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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Secret-Shared Shuffle with Malicious Security

Xiangfu Song (National University of Singapore), Dong Yin (Ant Group), Jianli Bai (The University of Auckland), Changyu Dong (Guangzhou University), Ee-Chien Chang (National University of Singapore)

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Designing and Evaluating a Testbed for the Matter Protocol:...

Ravindra Mangar (Dartmouth College) Jingyu Qian (University of Illinois), Wondimu Zegeye (Morgan State University), Abdulrahman AlRabah, Ben Civjan, Shalni Sundram, Sam Yuan, Carl A. Gunter (University of Illinois), Mounib Khanafer (American University of Kuwait), Kevin Kornegay (Morgan State University), Timothy J. Pierson, David Kotz (Dartmouth College)

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Security Attacks to the Name Management Protocol in Vehicular...

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

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