Garbled-Circuit Stream Analysis for Privacy-Preserving Multi-Party Data
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Solution Overview
Problem
Existing systems face challenges in analyzing data streams in real-time while ensuring privacy, particularly in distributed computing environments where multiple entities are involved, and there is a need for secure and efficient data processing without compromising privacy.
Innovation Solution
A cryptographic protocol is implemented that allows multiple computing entities to perform multi-party computations on obfuscated data, where the first computing entity and second computing entity agree on a circuit or function, generating a garbled truth table to determine outputs without revealing plaintext inputs, using an evaluation module and garbler module to execute the computation securely.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multi-party computation is performed on plaintext data to enable real-time data stream analysis, then productivity and analysis speed are improved, but data privacy and security deteriorate as parties can access each other's inputs
Solution Approach 1:
The patent introduces an intermediary cryptographic protocol layer between the computing parties. The garbler module creates garbled circuits that act as intermediaries, allowing computation to proceed while preventing direct access to plaintext inputs. The oblivious transfer mechanism serves as another intermediary layer that enables input sharing without revelation, thus maintaining productivity while protecting data privacy through multiple intermediary layers.
2Reliability
If cryptographic protocols are implemented to preserve data privacy in multi-party computations, then data security is improved, but device complexity and computational overhead increase
Solution Approach 1:
The cryptographic protocol is segmented into distinct functional modules: the garbler module that creates garbled circuits, the evaluation module that executes computations, and the oblivious transfer mechanism for input sharing. Each module has a specific responsibility, which simplifies the overall system design and makes the complex cryptographic operations more manageable and implementable in distributed environments.
3Productivity
If real-time processing constraints are enforced for data stream analysis, then productivity is improved, but the ability to perform secure cryptographic operations deteriorates due to time limitations
Solution Approach 1:
The garbled circuits are constructed in advance by the garbler module before the actual data processing begins. This preliminary action allows the computationally intensive cryptographic setup to be performed separately from the time-critical data analysis phase. When data arrives in real-time streams, the evaluation module can quickly execute pre-prepared garbled circuits without incurring cryptographic setup overhead, thus meeting real-time processing constraints.
Data Source
AI summary
Systems and methods for implementing a secure and efficient cryptographic protocol for analyzing data objects while providing assurances of data privacy and security. A data object may be obfuscated and provided for analysis (e.g., to a data analytics service) without necessarily providing access to the (e.g., plaintext) data object. For example, a first computing entity and second computing entity may agree upon a function or circuit that performs a certain type of computational task, such as comparing a first data set controlled by the first computing entity and a second data set controlled by the second computing entity. An event-driven function may be invoked by the event-driven compute service in response to detecting satisfaction of a condition as part of monitoring alerts that are generated as a result of the output of the computational task described above.