Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 649

The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.

Lossy Trapdoor Functions and Their Applications

Peikert, Chris, Waters, Brent·2011·SIAM Journal on Computing

Abstract

We propose a general cryptographic primitive called lossy trapdoor functions (lossy TDFs), and we use it to develop new approaches for constructing several important cryptographic tools, including (injective) trapdoor functions, collision-resistant hash functions, oblivious transfer, and chosen ciphertext-secure cryptosystems (in the standard model). All of these constructions are simple, efficient, and black-box. We realize lossy TDFs based on a variety of cryptographic assumptions, including the hardness of the decisional Diffie–Hellman (DDH) problem and the hardness of the “learning with errors” problem (which is implied by the worst-case hardness of various lattice problems). Taken together, our results resolve some long-standing open problems in cryptography. They give the first injective TDFs based on problems not directly related to integer factorization and provide the first chosen ciphertext-secure cryptosystem based solely on worst-case complexity assumptions.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1137/080733954

Cites

35 of 35 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 35 references

Cited by

See all 649

Metadata

Authors
Peikert, C., & Waters, B.
Venue
SIAM Journal on Computing
Published
2011-01
Volume
40
Issue
6
Pages
1803-1844
ISSN
  • 0097-5397 (ISSN-L)
  • 1095-7111
OpenAlex
W217975980
Cited by
649
References
35
FWCI
66.25
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Lossy Trapdoor Functions and Their Applications. https://app.cochat.ai/papers/10.1137/080733954
The paper
Peikert, C., & Waters, B. (2011). Lossy Trapdoor Functions and Their Applications. SIAM Journal on Computing. https://doi.org/10.1137/080733954

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.