial Engineering, vol. 7, no. 03, p. 2050030, 2020.