TY - GEN
T1 - Preliminary Analysis of Privacy Implications Observed in Social-Media Posts Across Shopping Platforms
AU - Sumner, Bethany
AU - Dorai, Gokila
AU - Heslen, John
N1 - Funding Information:
The authors would like to thank Prof. Ibrahim Baggili, Professor, Division of Computer Science and Engineering, Louisiana State University - Center for Computation and Technology for his valuable suggestions and insightful comments on this work, and Seth Barett, Undergraduate Research Assistant, School of Computer & Cyber Sciences for helping in the mobile stalking app analysis. The authors would like to acknowledge National Science Foundation (NSF) (Award number: 2131509) for supporting this project through supplemental funding.
Publisher Copyright:
© 2022 ACM.
PY - 2022/8/23
Y1 - 2022/8/23
N2 - The widespread activity of hash-tagging, especially among the Gen-Z population, and the impact of social commerce on average consumers raise questions about privacy implications and dangers of anonymous cyberstalking. In this work, we examined the privacy implications observed in hash-tag-based social-media posts (of average users and influencers) by following the trails of online shopping platform(s) product listings, consumer reviews, social-commerce policies, and influencer posts. We have conducted a preliminary analysis considering cyberstalking as one of the avenues that an anonymous stalker may use to impact the social-media user negatively. Further, we have conceptualized the trails behind hash-tagging activities in terms of a privacy threat model, the need for practical data analysis tools, and the lack of mitigation strategies at various layers. Mainly, this paper throws light on the need for more robust user privacy policies and the impact on socio-economic-privacy aspects. This paper also demonstrates the need for expanding the scope of digital investigations and DFIR tools beyond just the devices of individuals (including victims, suspects, perpetrators, and cyber-criminals) and to thoroughly prepare the forensic professionals to consider the online presence of individuals in its entirety including anonymous cyberstalking avenues and to raise awareness about the abuse of social networks.
AB - The widespread activity of hash-tagging, especially among the Gen-Z population, and the impact of social commerce on average consumers raise questions about privacy implications and dangers of anonymous cyberstalking. In this work, we examined the privacy implications observed in hash-tag-based social-media posts (of average users and influencers) by following the trails of online shopping platform(s) product listings, consumer reviews, social-commerce policies, and influencer posts. We have conducted a preliminary analysis considering cyberstalking as one of the avenues that an anonymous stalker may use to impact the social-media user negatively. Further, we have conceptualized the trails behind hash-tagging activities in terms of a privacy threat model, the need for practical data analysis tools, and the lack of mitigation strategies at various layers. Mainly, this paper throws light on the need for more robust user privacy policies and the impact on socio-economic-privacy aspects. This paper also demonstrates the need for expanding the scope of digital investigations and DFIR tools beyond just the devices of individuals (including victims, suspects, perpetrators, and cyber-criminals) and to thoroughly prepare the forensic professionals to consider the online presence of individuals in its entirety including anonymous cyberstalking avenues and to raise awareness about the abuse of social networks.
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U2 - 10.1145/3538969.3544457
DO - 10.1145/3538969.3544457
M3 - Conference contribution
AN - SCOPUS:85136963227
T3 - ACM International Conference Proceeding Series
BT - Proceedings of the 17th International Conference on Availability, Reliability and Security, ARES 2022
PB - Association for Computing Machinery
T2 - 17th International Conference on Availability, Reliability and Security, ARES 2022
Y2 - 23 August 2022 through 26 August 2022
ER -