Abstract
Twitter is a popular online social media network platform that has millions of users worldwide. Twitter activities have grown in popularity among different age groups. Various Twitter activities such as instant chats, wall comments and following others could create a number of footprints in different locations of the device. The footprints may be misused, which would compromise privacy and security of the users. In order to protect their personal data, it is important that the users to take every precautions when using the social media. The question is what measures are available for the users to take. In this research, through memory forensics we assess Twitter user’s privacy and security when is accessed via web browser on Windows 10 machine. We carry out a set of memory forensics analysis experiments in different modes. In each mode, we evaluate the retrieved forensics artifacts. Based on the results of our experiment, we recommend the best approach for the users.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Chang, M.S., Chang, C.Y.: Twitter social network forensics on Windows 10. IJISET – Int. J. Innov. Sci. Eng. Technol. 3(9), 55–60 (2016)
Ali, S., Islam, N., Rauf, A, Din, I.U., Guizani, M., Rodrigues, J.P.C.: Privacy and security issues in online social networks. Future Internet 10(12), 1–12 (2018)
Krishnamurthy, B.: Privacy and Social Media Networks: Can colorless green ideas sleep furiously: http://research.microsoft.com/pubs/64346/dwork.pdf
Buccafurri, F., Lax, G., Nicolazzo, S., Nocera, A.: Comparing Twitter and Facebook user behavior: privacy and other aspects. Comput. Hum. Behav. 52, 87–95 (2015)
Umair, A., Nanda, P., He, X.: Online social network information forensics: a survey on use of various tools and determining how cautious Facebook users are? IEEE Trustcom/BigDataSE/ICESS, pp. 1139–1144 (2017)
Fire, M, Kagan, D., Elishar, A., Elovici, Y.: Social Privacy Protector - Protecting Users’ Privacy in Social Networks (2012)
Chang, M.S.: Digital forensic investigation of facebook on Windows 10. Int. J. Innov. Sci. Eng. Technol. 3(9), 1–7 (2016)
Chang, M.S., Yen, C.P.: Twitter social network forensics on Windows 10. Int. J. Innov. Sci. Eng. Technol. 3(9), 55–60 (2016)
Majeed, A., Saleem, S.: Forensics analysis of social media apps in Windows 10. NUST J. Eng. Sci. 10(1), 37–45 (2017)
Singh, A., Sharma, P., Sharma, S.: A novel memory forensics technique for Windows 10. J. Network Inf. Secur. 4(2), 1–10 (2016)
Yang, T.Y., Dehghantanha, A., Choo, K.K., Muda, Z.: Windows instant messaging app forensics: Facebook and Skype as case studies. PLoS ONE 11(3), 1–29 (2016)
Yusoff, M.N., Dehghantanha, A., Mahmod, R.: Forensic Investigation of Social Media and Instant Messaging Services in Firefox OS: Facebook, Twitter, Google+, Telegram, OpenWapp, and Line as Case Studies. In book: Contemporary Digital Forensic Investigations of Cloud and Mobile Applications, Elsevier, pp. 41–62 (2016)
Bachler, M.: An Analysis of Smartphones Using Open Source Tools versus the Proprietary Tool Cellebrite UFED Touch. https://www.marshall.edu/forensics/files/BACHLER_MARCIE_Research-Paper_Aug-5.pdf
Venkateswara, R.V., Chakravarthy, A.S.N.: Survey on android forensic tools and methodologies. Int. J. Comput. Appl. 154(8), 17–21 (2016)
Junaid, M., Tewari, J.P., Kumar, R., Vaish, A.: Proposed methodology for smart phone forensic tool. Asian J. Comput. Sci. Technol. 4(2), 1–5 (2015)
VMware Workstation Player 15. https://www.vmware.com
Redline. https://www.fireeye.com/services/freeware/redline.html
Garfinkel, S.L.: Digital media triage with bulk data analysis and bulk_extractor. Comput. Secur. 32, 56–72 (2013)
Magnet RAM Capture. Acquiring Memory with Magnet RAM Capture. https://www.magnetforensics.com/blog/acquiring-memory-with-magnet-ram-capture/
Twitter privacy policy. https://twitter.com/en/privacy
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Ghafarian, A., Fiallo, D. (2021). An Analysis of Twitter Security and Privacy Using Memory Forensics. In: Arai, K. (eds) Intelligent Computing. Lecture Notes in Networks and Systems, vol 285. Springer, Cham. https://doi.org/10.1007/978-3-030-80129-8_51
Download citation
DOI: https://doi.org/10.1007/978-3-030-80129-8_51
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-80128-1
Online ISBN: 978-3-030-80129-8
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)