Imani N. S. Munyaka (University of California, San Diego), Daniel A Delgado, Juan Gilbert, Jaime Ruiz, Patrick Traynor (University of Florida)

Telephone carriers and third-party developers have created technical solutions to detect and notify consumers of spam calls. The goal of this technology is to help users make decisions about incoming calls and reduce the negative effects of spam calls on finances and daily life. Although useful, this technology has varying accuracy due to technical limitations. In this study, we conduct design interviews, a call response diary study, and an MTurk survey (N=143) to explore the relationship between warning accuracy and callee decision-making for incoming calls. Our results suggest that previous call experience can lead to incomplete mental models of how Caller ID works. Additionally, we find that false alarms and missed detection do not impact call response but can influence user expectations of the call. Since adversaries can use mismatched expectations to their advantage, we recommend using warning design characteristics that align with user expectations under detection accuracy constraints.

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Sharika Kumar (The Ohio State University), Imtiaz Karim, Elisa Bertino (Purdue University), Anish Arora (Ohio State University)

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A Two-Layer Blockchain Sharding Protocol Leveraging Safety and Liveness...

Yibin Xu (University of Copenhagen), Jingyi Zheng (University of Copenhagen), Boris Düdder (University of Copenhagen), Tijs Slaats (University of Copenhagen), Yongluan Zhou (University of Copenhagen)

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Stop to Unlock: Improving the Security of Android Unlock...

Alexander Suchan (SBA Research); Emanuel von Zezschwitz (Usable Security Methods Group, University of Bonn, Bonn, Germany); Katharina Krombholz (CISPA Helmholtz Center for Information Security)

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Benchmarking transferable adversarial attacks

Zhibo Jin (The University of Sydney), Jiayu Zhang (Suzhou Yierqi), Zhiyu Zhu, Huaming Chen (The University of Sydney)

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