Privacy-Preserving Technologies in Data
Privacy-Preserving Technologies in Data is a research topic within Artificial Intelligence. Science Explorer counts 35k research works in it since 1953. 29.8% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on privacy-preserving techniques for data analysis and machine learning, including topics such as differential privacy, federated learning, k-anonymity, secure computation, and location privacy. The papers explore methods to protect sensitive information while performing data mining, machine learning, and statistical analysis.
- Differential Privacy
- Federated Learning
- k-Anonymity
- Privacy Preservation
- Machine Learning
- Location Privacy
- Data Mining
- Anonymization
- Secure Computation
- Membership Inference Attacks
- Research works
- 35k fractional, since 1953
- In the world top 10%
- 10k per year above
- Top-10% rate
- 29.8% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- +101% the tick is no change
Which countries lead Privacy-Preserving Technologies in Data research?
By volume, China and the United States publish the most (5.2k and 2.2k works in 2022–2025).
By volume, 2022–2025
- 1 China 5.2k works
- 2 United States 2.2k works
- 3 India 1.6k works
- 4 United Kingdom 475 works
- 5 Germany 437 works
- 6 Australia 399 works
- 7 Canada 380 works
- 8 South Korea 337 works
- 9 Italy 327 works
- 10 Japan 324 works
How concentrated that is
The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.
Shares of the rows listed above, not of the whole node.
Which institutions lead Privacy-Preserving Technologies in Data research?
By volume in 2022–2025, Beijing University of Posts and Telecommunications publishes the most Privacy-Preserving Technologies in Data research, followed by Xidian University and University of Electronic Science and Technology of China.
By volume, 2022–2025
- 1 Beijing University of Posts and TelecommunicationsChina 156 works
- 2 Xidian UniversityChina 141 works
- 3 University of Electronic Science and Technology of ChinaChina 98 works
- 4 Shanghai Jiao Tong UniversityChina 84 works
- 5 Beijing Institute of TechnologyChina 80 works
- 6 Tsinghua UniversityChina 77 works
- 7 Nanyang Technological UniversitySingapore 75 works
- 8 Sun Yat-sen UniversityChina 74 works
- 9 University of Science and Technology of ChinaChina 74 works
- 10 Zhejiang UniversityChina 70 works
Who are the leading researchers in Privacy-Preserving Technologies in Data?
The most-cited researchers publishing on Privacy-Preserving Technologies in Data include Li Fei-Fei, Yoshua Bengio and H. Vincent Poor.
- 1 Li Fei-Fei United States 17k citations
- 2 Yoshua Bengio Canada 17k citations
- 3 H. Vincent Poor United States 9.5k citations
- 4 Rajkumar Buyya Australia 7.8k citations
- 5 Dan Boneh United States 7.5k citations
- 6 Philip S. Yu United States 6.6k citations
- 7 Francisco Herrera Spain 6.5k citations
- 8 Dacheng Tao Australia 6.1k citations
- 9 Alex Pentland United States 6k citations
- 10 Wil M. P. van der Aalst Netherlands 5.5k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Privacy-Preserving Technologies in Data research done?
The largest centres of Privacy-Preserving Technologies in Data research in 2022–2025 are Beijing (China), Shanghai (China), Nanjing (China) and Xi'an (China). Among places with at least 20 works in it, it is an unusually large share of all research in Fredericton.
Largest cities, 2022–2025
Where it is the local speciality
- FrederictonCA · 22.0 works9.8×
Location quotient: how much more of its research is in Privacy-Preserving Technologies in Data than the world average.
Where is the best place to study Privacy-Preserving Technologies in Data?
Among universities, judged by research, Xidian University, Hong Kong University of Science and Technology and Beijing University of Posts and Telecommunications score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.
One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.
| # | University | Score | Top 10% | Specialisation | Works | Growth |
|---|---|---|---|---|---|---|
| 1 | Xidian UniversityChina | 77.2 | 34.4% | 13.2× | 141 | +183.1% |
| 2 | Hong Kong University of Science and TechnologyHong Kong | 72.9 | 42.3% | 10.9× | 62 | +18.2% |
| 3 | Beijing University of Posts and TelecommunicationsChina | 71.4 | 28.5% | 17.4× | 156 | +135.9% |
| 4 | Nanyang Technological UniversitySingapore | 69.9 | 45.3% | 6.4× | 75 | +88.9% |
| 5 | University of Technology SydneyAustralia | 68.5 | 36.7% | 6.9× | 45 | +297.5% |
| 6 | Guangzhou UniversityChina | 68.3 | 31.3% | 9.6× | 51 | +177.0% |
| 7 | Singapore Management UniversitySingapore | 68.1 | 45.1% | 12.2× | 19 | +78.7% |
| 8 | City University of MacauMacau | 67.8 | 39.6% | 11.7× | 26 | — |
| 9 | Singapore University of Technology and DesignSingapore | 65.5 | 39.1% | 17.1× | 23 | — |
| 10 | Mohamed bin Zayed University of Artificial IntelligenceUnited Arab Emirates | 65.3 | 37.3% | 30.1× | 18 | — |
Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.
Is Privacy-Preserving Technologies in Data research growing?
Output in 2018–2022 was 101% higher than in 2013–2017, peaking in 2025. The fastest-growing topics are Privacy-Preserving Technologies in Data.
The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.
Which topics inside it are moving
Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.