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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Automatic Adversarial Adaption for Stealthy Poisoning Attacks in Federated...

Torsten Krauß (University of Würzburg), Jan König (University of Würzburg), Alexandra Dmitrienko (University of Wuerzburg), Christian Kanzow (University of Würzburg)

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Securing the Satellite Software Stack

Samuel Jero (MIT Lincoln Laboratory), Juliana Furgala (MIT Lincoln Laboratory), Max A Heller (MIT Lincoln Laboratory), Benjamin Nahill (MIT Lincoln Laboratory), Samuel Mergendahl (MIT Lincoln Laboratory), Richard Skowyra (MIT Lincoln Laboratory)

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DEMASQ: Unmasking the ChatGPT Wordsmith

Kavita Kumari (Technical University of Darmstadt, Germany), Alessandro Pegoraro (Technical University of Darmstadt), Hossein Fereidooni (Technische Universität Darmstadt), Ahmad-Reza Sadeghi (Technical University of Darmstadt)

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