Partitioned Data Security on Outsourced Sensitive and Non-sensitive Data (Extended 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 some of the limitations of existing encryption-based approaches. Taking the cue from recent papers on hybrid clouds, this paper explores a new direction of work that attempts to exploit database techniques to secure selection queries. We propose a new secure selection query 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). Interestingly, besides improving performance, we show that QB actually strengthens the security of the underlying cryptographic technique by preventing size, frequency-count, and workload-skew attacks.