Shujaat Mirza, Christina Pöpper (New York University)

Online social networks accumulate unprecedented amounts of data that continue to exist on user profiles long after the time of posting. Given that these platforms primarily provide a venue for people to connect and foster online friendships, the influence and the risks associated with longitudinal data may impact users and their reasons for using these platforms. To better understand these issues, we conducted two user studies of Facebook users analyzing the history of past postings w. r. t. to their perceived relevance, longitudinal exposure, and impact on the users’ befriending behavior. The studies give us a cross-cultural undergraduate student sample (n=89, campus study) and a Mechanical Turk sample of two cultural backgrounds from the US and India (n=209, MTurk study). Our findings reveal that a sizable group of participants consider their past postings irrelevant and, at times, embarrassing. However, participants’ awareness and usage of longitudinal privacy control features (e. g., Limit Past Posts) are limited, resulting in overexposure of their past postings and personal information. Importantly, we find support that these overexposed, yet irrelevant, past postings (of both participants and friend requesters) have the potential to influence users’ fundamental behavior on the platform: friend network expansion. Participants greatly valued friend requester’s past postings, particularly in the absence of prior personal interactions, but are influenced by their backgrounds (American users rely significantly more than their Indian counterparts on the requesters’ past postings for their befriending behavior). We close by discussing the implications of our findings on the future of longitudinal privacy controls.

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LaKSA: A Probabilistic Proof-of-Stake Protocol

Daniel Reijsbergen (Singapore University of Technology and Design), Pawel Szalachowski (Singapore University of Technology and Design), Junming Ke (University of Tartu), Zengpeng Li (Singapore University of Technology and Design), Jianying Zhou (Singapore University of Technology and Design)

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Towards Understanding and Detecting Cyberbullying in Real-world Images

Nishant Vishwamitra (University at Buffalo), Hongxin Hu (University at Buffalo), Feng Luo (Clemson University), Long Cheng (Clemson University)

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Work in Progress: Programmable In-Network Obfuscation of DNS Traffic

Liang Wang, Hyojoon Kim, Prateek Mittal, Jennifer Rexford (Princeton University)

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PyPANDA: Taming the PANDAmonium of Whole System Dynamic Analysis

Luke Craig, Tim Leek (MIT Lincoln Laboratory), Andrew Fasano, Tiemoko Ballo (MIT Lincoln Laboratory, Northeastern University), Brendan Dolan-Gavitt (New York University), William Robertson (Northeastern University)

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