Leveraging Users' Likes in a Video Streaming P2P Platform

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…

Multi-party metering: An architecture for privacy-preserving profiling schemes

Several privacy concerns about the massive deploy- ment of smart meters have been arisen recently. Namely, it has been shown that the fine-grained temporal traces generated by these meters can be correlated with different users behaviors. A new architecture, called multi-party metering, for enabling privacy-preserving analysis of high-frequency metering data without requiring additional complexity at the smart meter side is here proposed. The idea is to allow multiple entities to get a share of the high-frequency metering data rather than the real data, where this share does not reveal any information about the real data. By aggregating the shares provided by different users and publishing …

Experimental evaluation of privacy-preserving aggregation schemes on planetlab

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

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

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…

A secret sharing scheme for anonymous DNS queries

Since its adoption in the early 90's, several privacy concerns have emerged about the Domain Name System (DNS). By collecting the DNS queries performed by each user, it is possible to characterize habits, interests and other sensitive data of the users. Usually, users resolve their {\em url} requests by querying the DSN server belonging to their Internet Service Provider (ISP) and therefore they assume they can trust it. However, different DNS servers can be used, by revealing sensitive data to a partially untrusted entity that can collect and sell this data for several purposes (target advertising, user profiling, etc.). In this paper we address the possibility to integrate tools in the cu…

Multi-cloud privacy preserving schemes for linear data mining

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…

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…