Skip to main content
SpringerLink
Log in

Method for Cyber Threats Detection and Identification in Modern Cloud Services

  • Conference paper
  • First Online:
Advances in Computer Science for Engineering and Education IV (ICCSEEA 2021)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 83))

Abstract

Today cloud technologies and their applications are implementing in various ICT infrastructures. It has led to increased attention to the problems of cyber threats, the growth of which is inseparably linked with the growth of ICT. In this paper the analysis of the existing models, systems and methods for cyber threats detection was carried out for their disadvantages defining. A model of cloud service has been developed; it allows to ensure the security of cloud service based on cloud computing and conduct appropriate simulations. 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 NSL-KDD data base 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 by 48.02%. In addition, a cloud service model has been developed that can be used to build cloud services based on the various cloud computing architecture. In the future, based on the proposed method and model, appropriate tools for detecting and classifying cyber threats in cloud services can be developed. It is significant because it can be autonomous functional unit of SIEM as well as other instrumental tools of CSIRT/SOC.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

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. Anderson, J.P.: Computer security threat monitoring and surveillance. Tech. Rep. Contract 36, 179–185 (1982)

    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., Gnatyuk, V., Sydorenko, V., et al.: Method for cyberincidents network-centric monitoring in critical information infrastructure”. Int. J. Comput. Netw. Inf. Secur. 9(6), 30–43 (2017). https://doi.org/10.5815/ijcnis.2017.06.04

    Article  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. Abraham, T.: IDDM: intrusion detection using data mining techniques. DSTO Electron. Surveill. Res. Lab. 9, 30–39 (2001)

    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. In: CEUR Workshop Proceedings, 20186, vol. 2255, pp. 193–204 (2018)

    Google Scholar 

  14. 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 

  15. Zhengbing, H., Gnatyuk, S., Koval, O., Gnatyuk, V., Bondarovets, S.: Anomaly detection system in secure cloud computing environment. Int. J. Comput. Netw. Inf. Secur. 9(4), 10–21 (2017). https://doi.org/10.5815/ijcnis.2017.04.02

    Article  Google Scholar 

  16. Li, H.-H., Wu, C.-L.: Study of network access control system featuring collaboratively interacting network security components. Int. Rev. Comput. Softw. 8(2), 527–532 (2013)

    Google Scholar 

  17. 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 

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

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

    MathSciNet  Google Scholar 

  20. Cisco creates self-defending networks for cyber threats detection, Online access mode. https://nag.ru/news/newsline/30762/v-cisco-sozdayut-samooboronyayuschuyusya-set-dlya-vyiyavleniya-kiberugroz.html

  21. Xiaohua, Y.: Early detection of cyber security threats using structured behavior modeling. ACM Trans. Inf. Syst. Secur. 5, 10–35 (2013)

    Google Scholar 

  22. Methods for deep analytics to counteract of modern threats, Online access mode. http://bis-expert.ru/sites/default/files/archives/2016/bis9_konovalov.pdf

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

    Article  Google Scholar 

  24. Pat. No WO2015159287. System and method for cyber threats detection; author Malachi Y.; Accessed 22 October 2015

    Google Scholar 

  25. 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 Intern. Conf. on Methods and Systems of Navigation and Motion Control, 16–18 October 2018. Kyiv, Ukraine, pp. 283–288 (2018)

    Google Scholar 

  26. 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 

  27. 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 

  28. Pat. No US20020038430 A1. System and method of data collection, processing, analysis, and annotation for monitoring cyber-threats and the notification thereof to subscribers; authors Charles Ed., Samuel M., Roger N., Daniel O.; Accessed 23 March 2012

    Google Scholar 

  29. Pat. No US9749343B2. System and method of cyber threat structure mapping and application to cyber threat mitigation; authors John P, Frederick D., Henry P., Keane M.; Accessed 4 March 2013

    Google Scholar 

  30. 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. (IJCNIS) 8(9), 34–40 (2016). https://doi.org/10.5815/ijcnis.2016.09.05

    Article  Google Scholar 

  31. Buyya, R., Ranjan, R., Calheiros, R.: Modeling and simulation of scalable cloud computing environments and the CloudSim toolkit: Challenges and opportunities. In: International Conference on High Performance Computing Simulation USA, IEEE, pp. 1–11 (2009)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Central China Normal University, Wuhan, China

    Zhengbing Hu

  2. National Aviation University, Kyiv, Ukraine

    Zhengbing Hu & Sergiy Gnatyuk

  3. Yessenov University, Aktau, Kazakhstan

    Sergiy Gnatyuk & Berik Akhmetov

  4. International Research and Training Center for Information, Technologies and Systems, Kyiv, Ukraine

    Sergiy Gnatyuk & Volodymyr Simakhin

  5. Kazakh Humanitarian Juridical Innovative University, Semey, Kazakhstan

    Dinara Ospanova

  6. Satbayev University, Almaty, Kazakhstan

    Nurbol Akatayev

Authors
  1. Zhengbing Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sergiy Gnatyuk
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Berik Akhmetov
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Volodymyr Simakhin
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Dinara Ospanova
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Nurbol Akatayev
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sergiy Gnatyuk .

Editor information

Editors and Affiliations

  1. School of Educational Information Technology, Central China Normal University, Wuhan, China

    Zhengbing Hu

  2. Mechanical Engineering Research Institute of the Russian Academy of Sciences, Moscow, Russia

    Sergey Petoukhov

  3. Faculty of Applied Mathematics, National Technical University of Ukraine “Igor Sikorsky Kiev Polytechnic Institute”, Kiev, Ukraine

    Ivan Dychka

  4. Halmos College of Natural Sciences and Oceanography, Nova Southeastern University, Plantation, FL, USA

    Matthew He

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Hu, Z., Gnatyuk, S., Akhmetov, B., Simakhin, V., Ospanova, D., Akatayev, N. (2021). Method for Cyber Threats Detection and Identification in Modern Cloud Services. In: Hu, Z., Petoukhov, S., Dychka, I., He, M. (eds) Advances in Computer Science for Engineering and Education IV. ICCSEEA 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 83. Springer, Cham. https://doi.org/10.1007/978-3-030-80472-5_28

Download citation

Publish with us

Policies and ethics

Search

Navigation