Demo Data from VLDB 2026 / reviewers in the wild / expert
Ge Zhong
dblp:11/1269
· DBLP profile ↗
2ranked-venue papers
2as first author
0since 2021 · last 2009
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 1 · 1 first-authorHuman-computer interaction and ubiquitous computing · 1 · 1 first-author
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.
| Network and information security
1 paper |
Privacy and data protection · 91% Cryptographic protocols and secure computation · 9% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Privacy and data protection › anonymization
k-anonymity |
0.1 | 1 | 2009 | A Distributed k-Anonymity Protocol for Location Privacy · PerCom 2009 |
Privacy and data protection › location privacy
location cloaking |
0.1 | 1 | 2009 | A Distributed k-Anonymity Protocol for Location Privacy · PerCom 2009 |
Privacy and data protection
location privacy |
0.1 | 1 | 2009 | A Distributed k-Anonymity Protocol for Location Privacy · PerCom 2009 |
Cryptographic protocols and secure computation
secure multiparty computation |
0.0 | 1 | 2009 | A Distributed k-Anonymity Protocol for Location Privacy · PerCom 2009 |
Methods — techniques the papers use, named apart from their topics
cryptography · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2009 | A Distributed k-Anonymity Protocol for Location PrivacyabstractTo benefit from a location-based service, a person must reveal her location to the service. However, knowing the person's location might allow the service to re-identify the person. Location privacy based on k-anonymity addresses this threat by cloaking the person's location such that there are at least k - 1 other people within the cloaked area and by revealing only the cloaked area to a location-based service. Previous research has explored two ways of cloaking: First, have a central server that knows everybody's location determine the cloaked area. However, this server needs to be trusted by all users and is a single point of failure. Second, have users jointly determine the cloaked area. However, this approach requires that all users trust each other, which will likely not hold in practice. We propose a distributed approach that does not have these drawbacks. Our approach assumes that there are multiple servers, each deployed by a different organization. A user's location is known to only one of the servers (e.g., to her cellphone provider), so there is no single entity that knows everybody's location. With the help of cryptography, the servers and a user jointly determine whether the k-anonymity property holds for the user's area, without the servers learning any additional information, not even whether the property holds. A user learns whether the k-anonymity property is satisfied and no other information. The evaluation of our sample implementation shows that our distributed k-anonymity protocol is sufficiently fast to be practical. Moreover, our protocol integrates well with existing infrastructures for location-based services, as opposed to the previous research. Ge Zhong, Urs Hengartner |
PerCom | 1 |
| 2007 | Louis, Lester and Pierre: Three Protocols for Location Privacy
Ge Zhong, Ian Goldberg 0001, Urs Hengartner |
Privacy Enhancing Technologies | 1 |