… differential privacy guarantees. We study the privacy guarantees that can be achieved by …
Since the noise is calibrated to mask the effect of a single rating, larger datasets provide a …

… masking, to achieve (ε, δ)-differential privacy (DP) more efficiently. We prove that the additional
matrix masking … the Gaussian scheme to achieve (ε, δ)−DP in big data setting. Specifically…

… By definition, it pursues masking whether or not a user appears in the database, known
as per-user … Our system aims to achieve the following privacy requirements (see Table 2): …

… a robust, standardized mathematical framework ensuring strong privacy protection and finds
extensive application in big data … Specifically, we seek to achieve the following objectives: …

… privacy guarantees that can be achieved by the following approaches: (i) by obfuscating the
input data before applying the matrix … the unbounded differential privacy hiding the presence …

… the efficacy of differential privacy and the interaction with … to provide differential privacy
(typically at the cost of getting a … requests we perform latency hiding by prefetching. That is, …

… Privacy in big data can be achieved through various means but here the focus is on differential
privacy. … Thus hiding some information cannot assures the protection of individual identity. …

… strategic deployment of big data analytics in business settings and to achieve sustainable
… propose a Secure and Efficient data perturbation Algorithm utilizing local differential privacy. …

… strategy successfully masks the privacy of participating units, … effectively mask differential
privacy as well as can achieve … In this article, the differential privacy is employed to mask the …

… In addition, big data analytics can help power providers to … privacy is related with appliance
usage, we aim to achieve … Therefore, we will demonstrate the masking approach using …