Elijah Bouma-Sims (Carnegie Mellon University), Lily Klucinec (Carnegie Mellon University), Mandy Lanyon (Carnegie Mellon University), Julie Downs (Carnegie Mellon University), Lorrie Faith Cranor (Carnegie Mellon University)

Fraudsters often use the promise of free goods as a lure for victims who are convinced to complete online tasks but ultimately receive nothing. Despite much work characterizing these "giveaway scams," no human subjects research has investigated how users interact with them or what factors impact victimization. We conducted a scenario-based experiment with a sample of American teenagers (n = 85) and adult crowd workers (n = 205) in order to investigate how users reason about and interact with giveaway scams advertised in YouTube videos and to determine whether teens are more susceptible than adults. We found that most participants recognized the fraudulent nature of the videos, with only 9.2% believing the scam videos offered legitimate deals. Teenagers did not fall victim to the scams more frequently than adults but reported more experience searching for terms that could lead to victimization. This study is among the first to compare the interactions of adult and teenage users with internet fraud and sheds light on an understudied area of social engineering.

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I know what you MEME! Understanding and Detecting Harmful...

Yong Zhuang (Wuhan University), Keyan Guo (University at Buffalo), Juan Wang (Wuhan University), Yiheng Jing (Wuhan University), Xiaoyang Xu (Wuhan University), Wenzhe Yi (Wuhan University), Mengda Yang (Wuhan University), Bo Zhao (Wuhan University), Hongxin Hu (University at Buffalo)

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Decoupling Permission Management from Cryptography for Privacy-Preserving Systems

Ruben De Smet (Department of Engineering Technology (INDI), Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel), Tom Godden (Department of Engineering Technology (INDI), Vrije Universiteit Brussel), Kris Steenhaut (Department of Engineering Technology (INDI), Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel), An Braeken (Department of Engineering Technology (INDI), Vrije Universiteit Brussel)

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Tweezers: A Framework for Security Event Detection via Event...

Jian Cui (Indiana University), Hanna Kim (KAIST), Eugene Jang (S2W Inc.), Dayeon Yim (S2W Inc.), Kicheol Kim (S2W Inc.), Yongjae Lee (S2W Inc.), Jin-Woo Chung (S2W Inc.), Seungwon Shin (KAIST), Xiaojing Liao (Indiana University)

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A Key-Driven Framework for Identity-Preserving Face Anonymization

Miaomiao Wang (Shanghai University), Guang Hua (Singapore Institute of Technology), Sheng Li (Fudan University), Guorui Feng (Shanghai University)

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