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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Clement Fung (Carnegie Mellon University), Eric Zeng (Carnegie Mellon University), Lujo Bauer (Carnegie Mellon University)

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Shiqing Luo (George Mason University), Anh Nguyen (George Mason University), Hafsa Farooq (Georgia State University), Kun Sun (George Mason University), Zhisheng Yan (George Mason University)

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Zhengchuan Liang (UC Riverside), Xiaochen Zou (UC Riverside), Chengyu Song (UC Riverside), Zhiyun Qian (UC Riverside)

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Kosei Akama (Keio University), Yoshimichi Nakatsuka (ETH Zurich), Masaaki Sato (Tokai University), Keisuke Uehara (Keio University)

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