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.

View More Papers

WIP: Body Posture Analysis as an Objective Measurement for...

Cherin Lim, Tianhao Xu, Prashanth Rajivan (University of Washington)

Read More

ReqsMiner: Automated Discovery of CDN Forwarding Request Inconsistencies and...

Linkai Zheng (Tsinghua University), Xiang Li (Tsinghua University), Chuhan Wang (Tsinghua University), Run Guo (Tsinghua University), Haixin Duan (Tsinghua University; Quancheng Laboratory), Jianjun Chen (Tsinghua University; Zhongguancun Laboratory), Chao Zhang (Tsinghua University; Zhongguancun Laboratory), Kaiwen Shen (Tsinghua University)

Read More

SyzBridge: Bridging the Gap in Exploitability Assessment of Linux...

Xiaochen Zou (UC Riverside), Yu Hao (UC Riverside), Zheng Zhang (UC RIverside), Juefei Pu (UC RIverside), Weiteng Chen (Microsoft Research, Redmond), Zhiyun Qian (UC Riverside)

Read More

Understanding and Analyzing Appraisal Systems in the Underground Marketplaces

Zhengyi Li (Indiana University Bloomington), Xiaojing Liao (Indiana University Bloomington)

Read More