Delegatable Pseudorandom Function via GGM Trapdoor
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current cryptographic techniques lack a delegatable pseudorandom function (DPRF) primitive that enables secure delegation of pseudorandom function evaluation to an untrusted proxy according to a given predicate, which is essential for efficient and secure computation in various information security applications.
Innovation Solution
The development of a delegatable pseudorandom function (DPRF) cryptographic primitive allows a delegator to compute a trapdoor based on a secret key and a predicate, enabling a proxy to evaluate pseudorandom functions for a subset of inputs while maintaining security and privacy properties, using the Gordreich, Goldwasser, Micali (GGM) binary tree representation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If pseudorandom function evaluation is delegated to an untrusted proxy, then computational efficiency is improved, but security and privacy protection deteriorates
Solution Approach 1:
The patent segments the pseudorandom function evaluation process into two distinct phases: (1) trapdoor generation phase where the delegator computes a trapdoor based on the secret key and predicate, and (2) evaluation phase where the proxy uses the trapdoor to compute PRF values for inputs satisfying the predicate. This segmentation allows the delegator to retain control over the secret key while delegating computation, thus improving efficiency without compromising security.
Solution Approach 2:
The patent introduces a trapdoor as an intermediary mechanism that enables the proxy to evaluate pseudorandom functions without direct access to the secret key. The trapdoor acts as a mediator that contains encoded information about the predicate, allowing the proxy to compute PRF values for qualifying inputs while the security properties are maintained through the cryptographic design of the trapdoor structure.
2Adaptability or versatility
If the proxy is given full access to evaluate pseudorandom functions, then evaluation flexibility is improved, but information leakage increases
Solution Approach 1:
The patent applies local quality by encoding the predicate P directly into the trapdoor structure, which restricts the proxy's evaluation capability to only those inputs that satisfy the predicate. The trapdoor contains localized information about the predicate conditions, enabling the proxy to flexibly evaluate PRF values for qualifying inputs while preventing access to information about inputs that do not satisfy the predicate, thus avoiding information leakage.
3Measurement precision
If the trapdoor contains detailed predicate information, then evaluation accuracy is improved, but proxy inference capability increases
Solution Approach 1:
The patent uses copying by creating a transformed representation of the predicate information within the trapdoor that is functionally equivalent for evaluation purposes but cryptographically obscured. The trapdoor contains a copied and encoded version of the predicate conditions that enables accurate evaluation of qualifying inputs while the cryptographic transformation prevents the proxy from inferring additional information about the original predicate or non-qualifying inputs.
Data Source
AI summary
Techniques are provided for delegating evaluation of pseudorandom functions to a proxy. A delegator delegates evaluation of a pseudorandom function to a proxy, by providing a trapdoor τ to the proxy based on a secret key k and a predicate P using an algorithm T, wherein the predicate P defines a plurality of values for which the proxy will evaluate the pseudorandom function, wherein the plurality of values comprise a subset of a larger domain of values, and wherein the trapdoor τ provides an indication to the proxy of the plurality of values. A proxy evaluates a pseudorandom function delegated by a delegator by receiving a trapdoor τ from the delegator that provides an indication of a plurality of values to be evaluated, wherein the plurality of values comprise a subset of a larger domain of values; and evaluating an algorithm C on the trapdoor τ to obtain the pseudorandom function value for each of the plurality of values. The trapdoor τ can be provided to the proxy using a Gordreich, Goldwasser, Micali (GGM) binary tree representation.