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Digital forensics investigation methodology applicable for social network services

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Abstract

Social network services (SNSs) contain various information such as conversations between users, user location information, personal network, and user psychology. This information can be useful for incident investigation. However, in SNSs, unlike computing services that offer services by saving data on a device, a device that uses a SNS with real-time synchronization generally only saves information that is not effective evidence, such as SNS usage log records. However, if digital evidence can be collected through an appropriate digital forensic process, various information such as a social network user’s friend list, conversations, and personal relationships can be collected as digital evidence. Therefore, this paper suggests a digital forensic process for digital devices using SNSs. To analyze digital evidence about SNSs, this proposed method is composed of effective processes, classifying digital devices, collecting digital evidence, and analysis.

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References

  1. Choi J (2013) Boston terrorist suspects captured? Seoulnewspaper, 2013. 04

  2. Chorianopoulos K (2013) Collective intelligence within web video. Hum Centric Comput Inf Sci 3:10

    Article  Google Scholar 

  3. Dubey T, Sahu OP (2011) Self-localized packet forwarding in wireless sensor networks. J Inf Process Syst 9(3):477–488

    Article  Google Scholar 

  4. Gallego D, Huecas G (2012) An empirical case of a context-aware mobile recommender system in a banking environment. J Converg 3(No2):31–38

    Google Scholar 

  5. Gallego D, Huecas G (2012) An empirical case of a context-aware mobile recommender system in a banking environment. J Converg 3(No 4):49–56

    Google Scholar 

  6. Jang Y, Kwak J (2013) Mobile digital forensic procedure for social network service. J Korea Navig Inst 17(No 3):325–331

    Article  MathSciNet  Google Scholar 

  7. Kim I (2013) Crime tail caught in the SNS. etnews, http://www.etnews.com. 2013. 4

  8. Lee J, Jung H, Lee S (2012) Forensic investigation procedure for real-time synchronization service. J Korea Inst Inf Secur Cryptol 22(No 6):1363–1374, 12

    MathSciNet  Google Scholar 

  9. Lee S, Kim H, Lee S, Lim J (2006) A study of memory information collection and analysis in a view of digital forensic in window system. J Korea Inst Inf Secur Cryptol 11(No 3):87–96, 2

    Google Scholar 

  10. Lee S-H, Lee I-Y, Lee S-H, Lee I-Y (2011) A secure index management scheme for providing data sharing in cloud storage. J Inf Process Syst 9(No.2):287–300

    Article  Google Scholar 

  11. Lim S (2011) Wife murdering professor complicity with the Mistress. MBC NEWS, 2011. 5

  12. Pyshkin E, Kuznetsov A (2010) An empirical case of a context-aware mobile recommender system in a banking environment. J Converg 1(No 1):1–8

    Google Scholar 

  13. Shtykh RY, Jin Q, Teraoka T (2011) A human-centric integrated approach to web information search and sharing. Hum Centric Comput Inf Sci 1

  14. Teraoka T (2012) Organization and exploration of heterogeneous personal data collected in daily life. Hum Centric Comput Inf Sci 2:1–15

    Article  Google Scholar 

  15. Zou M, Han L, Liu M, Liu Q (2011) Virus detection method based on behavior resource tree. J Inf Process Syst 7(No.1):173–186

    Article  Google Scholar 

Download references

Acknowledgments

This research was funded by the MSIP (Ministry of Science, ICT & Future Planning), Korea in the ICT R & D Program 2014.

This paper is extended and improved from accepted paper of KCIC-2013/FCC-2014.

This work was supported by the Soonchunhyang University Research Fund.

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Authors and Affiliations

  1. ISAA Lab Department of Information Security Engineering Soonchunhyang University, Asan, South Korea

    Yu-Jong Jang

  2. Department of Information Security Engineering Soonchunhyang University, Asan, South Korea

    Jin Kwak

Authors
  1. Yu-Jong Jang
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  2. Jin Kwak
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Corresponding authors

Correspondence to Yu-Jong Jang or Jin Kwak.

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Jang, YJ., Kwak, J. Digital forensics investigation methodology applicable for social network services. Multimed Tools Appl 74, 5029–5040 (2015). https://doi.org/10.1007/s11042-014-2061-8

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  • DOI: https://doi.org/10.1007/s11042-014-2061-8

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