Identification of Tampered SMS Messages in iPhone – A Case Study

Authors

  • Chunduru ESP Computer Forensic Unit, Central Forensic Science Laboratory, Hyderabad
  • Mangarai K Computer Forensic Unit, Central Forensic Science Laboratory, Hyderabad
  • Babu S Deloitte Shared Services India LLP, Bengaluru
  • Pathak MB Computer Forensic Unit, Central Forensic Science Laboratory, Hyderabad

DOI:

https://doi.org/10.26438/ijcse/v7i1.386395

Keywords:

SMS Messages, iPhone, Tampering, Authenticity, iOS

Abstract

Mobile Phones, now-a-days have become the primary source of evidence in any type of investigation for providing initial leads for framing the future investigation as well as primary evidence. The retrieval and analysis of SMS messages, including deleted ones from the memory of smart mobiles is one of the main process of mobile phone forensics. With the evolution of technology, criminals can manipulate the SMS database and tamper the messages to prove their virtue and mis-guide the investigation. In the current paper we have discussed the method adopted for proving the authenticity of SMS messages retrieved during the analysis of an iPhone.

References

[1] Practical Investigations of Digital Forensics Tools for Mobile Devices by Maynard Yates II, M.S. Florida Agricultural and Mechanical University Department of Computer and Information Sciences Technical Building A, Room 211 Tallahassee, FL 32307-5100 Maynard1.yates@famu.edu retrieved December 2018.

[2] Barrios, Rita M. and Lehrfeld, Michael R., "Ios Mobile Device Forensics: Initial Analysis" (2011). Annual ADFSL Conference on Digital Forensics, Security and Law. 4. http://commons.erau.edu/adfsl/2011/friday/4 December 2018

[3] Hoene, Thomas & Creutzburg, Reiner. (2011). iPhone forensics: a practical overview with certain commercial software. 10.1117/12.884589. December 2018.

[4] Cheema, Ahmad & Iqbal, Waseem & Ali, Waqas. (2014). An Open Source Toolkit for iOS Filesystem Forensics. 10.1007/978-3-662-44952-3_15. December 2018.

[5] Forensic Analysis on iOS Devices Author: Tim Proffitt, tim@timproffitt.com https://www.sans.org/reading-room/whitepapers/forensics/forensic-analysis-ios-devices-34092 December 2018.

[6] iPhone and iOS Forensics: Investigation, Analysis and Mobile Security for Apple iPhone, iPad and iOS Devices by Andrew HoogKatie Strzempka.

[7] Bader, M., & Baggili, I. (2010). iPhone 3GS forensics: logical analysis using apple itunes backup utility. Small scale digital device forensics journal, 4(1), 1-15 January 2019.

[8] SQLite Wikipedia article. URL https://en.wikipedia.org/wiki/SQLite January 2019.

[9] How to back up your iPhone, iPad, and iPod touch URL https://support.apple.com/en-in/HT203977 January 2019.

[10] Parsing the iPhone SMS Database article. URL https://linuxsleuthing.blogspot.com/2011/02/parsing-iphone-sms-database.html January 2019.

[11] Wikipedia article. URL https://www.theiphonewiki.com/wiki/Messages#msg_group January 2019.

[12] https://smarterforensics.com/2014/09/sqlite-parser-theres-a-new-gui/ January 2019.

[13] https://smarterforensics.com/2017/09/time-is-not-on-our-side-when-it-comes-to-messages-in-ios-11/ visited on 19/01/2019.

[14] https://linuxsleuthing.blogspot.com/2012/10/whos-texting-ios6-smsdb.html visited on 19/01/2019.

[15] https://www.codeproject.com/Articles/833535/Accessing-Backed-Up-iPhone-SMS-Messages visited on 19/01/2019.

[16] https://blog.jverkamp.com/2015/01/27/ios-backups-in-racket-messages/ visited on 19/01/2019.

[17] http://mrdreigon.com/ios6-sms-database-investigation/ visited on 19/01/2019.

[18] https://www.vivekmchawla.com/2013/04/erd-crows-foot-relationship-symbols-quick-reference.html/ visited on 19/01/2019.

[19] Forensic investigations of Apple’s iPhone by Mats Engman, 2013. https://www.diva-portal.org/smash/get/diva2:651693/fulltext01.pdf retreived January 2019.

[20] Smartphone Forensics Analysis: A Case Study by Mubarak Al-Hadadi and Ali AlShidhani International Journal of Computer and Electrical Engineering, Vol. 5, No. 6, December 2013. January 2019.

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Published

2019-01-31
CITATION
DOI: 10.26438/ijcse/v7i1.386395
Published: 2019-01-31

How to Cite

[1]
E. S. P. Chunduru, K. Mangarai, S. Babu, and M. B. Pathak, “Identification of Tampered SMS Messages in iPhone – A Case Study”, Int. J. Comp. Sci. Eng., vol. 7, no. 1, pp. 386–395, Jan. 2019.

Issue

Vol. 7 No. 1 (2019): IJCSE January Edition

Section

Research Article

License

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