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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Certificate Transparency Revisited: The Public Inspections on Third-party Monitors

Aozhuo Sun (Institute of Information Engineering, Chinese Academy of Sciences), Jingqiang Lin (School of Cyber Science and Technology, University of Science and Technology of China), Wei Wang (Institute of Information Engineering, Chinese Academy of Sciences), Zeyan Liu (The University of Kansas), Bingyu Li (School of Cyber Science and Technology, Beihang University), Shushang Wen (School of…

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Resilient Routing for Low Earth Orbit Mega-Constellation Networks

Alexander Kedrowitsch (Virginia Tech), Jonathan Black (Virginia Tech) Daphne Yao (Virginia Tech)

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Towards Real-time Voice Interaction Data Collection Monitoring and Ambient...

Tu Le (University of California, Irvine), Zixin Wang (Zhejiang University), Danny Yuxing Huang (New York University), Yaxing Yao (Virginia Tech), Yuan Tian (University of California, Los Angeles)

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Securing Automotive Software Supply Chains (Long)

Marina Moore, Aditya Sirish A Yelgundhalli (New York University), Justin Cappos (NYU)

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