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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Large Language Model guided Protocol Fuzzing

Ruijie Meng (National University of Singapore, Singapore), Martin Mirchev (National University of Singapore), Marcel Böhme (MPI-SP, Germany and Monash University, Australia), Abhik Roychoudhury (National University of Singapore)

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Exploring the Influence of Prompts in LLMs for Security-Related...

Weiheng Bai (University of Minnesota), Qiushi Wu (IBM Research), Kefu Wu, Kangjie Lu (University of Minnesota)

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Sneaky Spikes: Uncovering Stealthy Backdoor Attacks in Spiking Neural...

Gorka Abad (Radboud University & Ikerlan Technology Research Centre), Oguzhan Ersoy (Radboud University), Stjepan Picek (Radboud University & Delft University of Technology), Aitor Urbieta (Ikerlan Technology Research Centre, Basque Research and Technology Alliance (BRTA))

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SSL-WM: A Black-Box Watermarking Approach for Encoders Pre-trained by...

Peizhuo Lv (Institute of Information Engineering, Chinese Academy of Sciences, China; School of Cyber Security, University of Chinese Academy of Sciences, China), Pan Li (Institute of Information Engineering, Chinese Academy of Sciences, China; School of Cyber Security, University of Chinese Academy of Sciences, China), Shenchen Zhu (Institute of Information Engineering, Chinese Academy of Sciences, China;…

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