PENDA: Privacy ENhanced Data Aggregator. (2022). Proceedings of 2022 the 12th International Workshop on Computer Science and Engineering. https://doi.org/10.18178/wcse.2022.06.010
Abstract:
Data is spread across different organizations and must be combined to get valuable analytics or
train machine learning models. Sensitive features such as identification numbers, as columns, are common in
these data, and organizations can only link if they share these columns. However, data protection regulations
prevent these organizations from revealing the values in these columns to others. This paper proposes a
technique, PENDA (Privacy ENhanced Data Aggregator), to encrypt columns of a database table or
spreadsheet so that a central aggregation server can join them without decrypting using XOR-based
homomorphism. We implement our PENDA system and demonstrate how organizations taking part in the
process can encrypt and merge data. The experimental results show that the system can handle very large
data files and scale to multiple organizations.
License type:
Publisher Copyright
Funding Info:
This research / project is supported by the A*STAR - Advanced Manufacturing and Engineering (AME) Programmatic Programme
Grant Reference no. : A19E3b0099