Udi Weinsberg

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Ridge regression is an algorithm that takes as input a large number of data points and finds the best-fit linear curve through these points. The algorithm is a building block for many machine-learning operations. We present a system for privacy-preserving ridge regression. The system outputs the best-fit curve in the clear, but exposes no other information(More)
Recommender systems typically require users to reveal their ratings to a recommender service, which subsequently uses them to provide relevant recommendations. Revealing ratings has been shown to make users susceptible to a broad set of inference attacks, allowing the recommender to learn private user attributes, such as gender, age, etc. In this work, we(More)
We propose introducing modern parallel programming paradigms to secure computation, enabling their secure execution on large datasets. To address this challenge, we present Graph SC, a framework that (i) provides a programming paradigm that allows non-cryptography experts to write secure code, (ii) brings parallelism to such secure implementations, and(More)
To address the pressing need to provide transparency into the online targeted advertising ecosystem, we present <i>AdReveal</i>, a practical measurement and analysis framework, that provides a first look at the prevalence of different ad targeting mechanisms. We design and implement a browser based tool that provides detailed measurements of online display(More)
The diversity of end-to-end &#40;e2e&#41; Internet routes has been studied for over a decade, dating back to Paxson's seminal work from 1995. This paper presents a measurement study of this issue and systematically evaluate the diversity of the Internet routes, while revisiting some of the conclusions previously made. Two large scale experiments are used(More)
User demographics, such as age, gender and ethnicity, are routinely used for targeting content and advertising products to users. Similarly, recommender systems utilize user demographics for personalizing recommendations and overcoming the cold-start problem. Often, privacy-concerned users do not provide these details in their online profiles. In this work,(More)
This paper presents the design of a novel architecture called CARE (Content-Aware Redundancy Elimination) that enables maximizing the informational value that challenged networks offer their users. We focus on emerging applications for situational awareness in disaster affected regions. Motivated by advances in computer vision algorithms, we propose to(More)
The topology of the Internet has been extensively studied in recent years, driving a need for increasingly complex measurement infrastructures. These measurements have produced detailed topologies with steadily increasing temporal resolution, but concerns exist about the ability of active measurement to measure the true Internet topology. Difficulties in(More)
The end-to-end (e2e) stability of Internet routing has been studied for over a decade, focusing on routes and delays. This paper presents a novel technique for uncovering the origins of delay variations by measuring the overlap between delay distribution of probed routes, and how these are affected by route stability. Evaluation is performed using two large(More)