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Although mobile devices benefit users in their daily lives in numerous ways, they also raise several privacy concerns. For instance, they can reveal sensitive information that can be inferred from location data. This location data is shared…

计算机与社会 · 计算机科学 2025-04-25 Antoine Boutet , Victor Morel

Among populations with limited literacy in emerging digital markets, the adoption of mobile phones, combined with comprehension barriers and poor cybersecurity hygiene, has created hidden privacy risks. This paper examines how informed…

It has been shown in the field of Author Profiling that texts may inadvertently reveal sensitive information about their authors, such as gender or age. This raises important privacy concerns that have been extensively addressed in the…

计算与语言 · 计算机科学 2024-12-18 Martin Borquez , Mikaela Keller , Michael Perrot , Damien Sileo

As artificial intelligence (AI) becomes increasingly integrated into education, understanding how students perceive its risks is essential for supporting responsible and effective adoption. This research aimed to examine the relationships…

计算机与社会 · 计算机科学 2025-12-05 Ville Heilala , Pieta Sikström , Mika Setälä , Tommi Kärkkäinen

Privacy regulations such as the CCPA and GDPR grant individuals rights over their personal data, yet it remains challenging for most users to exercise them in practice due to vague policy interpretation and unapproachable settings on web…

人机交互 · 计算机科学 2026-05-05 Qi Sun , Ziyang Li , Yinzhi Cao , Yaxing Yao

Split Learning (SL) is a collaborative learning approach that improves privacy by keeping data on the client-side while sharing only the intermediate output with a server. However, the distributed nature of SL introduces new security…

机器学习 · 计算机科学 2025-08-15 Tanveer Khan , Antonis Michalas

Federated learning is emerging as a machine learning technique that trains a model across multiple decentralized parties. It is renowned for preserving privacy as the data never leaves the computational devices, and recent approaches…

机器学习 · 计算机科学 2021-06-25 Yuchen Li , Yifan Bao , Liyao Xiang , Junhan Liu , Cen Chen , Li Wang , Xinbing Wang

While recent years have witnessed the advancement in big data and Artificial Intelligence (AI), it is of much importance to safeguard data privacy and security. As an innovative approach, Federated Learning (FL) addresses these concerns by…

密码学与安全 · 计算机科学 2024-11-05 Chunlu Chen , Ji Liu , Haowen Tan , Xingjian Li , Kevin I-Kai Wang , Peng Li , Kouichi Sakurai , Dejing Dou

AI-driven applications have become woven into students' academic and creative workflows, influencing how they learn, write, and produce ideas. Gaining a nuanced understanding of these usage patterns is essential, yet conventional survey and…

人机交互 · 计算机科学 2025-10-14 Donghan Hu , Rameen Mahmood , Annabelle David , Danny Yuxing Huang

With the spread of high-speed Internet and portable smart devices, the way people access and consume information has drastically changed. However, this presents many challenges, including information overload, personal data leakage, and…

Privacy Policies are the legal documents that describe the practices that an organization or company has adopted in the handling of the personal data of its users. But as policies are a legal document, they are often written in extensive…

密码学与安全 · 计算机科学 2021-02-25 Ayesha Qamar , Tehreem Javed , Mirza Omer Beg

Privacy concerns significantly impact AI adoption, yet little is known about how information environments shape user responses to data leak threats. We conducted a 2 x 3 between-subjects experiment (N=610) examining how risk versus…

人机交互 · 计算机科学 2026-03-11 Alexander Erlei , Tahir Abbas , Kilian Bizer , Ujwal Gadiraju

Ensuring the privacy of sensitive data used to train modern machine learning models is of paramount importance in many areas of practice. One recent popular approach to study these concerns is using the differential privacy via a…

密码学与安全 · 计算机科学 2020-07-29 Lichao Sun , Ji Wang , Philip S. Yu , Lifang He

The problem of private information "leakage" (inadvertently or by malicious design) from the myriad large centralized searchable data repositories drives the need for an analytical framework that quantifies unequivocally how safe private…

信息论 · 计算机科学 2010-02-09 Lalitha Sankar , S. Raj Rajagopalan , H. Vincent Poor

The research aims to explore how individuals perceive and interact with data protection practices in an era of increasing reliance on technology and the widespread availability of personal data. The study employs a game theoretical approach…

人机交互 · 计算机科学 2024-04-24 Mike Nkongolo , Jahrad Sewnath

Phishing attacks have become an increasing threat to online users. Recent research has begun to focus on the factors that cause people to respond to them. Our study examines the correlation between the Big Five personality traits and email…

人机交互 · 计算机科学 2013-02-11 Tzipora Halevi , Jim Lewis , Nasir Memon

We present an observational study on the relationship between demographic factors and phishing susceptibility at the University of Maryland, Baltimore County (UMBC). In spring 2018, we delivered phishing attacks to 450 randomly-selected…

密码学与安全 · 计算机科学 2018-11-16 Alejandra Diaz , Alan T. Sherman , Anupam Joshi

Logs are one of the most fundamental resources to any security professional. It is widely recognized by the government and industry that it is both beneficial and desirable to share logs for the purpose of security research. However, the…

密码学与安全 · 计算机科学 2007-05-23 Adam J. Slagell , William Yurcik

Privacy policies are intended to support informed consent, yet users rarely read them fully. This study examines how common privacy policy interface structures influence attention allocation, reading behavior, and perceived experience.…

人机交互 · 计算机科学 2026-03-17 Wei Xiao , Mengke Wu , Yeeun Jo

Recently, inference privacy has attracted increasing attention. The inference privacy concern arises most notably in the widely deployed edge-cloud video analytics systems, where the cloud needs the videos captured from the edge. The video…

密码学与安全 · 计算机科学 2023-05-26 Siping Shi , Bihai Zhang , Dan Wang