Demo Data from EDBT 2026 / reviewers in the wild / expert
Parth Kirankumar Thakkar
dblp:319/3589
· DBLP profile ↗
2ranked-venue papers
1as first author
2since 2021 · last 2024
0009-0007-3079-0524ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 2 · 1 first-author · 2 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Human-computer interaction and pervasive computing
1 paper |
Ubiquitous computing and smart environments · 100% | |
| Network and information security
1 paper |
Privacy and data protection · 100% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Ubiquitous computing and smart environments › smart home
smart home privacy |
0.6 | 1 | 2022 | "It would probably turn into a social faux-pas": Users' and Bystanders' Preferences of Privacy Awareness Mechanisms in Smart Homes · CHI 2022 |
Methods — techniques the papers use, named apart from their topics
survey study · 1.1design dimensions · 1.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Users' Perceptions of Online Child Abuse Detection MechanismsabstractChild sexual exploitation and abuse (CSEA) online has become a major safety issue for children to access the Internet. To combat CSEA, electronics services providers (ESP) have implemented various mechanisms to detect child sexual abuse materials (CSAM). However, these mechanisms, despite their capability to prevent the mass distribution of CSAM online, may raise significant privacy concerns among general users. In this paper, we conducted a semi-structured interview study with 23 participants to understand their privacy perceptions of two types of online CSAM detection mechanisms. Our results suggested that users were concerned about the transparency of the detection process, inappropriate access to users' data, and unclear boundaries of such mechanisms. Our results also highlight that, even though the majority of participants choose to sacrifice their privacy for societal benefits, they still have privacy concerns that need to be addressed. We discuss the design and policy implications for ESP to improve users' awareness of the data practices of these mechanisms, alleviate users' privacy concerns, and increase societal benefits. Elmira Deldari, Parth Kirankumar Thakkar, Yaxing Yao |
Proc. ACM Hum. Comput. Interact. | 2 |
| 2022 | "It would probably turn into a social faux-pas": Users' and Bystanders' Preferences of Privacy Awareness Mechanisms in Smart HomesabstractThe opaque data practices in smart home devices have raised significant privacy concerns for smart home users and bystanders. One way to learn about the data practices is through privacy-related notifications. However, how to deliver these notifications to users and bystanders and increase their awareness of data practices is not clear. We surveyed 136 users and 123 bystanders to understand their preferences of receiving privacy-related notifications in smart homes. We further collected their responses to four mechanisms that improve privacy awareness (e.g., Data Dashboard) as well as their selections of mechanisms in four different scenarios (e.g., friend visiting). Our results showed the pros and cons of each privacy awareness mechanism, e.g., Data Dashboard can help reduce bystanders’ dependence on users. We also found some unique benefits of each mechanism (e.g., Ambient Light could provide unobtrusive privacy awareness). We summarized four key design dimensions for future privacy awareness mechanisms design. Parth Kirankumar Thakkar, Shijing He, Danny Yuxing Huang, Yaxing Yao |
CHI | 1 |