# Partitioned Data Security on Outsourced Sensitive and Non-sensitive Data

## TL;DR

This paper introduces query binning (QB), a novel secure method for processing outsourced data that leverages non-sensitive data in clear-text to enhance efficiency and security without leaking information.

## Contribution

The paper proposes query binning (QB), a new approach that securely combines sensitive encrypted data with non-sensitive clear-text data for efficient query processing.

## Key findings

- QB improves query processing performance.
- QB prevents size, frequency, and workload-skew attacks.
- QB enhances security beyond traditional encryption methods.

## Abstract

Despite extensive research on cryptography, secure and efficient query processing over outsourced data remains an open challenge. This paper continues along the emerging trend in secure data processing that recognizes that the entire dataset may not be sensitive, and hence, non-sensitivity of data can be exploited to overcome limitations of existing encryption-based approaches. We propose a new secure approach, entitled query binning (QB) that allows non-sensitive parts of the data to be outsourced in clear-text while guaranteeing that no information is leaked by the joint processing of non-sensitive data (in clear-text) and sensitive data (in encrypted form). QB maps a query to a set of queries over the sensitive and non-sensitive data in a way that no leakage will occur due to the joint processing over sensitive and non-sensitive data. Interestingly, in addition to improve performance, we show that QB actually strengthens the security of the underlying cryptographic technique by preventing size, frequency-count, and workload-skew attacks.