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The Direction of Information Security Control Analysis Using Artificial Intelligence

  • Sangdo Lee
  • Yongtae Shin
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 474)

Abstract

The areas where artificial intelligence (AI) is employed are gradually increasing. The latest malicious codes are continually being found in the security control area and the security teams in various organizations are investigating an average of 200,000 security incidents a day and often wasting much of their time in tracking wrong targets or attacking methods. It is expected that the security-related incidents will be increased more than twice in near future. Thus, the security control staff will be able to prevent security breaches only by rapidly analyzing the latest vulnerabilities and logs in their systems or security equipment. In this study, we have studied the possibility of utilizing current AIs used for diagnosis of cancers, translations or simple conversations, along with the future direction of AI for security control. The study also attempts to find an effective method of reducing damages by rapidly analyzing attack methods and vulnerabilities, hoping the method will be effective in protecting the systems from a new variety of attacks.

Keywords

Cyber security SIEM Artificial intelligence Watson Hacking 

References

  1. 1.
    ITU-T Q.4/17 Proposed initial draft text for Rec. ITU-T X. cybex, Cybersecurity information exchange framework (TD503)Google Scholar
  2. 2.
    Chen, P., Desmet, L., Huygens, C.: A study on advanced persistent threats. Communications and Multimedia Security, pp. 63–72 (2014)Google Scholar
  3. 3.
    Jang, J., Moon, J.S.: A real-time user authenticating method using behavior pattern through web. J. Korea Inst. Secur. Cryptol. 26(6), 1493–1504 (2016)CrossRefGoogle Scholar
  4. 4.
    Choi, J.: A study on a scenarios development guideline for detecting security threats. Korea National Open University (2015)Google Scholar
  5. 5.
    Ghafir, I., Prenosil, V.: Advanced Persistent Threat Attack Detection. muni.cz, p. 2 (2014)Google Scholar
  6. 6.
    Zope, A.R., Vidhate, A., Harale, N.: Data mining approach in security information and event management. Int. J. Future Comput. Commun. 2(2), 80–84 (2013)CrossRefGoogle Scholar
  7. 7.
    Kim, Y.-J., Lee, S., Kwon, H.-Y., Lim, J.: A study on the improvement of effectiveness in national cyber security monitoring and control services. Korea Institute of Information Security and Cryptology, pp. 2–3 (2009)Google Scholar
  8. 8.
    IBM x-force threat intelligence quarterly, 1Q, p. 7 (2015)Google Scholar
  9. 9.
    NIST FIPS PUB 800-92, Guide to Computer Security Log Management (2006)Google Scholar
  10. 10.
    Huh, J.-H., Otgonchimeg, S., Seo, K.: Advanced metering infrastructure design and test bed experiment using intelligent agents: focusing on the PLC network base technology for smart grid system. J. Supercomput. 72(5), 1862–1877 (2016). Springer, USACrossRefGoogle Scholar
  11. 11.
    Huh, J.-H., Koh, T., Seo, K.: A design of reefer container monitoring system using PLC-based technology. In: Proceedings of the 2015 International Conference on Electrical and Information Technologies for Rail Transportation, vol. 377, pp. 795–802. Springer, Heidelberg (2016)Google Scholar
  12. 12.
    Huh, J.-H., Seo, K.: A preliminary analysis model of big data for prevention of bioaccumulation of heavy metal-based pollutants: focusing on the atmospheric data analyses for smart farm. Contemp. Eng. Sc. 9(30), 1447–1462 (2016). Hikari Ltd.CrossRefGoogle Scholar
  13. 13.
    Bu, Y., Seo, K., Huh, J.-H.: A study of enhancement of ranging performance of beacons through improvement of the smart phone’s gyroscope: focusing on the Bluetooth low energy. In: Proceedings of the 11th International Conference on Ubiquitous Information Management and Communication. ACM (2017)Google Scholar
  14. 14.
    Huh, J.-H., Seo, K.: Design and test bed experiments of server operation system using virtualization technology. Hum.-centric Comput. Inf. Sci. HCIS 6(1), 1–21 (2016). SpringerCrossRefGoogle Scholar
  15. 15.
    Huh, M.K., Huh, H.W.: Genetic diversity and phylogenetic relationships in alder, Alnus firma, revealed by AFLP. J. Plant Biol. 44(1), 33–40 (2001). Springer, New YorkCrossRefGoogle Scholar
  16. 16.
    Huh, J.-H., Kim, N., Seo, K.: Design and implementation of mobile medication-hour notification system with push service function. Int. J. Appl. Eng. Res 11(2), 1225–1231 (2016)Google Scholar
  17. 17.
    Huh, J.-H.: PLC-based design of monitoring system for ICT-integrated vertical fish farm. Hum.-centric Comput. Inf. Sci. 7(1), 1–19 (2017). SpringerMathSciNetCrossRefGoogle Scholar
  18. 18.
    Huh, J.-H.: Smart Grid Test Bed Using OPNET and Power Line Communication, pp. 66–120. IGI Global, Hershey (2017)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringSoongsil UniversitySeoulRepublic of Korea

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