Electronic Commerce Research

, Volume 13, Issue 3, pp 379–398 | Cite as

A framework for unified digital evidence management in security convergence

  • Kyung-Soo Lim
  • Changhoon Lee


Digital Forensics is being actively researched and performed in various areas against changing IT environment such as mobile phone, e-commerce, cloud service and video surveillance. Moreover, it is necessary to research unified digital evidence management for correlation analysis from diverse sources. Meanwhile, various triage approaches have been developed to cope with the growing amount of digital evidence being encountered in criminal cases, enterprise investigations and military contexts. Despite of debating over whether triage inspection is necessary or not, it will be essential to develop a framework for managing scattered digital evidences. This paper presents a framework with unified digital evidence management for appropriate security convergence, which is based on triage investigation. Moreover, this paper describes a framework in network video surveillance system to shows how it works as an unified evidence management for storing diverse digital evidences, which is a good example of security convergence.


Digital Forensics Digital evidence container Triage Investigation 



This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (grant number 2010-0005571).


  1. 1.
    Kshetri, N. (2013). Cybercrime and cyber-security issues associated with China: some economic and institutional considerations. Electronic Commerce Research, 13(1), 41–69. CrossRefGoogle Scholar
  2. 2.
    Narayanasamy, K., Rasiah, D., & Tan, T. M. (2011). The adoption and concerns of e-finance in Malaysia. Electronic Commerce Research, 11(4), 383–400. CrossRefGoogle Scholar
  3. 3.
    Antoniou, G., & Batten, L. (2011). E-commerce: protecting purchaser privacy to enforce trust. Electronic Commerce Research, 11, 421–456. CrossRefGoogle Scholar
  4. 4.
    Taylor, D. G., Donna, F. D., & Jillapalli, R. (2009). Privacy concern and online personalization: the moderating effects of information control and compensation. Electronic Commerce Research, 9(3), 203–223. CrossRefGoogle Scholar
  5. 5.
    Lim, K.-S., Park, J., Lee, C., & Lee, S. (2011). A new proposal for a digital evidence container for triage investigation. In ICCSCE’11. Google Scholar
  6. 6.
    Rogers, M. K., Goldman, J., Mislan, R., Wedge, T., & Debrot, S. (2006). Computer forensics field triage process model. In Conference on digital forensics, security and law. Google Scholar
  7. 7.
    Richard, G. G. III, Roussev, V., & Marziale, L. (2007). Forensic discovery auditing of digital evidence containers. Digital Investigation, 4, 88–97. CrossRefGoogle Scholar
  8. 8.
    Lim, K.-s., Lee, S., & Lee, S. (2009). Applying a stepwise forensic approach to incident response and computer usage analysis. In 2nd international conference on computer science and its application (CSA 2009). Google Scholar
  9. 9.
    Turner, P. (2005). Unification of digital evidence from disparate sources (digital evidence bags). Digital Investigation, 2(3), 223–228. CrossRefGoogle Scholar
  10. 10.
    Turner, P. (2006). Selective and intelligent imaging using digital evidence bags. Digital Investigation, 3 Supplement, 59–64. CrossRefGoogle Scholar
  11. 11.
    Turner, P. (2007). Applying a forensic approach to incident response, network investigation and system administration using digital evidence bags. Digital Investigation, 4(1), 30–35. CrossRefGoogle Scholar
  12. 12.
  13. 13.
  14. 14.
    Chang, K., Chen, C., Chen, J., & Chao, H. (2010). Challenges to next generation services in IP multimedia subsystem. Journal of Information Processing Systems, 6(2), 129–146. CrossRefGoogle Scholar
  15. 15.
  16. 16.
    Satone, M., & Kharate, D. G. (2012). Face Recognition based on PCA on wavelet subband of average-half-face. Journal of Information Processing Systems, 8(3), 483–494. CrossRefGoogle Scholar
  17. 17.
    Nagi, G. M., Rahmat, R., Khalid, F., & Taufik, M. (2013). Region-based facial expression recognition in still images. Journal of Information Processing Systems, 9(1), 173. CrossRefGoogle Scholar
  18. 18.
    Ghimire, D., & Lee, J. (2013). A robust face detection method based on skin color and edges. Journal of Information Processing Systems, 9(1), 141–156. CrossRefGoogle Scholar
  19. 19.
  20. 20.
  21. 21.
    Lim, K.-S., & Lee, C. (2012). Applying forensic approach to live investigation using XeBag. In Computer science and its applications. Google Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Convergence Service Security Research LaboratoryElectronics and Telecommunications Research Institute (ETRI)DaejeonSouth Korea
  2. 2.Department of Computer Science and EngineeringSeoul National University of Science & TechnologySeoulSouth Korea

Personalised recommendations