SYSTEM AND METHOD FOR SECURE DATA PROCESSING WITH PRIVACY-PRESERVING COMPRESSION AND QUALITY ENHANCEMENT
A unified platform for multi-type data compression and decompression is disclosed. The platform employs a virtual management layer to receive, organize, and route input data to corresponding compression subsystems. Multiple compression methods, including homomorphic encryption-based techniques, are utilized to compress data sets while maintaining data privacy. A data manager associates and manages related data sets throughout the compression and decompression processes. Compressed data is routed to appropriate decompression subsystems, where it is decompressed and reconstructed using advanced techniques, such as neural upsampling, to recover lost information and enhance data quality. The platform supports various data types and compression methods, enabling efficient and secure compression and decompression of data. By integrating homomorphic encryption and data reconstruction techniques, the platform provides a comprehensive solution for data compression and decompression while preserving data privacy and enhancing data quality.
1 . A system for data processing, comprising:
a computing device comprising at least a memory and a processor;
a plurality of programming instructions that, when operating on the processor, cause the computing device to:
receive data;
organize the data into a plurality of data sets;
route each data set to at least one processing component;
apply at least one privacy-preserving compression technique to the data sets;
perform operations on the compressed data sets while maintaining data privacy;
route the compressed data sets to at least one decompression component;
decompress the compressed data sets;
apply data reconstruction techniques to enhance quality of the decompressed data sets; and
output the enhanced data.
2 . The system of claim 1 , wherein the privacy-preserving compression technique comprises at least one of:
encoding data into lower-dimensional representations; and
encrypting the data using a privacy-preserving encryption scheme.
3 . The system of claim 1 , wherein the privacy-preserving compression technique comprises:
quantizes data sets into intervals represented by codewords; and
compresses the data sets using the codewords.
4 . The system of claim 1 , further comprising:
identifying relationships between data sets; and
maintaining the relationships throughout processing.
5 . The system of claim 1 , wherein applying data reconstruction techniques comprises:
receive decompressed data sets;
process the decompressed data sets using one or more trained models to recover information; and
output processed data.
6 . The system of claim 5 , wherein the one or more trained models are trained using paired processed and unprocessed data.
7 . A method for data processing, comprising:
receiving data;
organizing the data into a plurality of data sets;
routing each data set to at least one processing component;
applying at least one privacy-preserving compression technique to the data sets;
performing operations on the compressed data sets while maintaining data privacy;
routing the compressed data sets to at least one decompression component;
decompressing the data sets;
applying data reconstruction techniques to enhance quality of the decompressed data sets; and
outputting the enhanced data.
8 . The method of claim 7 , wherein the privacy-preserving compression technique comprises at least one of:
encoding data into lower-dimensional representations; and
encrypting the data sets using a privacy-preserving encryption scheme.
9 . The method of claim 7 , wherein the privacy-preserving compression technique comprises:
quantizes data sets into intervals represented by codewords; and
compresses the data sets using the codewords.
10 . The method of claim 7 , further comprising:
identifying relationships between the data sets; and
maintaining the relationships throughout the processing.
11 . The method of claim 7 , wherein applying data reconstruction techniques comprises:
receiving decompressed data sets;
processing the decompressed data sets using one or more trained models to recover information; and
outputting processed data.
12 . The method of claim 11 , wherein one or more trained models are trained using paired processed and unprocessed data.