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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Dev Vikesh Doshi (California State University San Marcos), Mehjabeen Tasnim (California State University San Marcos), Fernando Landeros (California State University San Marcos), Chinthagumpala Muni Venkatesh (California State University San Marcos), Daniel Timko (Emerging Threats Lab / Smishtank.com), Muhammad Lutfor Rahman (California State University San Marcos)

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CrowdGuard: Federated Backdoor Detection in Federated Learning

Phillip Rieger (Technical University of Darmstadt), Torsten Krauß (University of Würzburg), Markus Miettinen (Technical University of Darmstadt), Alexandra Dmitrienko (University of Würzburg), Ahmad-Reza Sadeghi (Technical University of Darmstadt)

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Maginot Line: Assessing a New Cross-app Threat to PII-as-Factor...

Fannv He (National Computer Network Intrusion Protection Center, University of Chinese Academy of Sciences, China), Yan Jia (DISSec, College of Cyber Science, Nankai University, China), Jiayu Zhao (National Computer Network Intrusion Protection Center, University of Chinese Academy of Sciences, China), Yue Fang (National Computer Network Intrusion Protection Center, University of Chinese Academy of Sciences, China),…

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