Paul Grubbs

1.6k total citations · 1 hit paper
14 papers, 769 citations indexed

About

Paul Grubbs is a scholar working on Artificial Intelligence, Information Systems and Computational Theory and Mathematics. According to data from OpenAlex, Paul Grubbs has authored 14 papers receiving a total of 769 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 6 papers in Information Systems and 2 papers in Computational Theory and Mathematics. Recurrent topics in Paul Grubbs's work include Cryptography and Data Security (11 papers), Internet Traffic Analysis and Secure E-voting (5 papers) and Privacy-Preserving Technologies in Data (3 papers). Paul Grubbs is often cited by papers focused on Cryptography and Data Security (11 papers), Internet Traffic Analysis and Secure E-voting (5 papers) and Privacy-Preserving Technologies in Data (3 papers). Paul Grubbs collaborates with scholars based in United States, Jamaica and United Kingdom. Paul Grubbs's co-authors include Thomas Ristenpart, David M. Cash, Jason Perry, Muhammad Naveed, Vitaly Shmatikov, Marie-Sarah Lacharité, Brice Minaud, Kenneth G. Paterson, Vincent Bindschaedler and Richard McPherson and has published in prestigious journals such as Proceedings of the VLDB Endowment, Network Security and IACR Cryptology ePrint Archive.

In The Last Decade

Paul Grubbs

11 papers receiving 754 citations

Hit Papers

Leakage-Abuse Attacks Against Searchable Encryption 2015 2026 2018 2022 2015 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Paul Grubbs United States 8 729 223 200 138 132 14 769
Brice Minaud United Kingdom 6 463 0.6× 138 0.6× 121 0.6× 88 0.6× 124 0.9× 8 488
Raphaël Bost France 4 754 1.0× 267 1.2× 170 0.8× 74 0.5× 165 1.3× 4 813
Nir Bitansky Israel 11 455 0.6× 215 1.0× 178 0.9× 65 0.5× 41 0.3× 23 508
Qingji Zheng United States 11 728 1.0× 550 2.5× 131 0.7× 227 1.6× 59 0.4× 20 864
Craig Costello United States 7 440 0.6× 220 1.0× 66 0.3× 101 0.7× 100 0.8× 18 504
Daniel Wichs United States 14 608 0.8× 205 0.9× 197 1.0× 68 0.5× 98 0.7× 31 651
Gil Segev Israel 13 444 0.6× 96 0.4× 156 0.8× 114 0.8× 80 0.6× 38 509
Nicolas Gama France 8 519 0.7× 153 0.7× 164 0.8× 74 0.5× 73 0.6× 12 581
Mariya Georgieva Switzerland 4 463 0.6× 139 0.6× 125 0.6× 61 0.4× 71 0.5× 5 510
Hoeteck Wee United States 10 334 0.5× 97 0.4× 144 0.7× 120 0.9× 39 0.3× 18 449

Countries citing papers authored by Paul Grubbs

Since Specialization
Citations

This map shows the geographic impact of Paul Grubbs's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Paul Grubbs with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paul Grubbs more than expected).

Fields of papers citing papers by Paul Grubbs

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Paul Grubbs. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Paul Grubbs. The network helps show where Paul Grubbs may publish in the future.

Co-authorship network of co-authors of Paul Grubbs

This figure shows the co-authorship network connecting the top 25 collaborators of Paul Grubbs. A scholar is included among the top collaborators of Paul Grubbs based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Paul Grubbs. Paul Grubbs is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
1.
Ozdemir, Alex, et al.. (2025). Efficient Proofs of Possession for Legacy Signatures. 3291–3308.
2.
3.
Dao, Quang, et al.. (2023). Weak Fiat-Shamir Attacks on Modern Proof Systems. 199–216.
4.
Grubbs, Paul, Anurag Khandelwal, Marie-Sarah Lacharité, et al.. (2020). PANCAKE: Frequency Smoothing for Encrypted Data Stores.. IACR Cryptology ePrint Archive. 2020. 1501–2468. 6 indexed citations
5.
Grubbs, Paul, Marie-Sarah Lacharité, Brice Minaud, & Kenneth G. Paterson. (2019). Learning to Reconstruct: Statistical Learning Theory and Encrypted Database Attacks. 1067–1083. 61 indexed citations
6.
Bindschaedler, Vincent, Paul Grubbs, David M. Cash, Thomas Ristenpart, & Vitaly Shmatikov. (2018). The tao of inference in privacy-protected databases. Proceedings of the VLDB Endowment. 11(11). 1715–1728. 39 indexed citations
7.
Grubbs, Paul, Marie-Sarah Lacharité, Brice Minaud, & Kenneth G. Paterson. (2018). Pump up the Volume. Zenodo (CERN European Organization for Nuclear Research). 315–331. 64 indexed citations
8.
Grubbs, Paul, Thomas Ristenpart, & Vitaly Shmatikov. (2017). Why Your Encrypted Database Is Not Secure. 162–168. 37 indexed citations
9.
Grubbs, Paul, et al.. (2017). Leakage-Abuse Attacks against Order-Revealing Encryption. 655–672. 106 indexed citations
10.
Wang, Liang, Paul Grubbs, Jiahui Lu, et al.. (2017). Side-Channel Attacks on Shared Search Indexes. 673–692. 5 indexed citations
11.
Grubbs, Paul, Richard McPherson, Muhammad Naveed, Thomas Ristenpart, & Vitaly Shmatikov. (2016). Breaking Web Applications Built On Top of Encrypted Data. 1353–1364. 63 indexed citations
12.
Cash, David M., Paul Grubbs, Jason Perry, & Thomas Ristenpart. (2015). Leakage-Abuse Attacks Against Searchable Encryption. 668–679. 367 indexed citations breakdown →
13.
Boldyreva, Alexandra & Paul Grubbs. (2014). Making encryption work in the cloud. Network Security. 2014(10). 8–10. 2 indexed citations
14.
Myers, Steven, et al.. (2013). GPU and CPU parallelization of honest-but-curious secure two-party computation. 169–178. 19 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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