Artificial Intelligence and Data Mining Approaches in Security Frameworks. Группа авторов

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СКАЧАТЬ “The Round Complexity of Secure Protocols,” Proceedings of the 22nd Annual ACM Symposium on Theory of Computing, pp. 503–513.

      Bhargava, N., Dayma, S., Kumar, A. & Singh, P. (2017) “An approach for classification using simple CART algorithm in WEKA,” 11th International Conference on Intelligent Systems and Control (ISCO), pp. 212–216.

      Patel, D., K., B., & Bhatt, S. H. (2014) “Implementnig Data Mining for Detection of Malware from Code,” International Journal of Advanced Computer Technology: Compusoft, vol. 3(4), pp. 732–740.

      Stanley, D. M. (2013) “CERIAS Tech Report 2013-19 Improved Kernel Security through Code Validation, Diversification, and Minimization,” Ph.D. Thesis.

      Yeung D. Y. & Ding, Y. (2003) “Host-Based Intrusion Detection Using Dynamic and Static Behavioral Models,” Pattern Recognition, vol. 36(1), pp. 229–243.

      Bloedorn, E., Christiansen, A. D., Hill, W., Skorupka, C., Talbot, L.M. & Tivel, J. (2001) “Data Mining for Network Intrusion Detection: How to Get Started,” MITRE, pp. 1–9.

      Barrantes, E.G., Ackley, D. H., Palmer, T.S., Stefanovic, D. & Zovi, D.D. (2003) “Randomized Instruction Set Emulation to Disrupt Binary Code Injection Attacks,” Proceedings of the 10th ACM Conference on Computer and Communications Security, pp. 281–289.

      Reddy, G., Iaeng, M., Reddy, V. & Rajulu (2011) “A Study of Intrusion Detection in Data Mining” World Congress on Engineering (WCE), pp. 6–8.

      Lee, W., Stolfo, S.J. & Mok, K.W. (1999) “A Data Mining Framework for Building Intrusion Detection Models,” Proceedings of the IEEE Symposium on Security and Privacy, pp. 120–132.

      Jacobson, E. R., Bernat, A.R., Williams, W.R. & Miller, B.P. (2014) “Detecting Code Reuse Attacks with a Model of Conformant Program Execution,” International Symposium on Engineering Secure Software and Systems, pp. 1–18.

      Giannotti, F., Lakshmanan, L.V., Monreale, A., Pedreschi, D. & Wang, H. (2013) “Privacy-Preserving Mining of Association Rules from Outsourced Transaction Databases,” IEEE Systems Journal, vol. 7(3), pp. 385–395.

      Thabtah, F., Cowling, P., & Peng, Y. (2005) “MCAR: Multiclass Classification based on Association Rule,” 3rd ACS/IEEE International Conference on Computer Systems and Applications, pp. 33–39.

      Habibi, J., Panicker, A., Gupta, A. & Bertino, E. (2015) “DISARM: Mitigating Buffer Overflow Attacks on Embedded Devices,” International Conference on Network and System Security, pp. 112–129.

      Zhan, J., Matwin, S. & Chang L (2005), “Privacy Preserving Collaborative Association Rule Mining,” IFIP Annual Conference on Data and Applications Security and Privacy, pp. 153–165.

      Desale, K.S. & Ade, R. (2015) “Genetic Algorithm Based Feature Selection Approach for Effective Intrusion Detection System,” International Conference on Computer Communication and Informatics (ICCCI), pp. 1–6.

      Polychronakis, M. (2009) “Generic Detection of Code Injection Attacks using Network-Level Emulation,” Ph.D. Thesis.

      Diwate, & Sahu, A., (2014) “Efficient Data Mining in SAMS through Association Rule,” International Journal of Electronics Communication and Computer Engineering, vol. 5(3), pp. 593–597.

      Mitchell R. & Chen, R. (2013) “Effect of Intrusion Detection and Response on Reliability of Cyber Physical Systems,” IEEE Transactions on Reliability, vol. 62(1), pp. 199–210.

      Bhatkar, S., DuVarney, D. C. & Sekar, R. (2005) “Efficient Techniques for Comprehensive Protection from Memory Error Exploits” Proceedings of the 14th USENIX Security Symposium.

      1 *Corresponding author: [email protected]

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