Partitioned Data Security on Outsourced Sensitive and Non-sensitive Data

12/20/2018
by   Sharad Mehrotra, et al.
0

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.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
05/13/2020

Panda: Partitioned Data Security on Outsourced Sensitive and Non-sensitive Data

Despite extensive research on cryptography, secure and efficient query p...
research
12/04/2018

Exploiting Data Sensitivity on Partitioned Data

Several researchers have proposed solutions for secure data outsourcing ...
research
07/18/2022

Don't Be a Tattle-Tale: Preventing Leakages through Data Dependencies on Access Control Protected Data

We study the problem of answering queries when (part of) the data may be...
research
01/29/2019

Secure selections on encrypted multi-writer streams

Performing searches over encrypted data is a very current and active are...
research
02/18/2020

An Efficient Secure Dynamic Skyline Query Model

It is now cost-effective to outsource large dataset and perform query ov...
research
02/18/2020

SCALE: An Efficient Framework for Secure Dynamic Skyline Query Processing in the Cloud

It is now cost-effective to outsource large dataset and perform query ov...
research
02/28/2020

Dynamic Skyline Queries on Encrypted Data Using Result Materialization

Skyline computation is an increasingly popular query, with broad applica...

Please sign up or login with your details

Forgot password? Click here to reset