The fact that the information can be collected not only by the government and power companies but also individual users adds seriousness to the problem. In this paper examined this issue by focusing on the load management system based on BEMS that uses the privacy policy-based protection system in the smart grid environment. The structure of the privacy policy-based protection system using load...

In this paper an analytical framework is proposed for the evaluation of the tradeoffs between location privacy and energy efficiency in wireless sensor networks. We assume that random routing is utilized to improve privacy. However, this involves an increase in the average path length and thus an increase in energy consumption. The privacy loss is measured using information theory concepts; ind...

It is arguable that the instinct for survival in animal species has evolved due to the evolutionary elimination of those individuals who did not have enough inclination nor desire to cluster in a team. Thus, the roots of ethical conduct in its many facets in today’s world, may be sought in this very primeval concern for the society that enabled communities, rather than individuals, to survive i...

We provide a detailed study of the estimation of probability distributions— discrete and continuous—in a stringent setting in which data is kept private even from the statistician. We give sharp minimax rates of convergence for estimation in these locally private settings, exhibiting fundamental trade-offs between privacy and convergence rate, as well as providing tools to allow movement along ...

Functional encryption (FE) supports constrained decryption keys that allow decrypters to learn specific functions of encrypted messages. In numerous practical applications of FE, confidentiality must be assured not only for the encrypted data but also for the functions for which functional keys are provided. This paper presents a non-generic simple private key FE scheme for the inner product fu...

Privacy-preserving data publishing addresses the problem of disclosing sensitive data when mining for useful information. Among the existing privacy models, ǫ-differential privacy provides one of the strongest privacy guarantees. In this paper, we address the problem of private data publishing where data is horizontally divided among two parties over the same set of attributes. In particular, w...

We derive the optimal -differentially private mechanism for a general two-dimensional real-valued (histogram-like) query function under a utility-maximization (or cost-minimization) framework for the ` cost function. We show that the optimal noise probability distribution has a correlated multidimensional staircase-shaped probability density function. Compared with the Laplacian mechanism, we s...

In this age of eternal connectedness, using various social networks, privacy is an important problem that needs to be transparent. Even though social networks provide a user the ability to control their privacy settings, it is often difficult to get similar privacy settings across different social network systems. This is because: (a) privacy settings rely on complicated privacy rules which def...

Secure multi-party computation platforms are becoming more and more practical. This has paved the way for privacy-preserving statistical analysis using secure multi-party computation. Simple statistical analysis functions have been emerging here and there in literature, but no comprehensive system has been compiled. We describe and implement the most used statistical analysis functions in the p...

Social network services enable users to share large quantities of private information. Often, the shared information concerns individuals who are members of the social network but did not upload the information to the service. In such situations, inappropriate sharing preferences can cause conflict and threaten users’ privacy. Since related studies suggest that users prefer to solve multi-party...