DOI QR코드

DOI QR Code

Security Framework for Intelligent Predictive Surveillance Systems

지능형 예측감시 시스템을 위한 보안 프레임워크

  • Park, Jeonghun (Dept. of Conv. Infor. Security, Graduate Sch., Jeju Natl. University) ;
  • Park, Namje (Dept. of Computer Education, Teachers College, Jeju Natl. University)
  • 박정훈 (제주대학교 대학원 융합정보보안학과) ;
  • 박남제 (제주대학교 교육대학 초등컴퓨터교육전공)
  • Received : 2020.02.07
  • Accepted : 2020.03.20
  • Published : 2020.03.28

Abstract

Recently, intelligent predictive surveillance system has emerged. It is a system that can probabilistically predict the future situation and event based on the existing data beyond the scope of the current object or object motion and situation recognition. Since such intelligent predictive monitoring system has a high possibility of handling personal information, security consideration is essential for protecting personal information. The existing video surveillance framework has limitations in terms of privacy. In this paper, we proposed a security framework for intelligent predictive surveillance system. In the proposed method, detailed components for each unit are specified by dividing them into terminals, transmission, monitoring, and monitoring layers. In particular, it supports active personal information protection in the video surveillance process by supporting detailed access control and de-identification.

최근 지능형 예측감시 시스템이 등장하고 있다. 지능형 예측감시 시스템의 추론을 위해서는 현재 및 과거의 데이터가 필요하며, 이러한 데이터의 분석을 통하여 곧 발생할 상황에 대한 예측을 가능하게 한다. 그러나, 이러한 과정에서 영상 객체의 개인정보를 취급하게 될 소지가 높으므로, 개인정보보호를 위해서는 보안에 대한 고려가 필수적이다. 특히, 개인의 생활패턴, 주요 이동 경로 등에 대한 정보가 해킹을 통하여 공개적으로 노출된다면 프라이버시 측면에서 문제가 될 것이다. 기존의 영상감시 프레임워크는 개인정보보호 측면에서 한계점이 있으며, 특히 개인정보보호에 취약한 측면이 있다. 본 논문에서는 개인정보보호를 고려한 지능형 예측감시 시스템을 위한 보안 프레임워크를 제안하였다. 제안한 방법에서는 단말, 전송, 감시, 모니터링 계층으로 구분하여 단위별 세부 구성요소를 명시하였으며, 특히 객체 단위별 세부 접근제어와 비식별화를 지원하여 영상감시 과정에서의 능동형 개인정보보호가 가능하다. 또한, 데이터 전송시 보안 기능과 RBAC 제공을 통한 접근제어의 장점을 갖는다.

Keywords

References

  1. Kokkonis. George et al. (2017). Real-time wireless multisensory smart surveillance with 3D-HEVC streams for internet-of-things (IoT). The Journal of Supercomputing, 73(3), 1044-1062. https://doi.org/10.1007/s11227-016-1769-9
  2. Sathishkumar. M. & S. Rajini. (2015). Smart surveillance system using pir sensor network and gsm. International Journal of Advnced Research in Computer Engineering & Technology, 4(1), 70-74.
  3. Nagothu. Deeraj et al. (2018). A microservice-enabled architecture for smart surveillance using blockchain technology. IEEE International Smart Cities Conference (ISC2), IEEE, 1-4.
  4. M. G. Ball, B. Qela & S. Wesolkowski. (2016). A review of the use of computational intelligence in the design of military surveillance networks. Recent Advances in Computational Intelligence in Defense and Security, Springer, 663-693.
  5. Campbell, Dan et al. (2016). Command and Control, Cyber, Communications, Intelligence, Surveillance and Reconnaissance (CRISR) and Cyber Tactical Measures. GEORGIA TECH RESEARCH INSTITUTE (GTRI), AFRL-RI-RS-TR-2016-209, Atlanta United States.
  6. Lin, C. F., Yuan, S. M., Leu, M. C. & Tsai, C. T. (2012). A framework for scalable cloud video recorder system in surveillance environment. In Ubiquitous intelligence & computing and 9th international conference on autonomic & trusted computing (UIC/ATC), IEEE, 655-660.
  7. M. Anwar Hossain. (2014). Framework for a cloud-based multimedia surveillance system. International Journal of Distributed Sensor Networks, 10(5), 1-11.
  8. D. Lee & N. Park. (2017). Geocasting-based synchronization of Almanac on the maritime cloud for distributed smart surveillance. The Journal of Supercomputing, 73(3), 1103-1118. https://doi.org/10.1007/s11227-016-1841-5
  9. J. Kim, N. Park, G. Kim & S. Jin. (2019). CCTV video processing metadata security scheme using character order preserving transformation in the emerging multimedia. Electronics, 8(4), 412. https://doi.org/10.3390/electronics8040412
  10. D. Lee. (2018). A Privacy Enhanced Video Surveillance Framework using Metadata De-identification, Doctoral dissertation. Jeju National University, Korea.
  11. N. Park, B. G. Kim & J. S. Kim. (2019). A Mechanism of Masking Identification Information Regarding Moving Objects Recorded on Visual Surveillance Systems by Differentially Implementing Access Permission. Electronics, 8(7), 735. https://doi.org/10.3390/electronics8070735
  12. D. Lee, N. Park, G. Kim & S. Jin. (2018). De-identification of metering data for smart grid personal security in intelligent CCTV-based P2P cloud computing environment. Peer-To-Peer Networking and Applications, 11(6), 1299-1308. https://doi.org/10.1007/s12083-018-0637-1
  13. N. Park, H. Hu & Q. Jin. (2016). Security and Privacy Mechanisms for Sensor Middleware and Application in Internet of Things (IoT). International Distributed Sensor Networks [Online], https://doi.org/10.1155/2016/2965438
  14. N. Park, J. Kwak, S. Kim, D. Won & H. Kim. (2006). WIPI Mobile Platform with Secure Service for Mobile RFID Network Environment. Advanced Web and Network Technologies, and Applications, LNCS, 741-748.
  15. D. Lee & N. Park. (2018). Electronic Identity Information Hiding Methods Using a Secret Sharing Scheme in Multimedia-centric Internet of Things Environment. Personal and Ubiquitous Computing, 22(1), 3-10. https://doi.org/10.1007/s00779-017-1017-1
  16. N. Park & N. Kang. (2015). Mutual Authentication Scheme in Secure Internet of Things Technology for Comfortable Lifestyle. Sensors, 16(1), 1-16. https://doi.org/10.3390/s16010001
  17. N. Park, Y. Sung, Y. Jeong, S. B. Shin & C. Kim. (2018). The Analysis of the Appropriateness of Information Education Curriculum Standard Model for Elementary School in Korea. International Conference on Computer and Information Science, 791, 1-15.
  18. J. Kim & N. Park. (2019). Lightweight knowledge-based authentication model for intelligent closed circuit television in mobile personal computing. Personal and Ubiquitous Computing, 1-9.
  19. N. Park & M. Kim. (2014). Implementation of load management application system using smart grid privacy policy in energy management service environment. Cluster Computing, 17(3), 653-664. https://doi.org/10.1007/s10586-014-0367-y