Leveraging Users' Likes in a Video Streaming P2P Platform

2014

This paper investigates how a p2p television platform can take advantage of the presence of frequent channel viewers to grant them a more satisfying service than to less regular spectators. The idea we explore is to learn beforehand about the users' interests, in order to cluster them in groups that display different behaviors; then, the neighborhood creation strategy and video chunk scheduling algorithm of the overlay is altered, with the aim of serving frequent spectators in a privileged manner, providing them with a faster access to the selected channel without overly penalizing less habitual customers. An analytical model is developed, to capture the difference in startup delay that the…

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…

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…

Rings for privacy: An architecture for privacy-preserving user profiling

2014

An interest-aware video streaming platform: Shaping its architecture to better suit users' demands

2014

This paper investigates how a p2p television platform can take advantage of the presence of frequent channel viewers to grant them a more satisfying service than to less regular spectators. The idea we explore is to learn beforehand about the users’ interests, in order to cluster them in groups that display different behaviors; then, the video chunk scheduling algorithm of the p2p overlay is altered, with the aim of serving frequent spectators in a privileged manner, providing them with a faster access to the selected channel. An analytical model is developed, to capture the difference in startup delay that the proposed changes introduce; several additional performance metrics are numerical…

Multi-cloud privacy preserving schemes for linear data mining

2015

This paper presents an approach to privacy-preserving data mining that relies upon a relatively simple secret sharing scheme. Its main feature is that users, sensitive data owners, are engaged in the secret sharing operations that protect their privacy. They are grouped in independent clouds connected to a central unit, the data miner, that only manages the aggregated data of each cloud, therefore avoiding the disclosure of information belonging to single nodes. We propose two privacy preserving schemes, with different privacy levels and communication costs. When designing them, we assume that some users' data might become inaccessible during the operation of the privacy preserving protocol…