Search results for "Secure multi-party computation"

Properties and constraints of cheating-immune secret sharing schemes

2006

AbstractA secret sharing scheme is a cryptographic protocol by means of which a dealer shares a secret among a set of participants in such a way that it can be subsequently reconstructed by certain qualified subsets. The setting we consider is the following: in a first phase, the dealer gives in a secure way a piece of information, called a share, to each participant. Then, participants belonging to a qualified subset send in a secure way their shares to a trusted party, referred to as a combiner, who computes the secret and sends it back to the participants.Cheating-immune secret sharing schemes are secret sharing schemes in the above setting where dishonest participants, during the recons…

Rings for Privacy: an Architecture for Large Scale Privacy-Preserving Data Mining

2021

This article proposes a new architecture for privacy-preserving data mining based on Multi Party Computation (MPC) and secure sums. While traditional MPC approaches rely on a small number of aggregation peers replacing a centralized trusted entity, the current study puts forth a distributed solution that involves all data sources in the aggregation process, with the help of a single server for storing intermediate results. A large-scale scenario is examined and the possibility that data become inaccessible during the aggregation process is considered, a possibility that traditional schemes often neglect. Here, it is explicitly examined, as it might be provoked by intermittent network connec…

PRIVACY-PRESERVING METERING AND LOAD CONTROL IN SMART GRID

In the last decade, electrical grids have experienced an impressive evolution towards the so called Smart Grids, inspired by the Internet model. Indeed, the main driver for this evolution is the exploitation of communication networks for enabling the integration of renewable energy sources and making the energy demand closer to the time-varying production. While witnessing to the incremental deployment of Smart Grids and novel services for Smart Grids, we note a growing awareness on the risks associated to the collection of many sensitive users data. For example, monitoring the temporal trace of the energy consumption data of a given residential customer, may reveal a lot of information on …

Experimental evaluation of privacy-preserving aggregation schemes on planetlab

2015

New pervasive technologies often reveal many sen- sitive information about users’ habits, seriously compromising the privacy and sometimes even the personal security of people. To cope with this problem, researchers have developed the idea of privacy-preserving data mining which refers to the possibility of releasing aggregate information about the data provided by multiple users, without any information leakage about individual data. These techniques have different privacy levels and communication costs, but all of them can suffer when some users’ data becomes inaccessible during the operation of the privacy preserving protocols. It is thus interesting to validate the applicability of such…

Privacy Preserving Client/Vertical-Servers Classification

2019

We present a novel client/vertical-servers architecture for hybrid multi-party classification problem. The model consists of clients whose attributes are distributed on multiple servers and remain secret during training and testing. Our solution builds privacy-preserving random forests and completes them with a special private set intersection protocol that provides a central commodity server with anonymous conditional statistics. Subsequently, the private set intersection protocol can be used to privately classify the queries of new clients using the commodity server’s statistics. The proviso is that the commodity server must not collude with other parties. In cases where this restriction …

Pricavy-Preserving Aspects for Data Mining in ICT Services

The steady adoption of systems for profiling users behavior, collecting and critically interpreting as much information as possible about likes and dislikes, interests and habits of Internet residents and generic services consumers have rapidly become some of the hottest keywords within networking research community. Indeed, mining information about users behavior is an advantage for both service providers and service customers: on one side, providers can improve their revenues by focusing on the most successful features of their services, while on the other side, users can enjoy services which reflect closer their specific needs. There are many examples of user profiling applications. Inte…