helpResearch questionPrivacy-Enhancing Technologies
How do anonymous online discussion platforms affect employees' willingness to discuss cybersecurity topics?Direction: Privacy, Security, and Identity
Privacy-Enhancing Technologies
Stats are based on currently indexed question data; missing sources remain visible.
64
items
16
sources
2025
latest
All questions
64 items
helpResearch questionPrivacy-Enhancing Technologies
How do anonymity mechanisms improve employee acceptance of and feedback on cybersecurity policies?helpResearch questionPrivacy-Enhancing Technologies
What role do anonymous discussion platforms play in collecting and improving cybersecurity culture?lightbulbPractical problemPrivacy-Enhancing Technologies
Employees find cybersecurity measures burdensome and fear punishment for raising cybersecurity concerns.helpResearch questionPrivacy-Enhancing Technologies
How well do ordinary users understand transfer risks in smart contracts (e.g., USDT contracts)?helpResearch questionPrivacy-Enhancing Technologies
Which transfer risks (e.g., user blacklisting, contract upgradability) are most common in ERC-20 smart contracts?helpResearch questionPrivacy-Enhancing Technologies
Can automated detection algorithms effectively identify transfer risks in smart contracts?lightbulbPractical problemPrivacy-Enhancing Technologies
Ordinary users struggle to understand risks in smart contracts, potentially causing financial losses.helpResearch questionPrivacy-Enhancing Technologies
How does VeraCrypt's user interface affect non-technical users' efficiency and success in completing device encryption?helpResearch questionPrivacy-Enhancing Technologies
Which specific design improvements can effectively simplify VeraCrypt workflows while maintaining security?helpResearch questionPrivacy-Enhancing Technologies
How can academic usability research findings be more effectively translated into open-source software practice?lightbulbPractical problemPrivacy-Enhancing Technologies
Non-technical users struggle to complete complex VeraCrypt device encryption tasks.helpResearch questionPrivacy-Enhancing Technologies
How do cryptocurrency users choose different wallet types (e.g., hardware, software, custodial, and non-custodial) to balance security and convenience?helpResearch questionPrivacy-Enhancing Technologies
What security strategies do users adopt when using multiple wallets to reduce security risks?helpResearch questionPrivacy-Enhancing Technologies
How does users' understanding of wallets' social security features (e.g., social recovery) affect their selection and usage behavior?lightbulbPractical problemPrivacy-Enhancing Technologies
Cryptocurrency users face diverse choices and complexity when selecting wallets and securing assets.helpResearch questionPrivacy-Enhancing Technologies
How should the core technical capabilities, scan content, and user interaction of client-side scanning (CSS) be defined?helpResearch questionPrivacy-Enhancing Technologies
What do experts expect from CSS technology, and what challenges does it face in practice?helpResearch questionPrivacy-Enhancing Technologies
What potential privacy and societal impacts might CSS technology have?lightbulbPractical problemPrivacy-Enhancing Technologies
It is difficult to effectively prevent child sexual abuse material distribution in the face of end-to-end encryption.helpResearch questionPrivacy-Enhancing Technologies
How can edge-case backdoor attacks in federated learning (where attackers inject tasks via anomalous data points) be detected and mitigated?helpResearch questionPrivacy-Enhancing Technologies
How does the ARMOR framework detect edge-case backdoor attacks without access to real data?helpResearch questionPrivacy-Enhancing Technologies
Can ARMOR improve the security and robustness of federated learning without compromising privacy protection?lightbulbPractical problemPrivacy-Enhancing Technologies
Federated learning systems are vulnerable to privacy leakage and edge-case backdoor attacks.helpResearch questionPrivacy-Enhancing Technologies
How can privacy be protected while enabling efficient collaborative AI model building when sharing sensitive data?UbiComp '23Sandbox AI: We Don’t Trust Each Other but Want to Create New Value Efficiently Through Collaboration Using Sensitive Data
helpResearch questionPrivacy-Enhancing Technologies
How can sandbox AI environments implement privacy-preserving annotation and model retraining workflows?UbiComp '23Sandbox AI: We Don’t Trust Each Other but Want to Create New Value Efficiently Through Collaboration Using Sensitive Data
helpResearch questionPrivacy-Enhancing Technologies
Can differential privacy-based data generation and active learning improve annotation efficiency and reduce privacy leakage risk?UbiComp '23Sandbox AI: We Don’t Trust Each Other but Want to Create New Value Efficiently Through Collaboration Using Sensitive Data
lightbulbPractical problemPrivacy-Enhancing Technologies
Sensitive data holders struggle to collaborate with others to build AI models under privacy constraints.UbiComp '23Sandbox AI: We Don’t Trust Each Other but Want to Create New Value Efficiently Through Collaboration Using Sensitive Data
helpResearch questionPrivacy-Enhancing Technologies
How can online safe spaces support women and gender minorities in learning to discuss health taboo topics?helpResearch questionPrivacy-Enhancing Technologies
How can group learning and safe spaces be combined to promote breaking health-related social taboos?helpResearch questionPrivacy-Enhancing Technologies
How does partial anonymity affect learning motivation and outcomes in online community discussions of sensitive topics?lightbulbPractical problemPrivacy-Enhancing Technologies
Women and gender minorities lack safe environments to openly discuss health taboo topics.helpResearch questionPrivacy-Enhancing Technologies
How does differential privacy affect each stage of data science workflows, especially for non-expert users?helpResearch questionPrivacy-Enhancing Technologies
How do differential privacy tools meet different needs of data managers and analysts in data sharing and privacy protection?helpResearch questionPrivacy-Enhancing Technologies
How can differential privacy tools be improved to better support exploratory analysis and reproducibility of scientific research in data science?lightbulbPractical problemPrivacy-Enhancing Technologies
Users struggle to obtain sufficiently open data while protecting privacy in data analysis.helpResearch questionPrivacy-Enhancing Technologies
How can statistical and system heterogeneity be addressed in multi-device environments to improve federated learning performance?UbiComp '22FLAME: Federated Learning across Multi-device Environments
helpResearch questionPrivacy-Enhancing Technologies
How can inference consistency be improved in multi-device environments while preserving privacy?UbiComp '22FLAME: Federated Learning across Multi-device Environments
helpResearch questionPrivacy-Enhancing Technologies
How can device selection strategies be designed to balance model accuracy, energy efficiency, and time efficiency?UbiComp '22FLAME: Federated Learning across Multi-device Environments
lightbulbPractical problemPrivacy-Enhancing Technologies
Users owning multiple devices create data heterogeneity, making federated learning difficult to ensure efficiency and effectiveness.UbiComp '22FLAME: Federated Learning across Multi-device Environments
helpResearch questionPrivacy-Enhancing Technologies
How can differential privacy and federated learning be used for real-time network anomaly detection in the Internet of Healthcare Things (IoHT) while protecting patient privacy?UbiComp '21Differentially Private Federated Learning for Anomaly Detection in eHealth Networks
helpResearch questionPrivacy-Enhancing Technologies
How does differential privacy affect the accuracy of anomaly detection models in healthcare environments?UbiComp '21Differentially Private Federated Learning for Anomaly Detection in eHealth Networks
helpResearch questionPrivacy-Enhancing Technologies
How can natural anomalies (e.g., health deterioration) be distinguished from malicious anomalies (e.g., attacks) in healthcare data?UbiComp '21Differentially Private Federated Learning for Anomaly Detection in eHealth Networks
lightbulbPractical problemPrivacy-Enhancing Technologies
Healthcare IoT devices are vulnerable to data breaches and malicious attacks that endanger patients' lives.UbiComp '21Differentially Private Federated Learning for Anomaly Detection in eHealth Networks
helpResearch questionPrivacy-Enhancing Technologies
What are the main UX problems with mobile cryptocurrency wallets?helpResearch questionPrivacy-Enhancing Technologies
What are the root causes of these UX problems?helpResearch questionPrivacy-Enhancing Technologies
How can mobile cryptocurrency wallet design be improved to reduce user errors and increase trust?lightbulbPractical problemPrivacy-Enhancing Technologies
Ordinary users easily make mistakes when using cryptocurrency wallets, which can cause irreversible financial loss.helpResearch questionPrivacy-Enhancing Technologies
How can social media features be designed to meet the psychological and social development needs of adolescents aged 10-14?helpResearch questionPrivacy-Enhancing Technologies
How do designs such as anonymity and visual feedback support adolescents' identity exploration and self-expression?Related papers
CHI 2025
Using Anonymous Discussion Platforms to Support Open Conversations about Cybersecurity in Organisations
Eve Jenkins, Dinislam Abdulgalimov, Pamela Briggs
CHI 2025
Understanding End-User Perception of Transfer Risks in Smart Contracts
Yustynn Panicker, Ezekiel Soremekun, Sudipta Chattopadhyay
CHI 2025
Bridging the Gap Between Usable Security Research and Open-Source Practice — Lessons From a Long-Term Engagement With VeraCrypt
Felix Reichmann, Annalina Buckmann, Konstantin Fischer
CHI 2024
"Don't put all your eggs in one basket": How Cryptocurrency Users Choose and Secure Their Wallets
Yaman Yu, Tanusree Sharma, Sauvik Das
CHI 2024
Mental Models, Expectations and Implications of Client-Side Scanning: An Interview Study with Experts
Divyanshu Bhardwaj, Carolyn Guthoff, Adrian Dabrowski
UbiComp 2023
Robust Federated Learning for Ubiquitous Computing through Mitigation of Edge-Case Backdoor Attacks
Fatima Elhattab, Sara Bouchenak, Rania Talbi
CHI 2023
Learning to Navigate Health Taboos through Online Safe Spaces
Hannah Tam, Karthik S Bhat, Priyanka Mohindra
CHI 2023
Don't Look at the Data! How Differential Privacy Reconfigures the Practices of Data Science
Jayshree Sarathy, Sophia Song, Audrey Haque
CHI 2021
The U in Crypto Stands for Usable: An Empirical Study of User Experience with Mobile Cryptocurrency Wallets
Artemij Voskobojnikov, Oliver Wiese, Masoud Mehrabi Koushki
CHI 2021
Prototyping for Social Wellbeing with Early Social Media Users
Linda Charmaraman, Catherine Grevet Delcourt
CHI 2021
Distress Disclosure across Social Media Platforms during the COVID-19 Pandemic: Untangling the Effects of Platforms, Affordances, and Audiences
Renwen Zhang, Natalya N. Bazarova, Madhu Reddy
CHI 2021
Exploring Design and Governance Challenges in the Development of Privacy-Preserving Computation
Nitin Agrawal, Reuben Binns, Max Van Kleek
Adjacent categories
Privacy, Security, and Identity
Smart Home and IoT Privacy, Security, and Developer Support
117 items
Privacy, Security, and Identity
Vulnerable Group Privacy
115 items
Privacy, Security, and Identity
Smart Device, Location Tracking, and Contextual Surveillance Privacy
111 items
Privacy, Security, and Identity
Cyber Threats and Protection
104 items
Privacy, Security, and Identity
Security and Privacy Risk Factors and Impact Assessment
97 items
Privacy, Security, and Identity
Social Platform Safety, Content Governance, and Online Harm
95 items
Privacy, Security, and Identity
Surveillance and Sensing Privacy
88 items
Privacy, Security, and Identity
Privacy and Digital Security for Marginalized Identity Groups
77 items