5,046 research outputs found
Efficiently Enforcing Input Validity in Secure Two-party Computation
Secure two-party computation based on cut-and-choose has made great strides in recent years, with a significant reduction in the total number of garbled circuits required. Nevertheless, the overhead of cut-and-choose can still be significant for large circuits (i.e., a factor of in both communication and computation for statistical security ).
We show that for a particular class of computation it is possible to do better. Namely, consider the case where a function on the parties\u27 inputs is computed only if each party\u27s input satisfies some publicly checkable predicate (e.g., is signed by a third party, or lies in some desired domain). Using existing cut-and-choose-based protocols, both the predicate checks and the function would need to be garbled times. Here we show a protocol in which only the underlying function is garbled times, and the predicate checks are each garbled only \emph{once}. For certain natural examples (e.g., signature verification followed by evaluation of a million-gate circuit), this can lead to huge savings in communication (up to 80) and computation (up to 56). We provide detailed estimates using realistic examples to validate our claims
Oblivion: Mitigating Privacy Leaks by Controlling the Discoverability of Online Information
Search engines are the prevalently used tools to collect information about
individuals on the Internet. Search results typically comprise a variety of
sources that contain personal information -- either intentionally released by
the person herself, or unintentionally leaked or published by third parties,
often with detrimental effects on the individual's privacy. To grant
individuals the ability to regain control over their disseminated personal
information, the European Court of Justice recently ruled that EU citizens have
a right to be forgotten in the sense that indexing systems, must offer them
technical means to request removal of links from search results that point to
sources violating their data protection rights. As of now, these technical
means consist of a web form that requires a user to manually identify all
relevant links upfront and to insert them into the web form, followed by a
manual evaluation by employees of the indexing system to assess if the request
is eligible and lawful.
We propose a universal framework Oblivion to support the automation of the
right to be forgotten in a scalable, provable and privacy-preserving manner.
First, Oblivion enables a user to automatically find and tag her disseminated
personal information using natural language processing and image recognition
techniques and file a request in a privacy-preserving manner. Second, Oblivion
provides indexing systems with an automated and provable eligibility mechanism,
asserting that the author of a request is indeed affected by an online
resource. The automated ligibility proof ensures censorship-resistance so that
only legitimately affected individuals can request the removal of corresponding
links from search results. We have conducted comprehensive evaluations, showing
that Oblivion is capable of handling 278 removal requests per second, and is
hence suitable for large-scale deployment
Raziel: Private and Verifiable Smart Contracts on Blockchains
Raziel combines secure multi-party computation and proof-carrying code to
provide privacy, correctness and verifiability guarantees for smart contracts
on blockchains. Effectively solving DAO and Gyges attacks, this paper describes
an implementation and presents examples to demonstrate its practical viability
(e.g., private and verifiable crowdfundings and investment funds).
Additionally, we show how to use Zero-Knowledge Proofs of Proofs (i.e.,
Proof-Carrying Code certificates) to prove the validity of smart contracts to
third parties before their execution without revealing anything else. Finally,
we show how miners could get rewarded for generating pre-processing data for
secure multi-party computation.Comment: Support: cothority/ByzCoin/OmniLedge
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