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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Towards Precise Reporting of Cryptographic Misuses

Yikang Chen (The Chinese University of Hong Kong), Yibo Liu (Arizona State University), Ka Lok Wu (The Chinese University of Hong Kong), Duc V Le (Visa Research), Sze Yiu Chau (The Chinese University of Hong Kong)

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Strengthening Privacy in Robust Federated Learning through Secure Aggregation

Tianyue Chu, Devriş İşler (IMDEA Networks Institute & Universidad Carlos III de Madrid), Nikolaos Laoutaris (IMDEA Networks Institute)

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Cybercrime Investigators are Users Too! Understanding the Socio-Technical Challenges...

Mariam Nouh (University of Oxford); Jason R. C. Nurse (University of Kent); Helena Webb, Michael Goldsmith (University of Oxford)

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NODLINK: An Online System for Fine-Grained APT Attack Detection...

Shaofei Li (Key Laboratory of High-Confidence Software Technologies (MOE), School of Computer Science, Peking University), Feng Dong (Huazhong University of Science and Technology), Xusheng Xiao (Arizona State University), Haoyu Wang (Huazhong University of Science and Technology), Fei Shao (Case Western Reserve University), Jiedong Chen (Sangfor Technologies Inc.), Yao Guo (Key Laboratory of High-Confidence Software Technologies…

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