Skip to main content
Log in

Catching up faster data in digital crime using mobile devices

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

Mass storage media are becoming increasingly common due to the spread of smartphones to which new technologies are applied. Correspondingly, the amount of data collected from digital crime has considerably increased. Previously, if an investigator did not properly conduct the initial response, valuable evidence would be lost. Thus, collection of digital evidence within a short time frame is required. Further, in searches using data from the smartphones to gather evidence, evidence must be collected and analyzed quickly. Therefore, in this paper, a method is proposed for rapidly collecting data at a crime scene based on the type of criminal charge. Once implemented, our method can collect data by accounting for each feature of the software, providing rapid results through a pattern search. There is also a range of options available with parallel routines. Single or multiple options can be utilized depending on the investigator’s requirements.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Akkaladevi S, Keesara H, Luo X (2011) Efficient forensic tools for handheld device: a comprehensive perspective. Softw Eng Res Manag Appl Stud Comput Intell 377:349–359

    Google Scholar 

  2. Andrew H (2011) Android forensics: investigation, analysis and mobile security for google android. Syngress

  3. Andrew H, Katie S (2011) iPhone and iOS forensics: investigation, analysis and mobile security for apple iPhone, iPad, and iOS devices. Syngress

  4. Andriotis P, Oikonomou G, Tryfonas T (2012) Forensic analysis of wireless networking evidence of android smartphones. 2012 I.E. International Workshop on Information Forensics and Security, pp. 109–114

  5. Baek SJ, Han JS, Chung KY (2013) Dynamic reconfiguration based on goal-scenario by adaptation strategy. Wirel Pers Commun. doi:10.1007/s11277-013-1239-0

    Google Scholar 

  6. Bertè R, Dellutri F, Grillo A, Lentini A, Me G, Ottaviani V (2009) Fast smartphones forensic analysis results through MIAT and forensic farm. Int J Electron Secur Digit Forensic Inderscience

  7. Choi J, Jang B, Kim GJ (2011) Organizing and presenting geospatial tags in location-based augmented reality. Pers Ubiquit Comput 15(6):641–647

    Article  Google Scholar 

  8. Dearman D, Inkpen M, Truong N (2010) Mobile map interactions during a rendezvous: exploring the implications of automation. Pers Ubiquit Comput 14(1):1–13

    Article  Google Scholar 

  9. Hourcade P, Rest B, Hansen E (2012) Multitouch tablet applications and activities to enhance the social skills of children with autism spectrum disorders. Pers Ubiquit Comput 16(2):157–168

    Article  Google Scholar 

  10. Hynes M, Wang H, McCarrick E, Kilmartin L (2011) Accurate monitoring of human physical activity levels for medical diagnosis and monitoring using off-the-shelf cellular handsets. Pers Ubiquit Comput 15(7):667–678

    Article  Google Scholar 

  11. Iqbal B, Iqbal A, Obaidli HA (2012) A novel method of iDevice (iPhone, iPad, iPod) forensics without jailbreaking. 2012 International Conference on Innovations in Information Technology, pp. 238–243

  12. Jung YG, Han MS, Chung KY, Lee SJ (2011) A study of a valid frequency range using correlation analysis of throat signal. Inf Int Interdisc J 14(11):3791–3799

    Google Scholar 

  13. Kim SH, Chung KY (2013) 3D simulator for stability analysis of finite slope causing plane activity. Multimed Tools Appl. doi:10.1007/s11042-013-1356-5

    Google Scholar 

  14. Kim JH, Chung KY (2013) Ontology-based healthcare context information model to implement ubiquitous environment. Multimed Tools Appl. doi:10.1007/s11042-011-0919-6

    Google Scholar 

  15. Kim SH, Chung KY (2013) Medical information service system based on human 3D anatomical model. Multimed Tools Appl. doi:10.1007/s11042-013-1584-8

    Google Scholar 

  16. Kim GH, Kim YG, Chung KY (2013) Towards virtualized and automated software performance test architecture. Multimed Tools Appl. doi:10.1007/s11042-013-1536-3

    Google Scholar 

  17. Kim JH, Lee D, Chung KY (2013) Item recommendation based on context-aware model for personalized u-healthcare service. Multimed Tools Appl. doi:10.1007/s11042-011-0920-0

    Google Scholar 

  18. Kim H, Reitmayr G, Woo W (2013) IMAF: in situ indoor modeling and annotation frame-work on mobile phones. Pers Ubiquit Comput 17(3):571–582

    Article  Google Scholar 

  19. Ko JW, Chung KY, Han JS (2013) Model transformation verification using similarity and graph comparison algorithm. Multimed Tools Appl. doi:10.1007/s11042-013-1581-y

    Google Scholar 

  20. Koufi V, Malamateniou F, Vassilacopoulos G (2010) A system for the provision of medical diagnostic and treatment advice in home care environment. Pers Ubiquit Comput 14(6):551–561

    Article  Google Scholar 

  21. Kubi AK, Saleem S, Popov O (2011) Evaluation of some tools for extracting e-evidence from mobile devices. Proc. of the International Conference on Application of Information and Communication Technologies, pp. 1–6

  22. Kuntze N, Rudolph C (2011) Secure digital chains of evidence. Proc. of the IEEE Inter-national Workshop on Systematic Approaches to Digital Forensic Engineering, pp. 1–8

  23. Lee KD, Nam MY, Chung KY, Lee YH, Kang UG (2013) Context and profile based cascade classifier for efficient people detection and safety care system. Multimed Tools Appl 63(1):27–44

    Article  Google Scholar 

  24. Lim JH, Song CW, Chung KY, Rim KW, Lee JH (2012) Forensic evidence collection procedures of smartphone in crime scene. Proc. of the 2th International Conference IT Convergence and Security 2012, LNEE 215, pp. 711–718, Springer

  25. Lin IL, Chao HC, Peng SH (2011) Research of digital evidence forensics standard operating procedure with comparison and analysis based on smart phone. Proc. of the International Conference on Broadband and Wireless Computing, Communication and Applications, pp. 386–391

  26. Lopez P, Orfila A, Palomar E, Castro H (2012) A secure distance-based RFID identification protocol with an off-line back-end database. Pers Ubiquit Comput 16(3):351–365

    Article  Google Scholar 

  27. Moreland D, Nepal S, Hwang H, Zic J (2010) A snapshot of trusted personal devices applicable to transaction processing. Pers Ubiquit Comput 14(4):347–361

    Article  Google Scholar 

  28. Oh SY, Chung KY (2013) Target speech feature extraction using non-parametric correlation coefficient. Clust Comput. doi:10.1007/s10586-013-0284-5

    Google Scholar 

  29. Otani T, Kobayashi H (2013) A SCADA system using mobile agents for a next-generation distribution system. IEEE Trans Power Deliv. doi:10.1109/TPWRD.2012.2222055

    Google Scholar 

  30. Portet F, Vacher M, Golanski C, Roux C, Meillon B (2013) Design and evaluation of a smart home voice interface for the elderly: acceptability and objection aspects. Pers Ubiquit Comput 17(1):127–144

    Article  Google Scholar 

  31. Raghav S, Saxena AK (2009) Mobile forensics: guidelines and challenges in data preservation and acquisition. 2009 I.E. Student Conference on Research and Development, pp. 5–8

  32. Said H, Yousif A, Humaid H (2011) IPhone forensics techniques and crime investigation. Proc. of the International Conference and Workshop on Current Trends in Information Technology, pp. 120–125

  33. Salmela L, Tarhio J, Kalsi P (2007) Approximate Boyer-Moore string matching for small alphabets. Proceedings of String Processing and Information Retrieval, pp. 173–183

  34. Song CW, Chung KY, Jung JJ, Rim KW, Lee JH (2011) Localized approximation method using inertial compensation in WSNs. Inf Int Interdisc J 14(11):3591–3600

    Google Scholar 

  35. Song CW, Lee D, Chung KY, Rim KW, Lee JH (2013) Interactive middleware architecture for lifelog based context awareness. Multimed Tools Appl. doi:10.1007/s11042-013-1362-7

    Google Scholar 

  36. Song CW, Lim JH, Chung KY, Rim KW, Lee JH (2012) Fast data acquisition with mobile device in digital crime. Proc. of the 2th International Conference IT Convergence and Security 2012, LNEE 215, pp. 711–718, Springer

  37. Wu S (1994) A fast algorithm for multi-pattern searching. Technical Report Department of Computer Science Chung-Cheng University

  38. Zareen A, Baig S (2010) Mobile phone forensics: challenges, analysis and tools classification. Proc. of the IEEE International Workshop on Systematic Approaches to Digital Forensic Engineering, pp. 47–55

  39. Zhang Y, Huang H, Yang D, Zhang H, Chao HC, Huang YM (2009) Bring QoS to P2P-based semantic service discovery for the universal network. Pers Ubiquit Comput 13(7):1–13

    Article  MATH  Google Scholar 

  40. Zheng K, Zheng Y, Yuan NJ, Shang S (2013) On discovery of gathering patterns from trajectories. 2013 I.E. 29th International Conference on Data Engineering, pp. 242–253

  41. National Institute of Justice (2009) Electronic Crime Scene Investigation: An On-the-Scene Reference for First Responders

Download references

Acknowledgement

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2013R1A1A2059964).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chang-Woo Song.

Additional information

This paper is significantly revised from an earlier version presented at [24, 36].

Rights and permissions

Reprints and permissions

About this article

Cite this article

Song, CW., Chung, KY. & Lee, JH. Catching up faster data in digital crime using mobile devices. Multimed Tools Appl 74, 9007–9016 (2015). https://doi.org/10.1007/s11042-013-1725-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-013-1725-0

Keywords

Navigation