Private Set Intersection Patents: Leaders & Filing Trends 2026
Filing growth compares 2021 (37 records) with 2024 (32) — a three-year span. 2024 is the most recent year we treat as complete: publication lags filing by roughly 18 months, so 2025 onwards are still filling in and any growth rate that ends there would understate the field. Top-5 share is the combined record count of the five largest assignees divided by all 291 records in scope (CR5), not by the ranked leaders only.
What this landscape covers
Private set intersection (PSI) lets two or more parties compute the overlap between their data sets without revealing anything beyond that overlap. This landscape covers 291 published records filed between 2015 and the 2026-07-31 data cut-off, spanning cryptographic protocol claims, data-processing implementations and applied use cases in payments, identity and analytics. Patent families, rather than raw document counts, are the fairer unit for judging how much genuine invention sits behind the filing volume.
Filing activity is concentrated in two overlapping technical classes — digital information transmission and general-purpose data processing — with the assignee base showing a moderately concentrated top tier above a long tail of smaller filers. The most heavily cited records date back to the earliest years in scope, reflecting the time it takes citations to accumulate rather than a claim that older approaches remain dominant.
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Filing trends and technology composition
The 291 records in scope span 2015 to the 2026-07-31 cut-off, with filing activity concentrated in the cryptographic and data-processing classes that underpin private set intersection.
Filings rose sharply, then eased from a 2023 peak
Annual filings climbed from 4 in 2017 to a peak of 55 in 2023. The 2021-to-2024 span shows a -14% change (37 to 32); because publication lags filing by roughly 18 months, 2025 and 2026 figures are still incomplete and should not be read as a decline.
Cryptographic transport and data processing dominate
H04L (digital information transmission) appears in 59.5% of the 291 records and G06F (electric digital data processing) in 55.0%, together forming the technical backbone of most PSI filings. Wireless networks, AI-model computing and business-process classes each account for under 10% of records, and a handful of niche classes sit near 1%.
Shares are the percentage of the 291 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
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Try EurekaMost-cited and representative filings
Federated decision tree learning via private set intersection (US20240330704A1)
A protocol for federated decision tree learning is provided. In one set of embodiments, this protocol employs a cryptographic technique known as private set intersection (PSI) — more precisely a variant called quorum private set intersection analytics (QPSIA) — to carry out federated learning of decision trees efficiently and effectively.Filed by VMware, published 2024-10-03; illustrates how PSI is being combined with federated machine learning rather than used as a standalone protocol.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US20130010950A1 | Public-Key Encrypted Bloom Filters With Applications To Private Set Intersection | 140 |
| 2 | US20150149763A1 | Server-Aided Private Set Intersection (PSI) with Data Transfer | 96 |
| 3 | US20220004654A1 | Security measures for determination of private set intersections | 57 |
| 4 | US20190342270A1 | Computing a private set intersection | 54 |
| 5 | US20150161398A1 | Method and apparatus for privacy and trust enhancing sharing of data for collaborative analytics | 46 |
| 6 | US20200195618A1 | Secure multiparty detection of sensitive data using Private Set Intersection (PSI) | 40 |
| 7 | US20140121990A1 | Secure Informatics Infrastructure for Genomic-Enabled Medicine, Social, and Other Applications | 39 |
| 8 | US20210194668A1 | Weighted partial matching under homomorphic encryption | 38 |
| 9 | CN110622165A | 用于确定隐私集交集的安全性措施 | 37 |
| 10 | US20180367293A1 | Private set intersection encryption techniques | 32 |
Ranked by citation count within the 291 records in scope; older records accumulate more citations by virtue of age, not necessarily current relevance.
Patent titles are shown in the language they were filed in, not translated, so that each record stays verifiable against the original filing — a translated title will not match in Eureka or in any national register. Each row carries its publication number; clicking a row searches Eureka by that number.
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These figures point to a field with an established cryptographic core, moderate ownership concentration and a filing curve still working through publication lag.
Ownership is concentrated but not locked up
The top 5 assignees hold 37.8% of the 291 records in scope, and the top 10 hold 56.0%. That leaves a substantial share spread across a long tail of smaller filers, so new entrants are not filing into a field owned by one or two companies.
Cryptographic transport is the dominant technical route
H04L (digital information transmission) and G06F (electric digital data processing) together anchor the great majority of filings, at 59.5% and 55.0% of the 291 records respectively. Smaller classes like G06N and H04W represent extensions rather than separate commercial routes.
Growth cooled after the 2023 peak, reporting lag pending
Filings rose from 4 records in 2017 to a peak of 55 in 2023, then the 2021-2024 window shows a -14% change (37 to 32). Because publication lags filing by around 18 months, 2025-2026 counts are not yet a reliable signal of a genuine slowdown.
A small number of foundational records anchor the field
The most-cited record, on public-key encrypted Bloom filters for PSI, has drawn 140 citations, well ahead of the next most-cited record at 96. High citation counts inside an older corpus reflect influence built up over years, not necessarily current commercial importance.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to privacy-enhancing technologies: private set intersection patent landscape, with the prior art for and against each one.
| Assignee | Co-assignee | Shared families |
|---|---|---|
| Cayman Islands Faceu Limited | Beijing Zitiao Network Technology Co., Ltd. | 7 |
| Alipay (Hangzhou) Digital Service Technology Co., Ltd. | Ant Blockchain Technology (Shanghai) Co., Ltd. | 2 |
| International Business Machines Corporation (IBM) | IBM (China) Co., Ltd. | 1 |
| International Business Machines Corporation (IBM) | IBM UNITED KINGDOM LTD INTELLECTUAL PROPERTY DEPARTMENT | 1 |
Only 4 co-assignee pairs appear across the dataset, the strongest linking two related entities with 7 shared records — most filers in this space file independently rather than jointly.
Where to take this next
The figures here establish the shape of the field; a deeper review depends on what decision you are making.
Check freedom-to-operate against the top-cited records
The most-cited filings, particularly the foundational Bloom-filter and server-aided PSI constructions, are the ones most new filings need to design around or license.
Run a claim comparison in EurekaTrack the assignee list for M&A and licensing signals
With ownership split between a concentrated top tier and a long tail of smaller filers, shifts in who holds key records can signal consolidation before it is publicly announced.
Monitor assignee activity in EurekaWatch the under-claimed classification branches
Classes like AI-model-integrated PSI and business-process PSI carry far fewer filings than the cryptographic core, which may leave room for differentiated claims.
Explore white space in EurekaFrequently asked questions
Private set intersection (PSI) is a cryptographic protocol that lets two or more parties learn which elements their data sets have in common without revealing anything else about their respective sets. It matters commercially because it lets organisations match records — customer lists, contact identifiers, transaction sets — without exposing the underlying data to each other, which is valuable for advertising measurement, fraud detection and cross-institution analytics. Filing activity rose from 4 records in 2017 to a peak of 55 in 2023 across the 291 records in this dataset, reflecting growing commercial interest as privacy regulation and cross-party data collaboration both increased.
The ranked leaders in this dataset span technology, payments and enterprise-software companies, with the top-ranked assignee holding 36 records. Filing is moderately concentrated: the top 5 assignees together account for 37.8% of the 291 records in scope, and the top 10 account for 56.0%. That leaves a large share of records held by a long tail of single- or few-filing entrants, so the field is not controlled by one or two dominant players.
H04L (digital information transmission) is the most common classification, appearing in 59.5% of the 291 records in scope, closely followed by G06F (electric digital data processing) at 55.0%. Because a single record can carry multiple IPC classes, these two figures overlap substantially — many filings combine a cryptographic transport method with a general data-processing implementation. Smaller classes such as H04W (wireless networks) and G06N (AI-model computing) each cover under 10% of records, marking them as extensions rather than core routes.
Filings grew substantially from 2017 through the 2023 peak of 55 records, but the 2021-to-2024 window shows a -14% change (37 records down to 32). That figure should be read carefully: publication typically lags filing by around 18 months, so the apparent tapering after 2024 is largely a reporting artefact rather than a genuine slowdown, and the most recent one to two years in any such dataset are always understated. A clearer read on 2025 and 2026 filing volumes will only be available once those cohorts finish publishing.
Risk concentrates around the most-cited foundational records, particularly the public-key encrypted Bloom filter construction (140 citations) and server-aided PSI with data transfer (96 citations), both of which underpin a large share of later filings. Anyone building a new PSI implementation using Bloom filters, public-key encryption or server-aided computation should expect to review these records closely. Less-crowded classification branches, such as AI-model-integrated PSI or business-process PSI, currently carry lower filing density and may present comparatively lower freedom-to-operate friction, though with less established prior art to rely on.
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Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, or validity search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. Any patent, commercial, or strategic decision should be verified independently and reviewed with qualified patent, legal, and domain professionals. Patsnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.
Machine translation. Assignee and organisation names originally recorded in Chinese, Japanese or Korean have been rendered into English by an AI translation step so that the tables stay readable. These renderings are best-effort and may not match a company’s registered English name; the original name is what the underlying patent record carries, and it is what any Eureka query launched from this page uses.