한국융합학회논문지 (Journal of the Korea Convergence Society)

  • 제9권5호
  • /
  • Pages.27-32
  • /
  • 2018
  • /
  • 2233-4890(pISSN)
  • /
  • 2713-6353(eISSN)
한국융합학회 (Korea Convergence Society)
권호 표지
DOI QR코드

DOI QR Code

포그 컴퓨팅 보안 모델과 보안 요구사항 연구: 서베이

Research on Security Model and Requirements for Fog Computing: Survey

  • 투고 : 2018.04.09
  • 심사 : 2018.05.20
  • 발행 : 2018.05.28
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

4차 산업혁명시대 핵심인 IoT(사물인터넷) 기술이 발전하면서 다양한 적용 분야가 생겨나고 있으며, 그에 따른 서비스를 이용하는 사용자 수도 대폭 증가하고 있다. 주변 환경에 흩어져 있는 수많은 IoT 디바이스들에 의해 생성되는 실시간 센싱 데이터들을 실시간 클라우드 컴퓨팅 환경에 전송하여 저장하는 것은 시간 및 저장 공간에 대한 효율성이 적합하지 않다. 따라서 이러한 문제들을 해결하기 위해서 응답시간을 최소화 하면서 처리 시간이 효율적으로 관리가 될 수 있도록 하는 포그 컴퓨팅이 제안되었다. 그러나 포그 컴퓨팅이라는 새로운 패러다임에 대한 보안 요구사항이 아직 정립되지 않고 있다. 클라우드 끝단에 있는 센서노드들은 컴퓨팅 파워가 높지 않기 때문에 보안 모듈을 적용하기가 어렵고, 보안 모듈 적용 시에 경량화된 프로토콜 적용을 통하여 보안과 효율성을 수립하여야 한다. 따라서 이 논문에서는 포그 컴퓨팅에 대한 보안 모델 제시와 포그 컴퓨팅에 최적화된 보안 요구사항을 제시하여 안전한 포그 컴퓨팅 발전에 기여한다.

IoT technology is developing with various application areas in $4^{th}$ Industrial revolution. There are many users using the application services. Sensing data from various environment need to be transferred to cloud computing storage and store in the cloud storage. However, physical distance from the end node to cloud computing storage is far away, and it is not efficient to transfer data from sensors and store the sensing data in the cloud storage whenever sensing data happen. Therefore, Fog computing is proposed to solve these problems which can process and store the sensing data. However, Fog computing is new emerging technology, there is no standard security model and requirements. This research proposes to security requirements and security model for Fog computing to establish a secure and efficient cloud computing environment.

키워드

참고문헌

  1. S. Hong. (2017). Research on IoT International Strategic Standard Model. Journal of the Korea Convergence Society, 8(2), 21-26. doi:10.15207/jkcs.2017.8.2.021
  2. S. Hong. (2014). Analysis of DDoS Attack and Countermeasure: Survey. The Journal of Digital Policy and Management, 12(1), 423-429. doi:10.14400/jdpm.2014.12.1.423
  3. C. Gu, Y. Zheng, F. Kang & D. Xin. (2015). Keyword Search Over Encrypted Data in Cloud Computing from Lattices in the Standard Model. Cloud Computing and Big Data Lecture Notes in Computer Science, 335-343. doi:10.1007/978-3-319-28430-9_25
  4. K. Tammemae, A. Jantsch, A. Kuusik, J. Preden & E. Ounapuu. (2017). Self-Aware Fog Computing in Private and Secure Spheres. Fog Computing in the Internet of Things, 71-99. doi:10.1007/978-3-319-57639-8_5
  5. P. K. Rayani, B. Bhushan & V. R. Thakare. (2018). Multi-Layer Token Based Authentication Through Honey Password in Fog Computing. International Journal of Fog Computing, 1(1), 50-62. doi:10.4018/ijfc.2018010104
  6. V. Mushunuri, A. Kattepur, H. K. Rath, & A. Simha. (2017). Resource optimization in fog enabled IoT deployments. 2017 Second International Conference on Fog and Mobile Edge Computing (FMEC). doi:10.1109/fmec.2017.7946400
  7. Cloud and Fog Computing. (2017). Secure Connected Objects, 238-247. doi:10.1002/9781119426639.ch17
  8. R. Rios, R. Roman, J. A. Onieva & J. Lopez. (2017). From SMOG to Fog: A security perspective. 2017 Second International Conference on Fog and Mobile Edge Computing (FMEC). doi:10.1109/fmec.2017.7946408.
  9. S. Hong, S. Lim & J. Song. (2011). Unified Modeling Language based Analysis of Security Attacks in Wireless Sensor Networks: A Survey. KSII Transactions on Internet and Information Systems, 805-821. doi:10.3837/tiis.2011.04.010
  10. S. Hong. (2013). Disconnection of Wireless LAN Attack and Countermeasure. The Journal of Digital Policy and Management, 11(12), 453-458. doi:10.14400/jdpm.2013.11.12.453
  11. Hong, S. (2015). Two-channel user authentication by using USB on Cloud. Journal of Computer Virology and Hacking Techniques, 12(3), 137-143. doi:10.1007/s11416-015-0254-y
  12. S. Hong. (2017). Secure and light IoT protocol (SLIP) for anti-hacking. Journal of Computer Virology and Hacking Techniques, 13(4), 241-247. doi:10.1007/s11416-017-0295-5.
  13. K. Choi & J. A. Yoo. (2015). A reviews on the social network analysis using R. Journal of the Korea Convergence Society, 6(1), 77-83. doi:10.15207/jkcs.2015.6.1.077
  14. G. Ryu. (2015). Development of Educational Model for ICT-based Convergence Expert. Journal of the Korea Convergence Society, 6(6), 75-80. doi:10.15207/jkcs.2015.6.6.075.
  15. Y. Joh, Y. (2014). A Framework for IoT-Based Convergence Personalized Menu Recommendation System. Journal of the Korea Convergence Society ,5(4), 147-153. doi:10.15207/jkcs.2014.5.4.147.
  16. Fog Computing and compare with Cloud Computing. (2017). International Journal of Recent Trends in Engineering and Research, 3(12), 129-131. doi:10.23883/ijrter.2017.3546.pszaf
  17. B. Negash, A. M. Rahmani, P. Liljeberg & A. Jantsch. (2017). Fog Computing Fundamentals in the Internet-of-Things. Fog Computing in the Internet of Things, 3-13. doi:10.1007/978-3-319-57639-8_1