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Cloud-Based Cyber Incidents Response System and Software Tools

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Information and Software Technologies (ICIST 2021)

Abstract

Cloud technologies and their applications are implementing in various ICT infrastructures. Today cyber threats mitigation in clouds is hot topic and it has scientific interest. Authors analyzed cyber threats detection methods and defined their disadvantages. Next, model of cloud service was proposed and it allows to ensure the cyber security of cloud services. An improved method for cyber threats detection has been developed, it allows to detect cyber threats in cloud services and classify them. The developed method was experimentally investigated using the NSL-KDD database as well as simulation tools RStudio and CloudSim. It was proved the correctness of its work and the possibility of application in cloud services as well as increase efficiency of cloud system security. Cyber Incidents Response System has been developed that can be used to build cloud services based on the various cloud computing architecture. It is significant because it can be the autonomous functional unit of cyber incident response system or other instrumental cybersecurity tools.

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References

  1. Abidar, R., Moummadi, K., Moutaouakkil, F., Medromi, H.: Intelligent and pervasive supervising platform for information system security based on multi-agent systems. Int. Rev. Comput. Softw. 10(1), 44–51 (2015)

    Google Scholar 

  2. Ivanov, A.: Security as main pain of the cloud computing, Online access mode. http://www.cnews.ru/reviews/free/saas/articles/articles12.shtml

  3. Active security for advanced threats counteraction, Online access mode. http://www.itsec.ru/articles2/target/aktivnaya-zaschita-kak-metod-protivodeystviya-prodvinutym-kiberugrozam

  4. The 6 Major Cyber Security Risks to Cloud Computing, Online access mode. http://www.adotas.com/2017/08/the-6-major-cyber-security-risks-to-cloud-computing/

  5. Google Security Whitepaper for Google Cloud Platform, Online access mode. https://habrahabr.ru/post/183168/

  6. Dokas, P., Ertoz, L., Kumar, V.: Data mining for network intrusion detection. Recent Adv. Intrusion Detect. 15(78), 21–30 (2014)

    Google Scholar 

  7. Ahmed, P.: An intrusion detection and prevention system in cloud computing: a systematic review. J. Netw. Comput. Appl. 11, 1–18 (2016)

    MathSciNet  Google Scholar 

  8. Iavich, M., Gnatyuk, S., Odarchenko, R., Bocu, R., Simonov, S.: The novel system of attacks detection in 5G. In: Barolli, L., Woungang, I., Enokido, T. (eds.) AINA 2021. LNNS, vol. 226, pp. 580–591. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-75075-6_47

    Chapter  Google Scholar 

  9. Carl, G., Kesidis, G., Brooks, R.R., Rai, S.: Denial-of-service attack-detection techniques. Internet Comput. IEEE 10, 82–89 (2006)

    Article  Google Scholar 

  10. Hu, Z., et al.: Statistical techniques for detecting cyberattacks on computer networks based on an analysis of abnormal traffic behavior. Int. J. Comput. Netw. Inf. Secur. 12(6), 1–13 (2020)

    Google Scholar 

  11. Chatzigiannakis, V., Androulidakis, G., Maglaris, B.: A Distributed Intrusion Detection Prototype Using Security Agents, HP OpenView University Association, pp. 14–25 (2004)

    Google Scholar 

  12. Berdibayev, R., Gnatyuk, S., Yevchenko, Y., Kishchenko, V.: A concept of the architecture and creation for SIEM system in critical infrastructure. In: Zaporozhets, A., Artemchuk, V. (eds.) Systems, Decision and Control in Energy II. SSDC, vol. 346, pp. 221–242. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-69189-9_13

    Chapter  Google Scholar 

  13. Zaliskyi, M., Odarchenko, R., Gnatyuk, S., Petrova, Y., Chaplits, A.: Method of traffic monitoring for DDoS attacks detection in e-health systems and networks. CEUR Workshop Proceedings, 20186, vol. 2255, pp. 193–204

    Google Scholar 

  14. Dilek, S., Çakır, H., Aydın, M.: Applications of artificial intelligence techniques to combating cyber crimes: a review. Int. J. Artif. Intell. Appl. 6(1), 21–39 (2015)

    Google Scholar 

  15. How Big Data Can Improve Cyber Security, Online access mode. https://csce.ucmss.com/cr/books/2017/LFS/CSREA2017/ABD3239.pdf

  16. Kirichenko, L.: Cyber threats detection using social networks analysis. Int. J. Inf. Technol. Knowl. 11, 23–32 (2017)

    Google Scholar 

  17. Charles, E., Samuel, M., Roger, N., et al.: Pat. № US20020038430 A1. System and method of data collection, processing, analysis, and annotation for monitoring cyber-threats and the notification thereof to subscribers (2012)

    Google Scholar 

  18. John, P., Frederick, D., Henry, P., et al.: Pat. № US9749343B2. System and method of cyber threat structure mapping and application to cyber threat mitigation (2013)

    Google Scholar 

  19. Chouhan, M.: Adaptive detection technique for cache-based side channel attack using Bloom Filter for secure cloud. Conf. Comput. Inf. Sci. 1, 293–297 (2016)

    Google Scholar 

  20. Sakr, M.M., Tawfeeq, M.A., El-Sisi, A.B.: An Efficiency optimization for network intrusion detection system. Int. J. Comput. Netw. Inf. Secur. 11(10), 1–11 (2019). https://doi.org/10.5815/ijcnis.2019.10.01

    Article  Google Scholar 

  21. Byrski, A., Carvalho, M.: Agent-based immunological intrusion detection system for mobile ad-hoc networks. In: Bubak, M., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds.) ICCS 2008. LNCS, vol. 5103, pp. 584–593. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-69389-5_66

    Chapter  Google Scholar 

  22. Zhang, Z.: Hide: a hierarchical network intrusion detection system using statistical preprocessing and neural network classification. IEEE Workshop Inf. Assur. Secur. 16, 85–90 (2001)

    Google Scholar 

  23. Arora, I.S., Bhatia, G.K., Singh, A.P.: Comparative analysis of classification algorithms on KDD’99 data set. Int. J. Comput. Netw. Inf. Secur. 8(9), 34–40 (2016). https://doi.org/10.5815/ijcnis.2016.09.05

    Article  Google Scholar 

  24. Hassan, Z., Odarchenko, R., Gnatyuk, S. et al.: Detection of distributed denial of service attacks using snort rules in cloud computing & remote control systems. In: Proceedings of the 2018 IEEE 5th International Conference on Methods and Systems of Navigation and Motion Control, October 16–18, pp. 283–288. Kyiv, Ukraine (2018)

    Google Scholar 

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Acknowledgment

This research study was conducted with support of research grant № AP06851243 “Methods, models and tools for security events and incidents management for detecting and preventing cyber attacks on critical infrastructures of digital economics” (2020–2022), funded by Ministry of Digital Development, Innovation and Aerospace Industry of the Republic of Kazakhstan.

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Correspondence to Sergiy Gnatyuk .

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Gnatyuk, S., Berdibayev, R., Smirnova, T., Avkurova, Z., Iavich, M. (2021). Cloud-Based Cyber Incidents Response System and Software Tools. In: Lopata, A., Gudonienė, D., Butkienė, R. (eds) Information and Software Technologies. ICIST 2021. Communications in Computer and Information Science, vol 1486. Springer, Cham. https://doi.org/10.1007/978-3-030-88304-1_14

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  • DOI: https://doi.org/10.1007/978-3-030-88304-1_14

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  • Online ISBN: 978-3-030-88304-1

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