Publications by Reza Shokri | EPFL Graph Search

Related publications (20)

Quantifying and Protecting Location Privacy

Recent developments in information and communication technologies have been profound and life-changing. Most people are now equipped with smart phones with high computation power and communication capabilities. These devices can efficiently run multiple so ...

EPFL2013

Collaborative Location Privacy with Rational Users

Jean-Pierre Hubaux, Mathias Jacques Jean-Marc Humbert, Reza Shokri

Recent smartphones incorporate embedded GPS devices that enable users to obtain geographic information about their surroundings by providing a location-based service (LBS) with their current coordinates. However, LBS providers collect a significant amount ...

Springer-Verlag Berlin2011

Protecting Location Privacy: Optimal Strategy against Localization Attacks

Jean-Yves Le Boudec, Jean-Pierre Hubaux, Carmela González Troncoso, Reza Shokri

The mainstream approach to protecting the location-privacy of mobile users in location-based services (LBSs) is to alter the users' actual locations in order to reduce the location information exposed to the service provider. The location obfuscation algor ...

2012

Quantifying the Effect of Co-location Information on Location Privacy

Jean-Pierre Hubaux, Reza Shokri, Kévin Clément Huguenin, Alexandra-Mihaela Olteanu

Mobile users increasingly report their co-locations with other users, in addition to revealing their locations to online services. For instance, they tag the names of the friends they are with, in the messages and in the pictures they post on social networ ...

Springer-Verlag Berlin2014

A Predictive Model for User Motivation and Utility Implications of Privacy-Protection Mechanisms in Location Check-Ins

Jean-Pierre Hubaux, Kévin Clément Huguenin, Igor Bilogrevic, Reza Shokri, Italo Ivan Dacosta Petrocelli, Joana Catarina Soares Machado

Location check-ins contain both geographical and semantic information about the visited venues. Semantic information is usually represented by means of tags (e.g., “restaurant”). Such data can reveal some personal information about users beyond what they a ...

2018

Quantifying Interdependent Privacy Risks with Location Data

Jean-Pierre Hubaux, Kévin Clément Huguenin, Mathias Jacques Jean-Marc Humbert, Reza Shokri, Alexandra-Mihaela Olteanu

Co-location information about users is increasingly available online. For instance, mobile users more and more frequently report their co-locations with other users in the messages and in the pictures they post on social networking websites by tagging the ...

Ieee Computer Soc2017

Hiding in the Mobile Crowd: Location Privacy through Collaboration

Jean-Pierre Hubaux, Panagiotis Papadimitratos, Reza Shokri, Ehsan Kazemi

Location-aware smartphones support various location-based services (LBSs): users query the LBS server and learn on the fly about their surroundings. However, such queries give away private information, enabling the LBS to track users. We address this probl ...

Ieee Computer Soc2014

Quantifying Location Privacy

Jean-Yves Le Boudec, Jean-Pierre Hubaux, Reza Shokri

It is a well-known fact that the progress of personal communication devices leads to serious concerns about privacy in general, and location privacy in particular. As a response to these issues, a number of Location-Privacy Protection Mechanisms (LPPMs) ha ...

Ieee Computer Soc Press, Customer Service Center, Po Box 3014, 10662 Los Vaqueros Circle, Los Alamitos, Ca 90720-1264 Usa2011

Predicting Users' Motivations behind Location Check-Ins and Utility Implications of Privacy Protection Mechanisms

Jean-Pierre Hubaux, Reza Shokri, Kévin Clément Huguenin, Igor Bilogrevic

Location check-ins contain both geographical and semantic information about the visited venues, in the form of tags (e.g., “restaurant”). Such data might reveal some personal information about users beyond what they actually want to disclose, hence their p ...

2015

Preserving Privacy in Collaborative Filtering through Distributed Aggregation of Offline Profiles

Jean-Pierre Hubaux, Reza Shokri, Pedram Pedarsani

In recommender systems, usually, a central server needs to have access to users' profiles in order to generate useful recommendations. Having this access, however, undermines the users' privacy. The more information is revealed to the server on the user-it ...

ACM2009

Quantifying Location Privacy: The Case of Sporadic Location Exposure

Jean-Yves Le Boudec, Jean-Pierre Hubaux, Reza Shokri

Mobile users expose their location to potentially untrusted entities by using location-based services. Based on the frequency of location exposure in these applications, we divide them into two main types: Continuous and Sporadic. These two location exposu ...

Springer-Verlag Berlin2011

On the Optimal Placement of Mix Zones

Jean-Pierre Hubaux, Julien Freudiger, Reza Shokri

In mobile wireless networks, third parties can track the location of mobile nodes by monitoring the pseudonyms used for identification. A frequently proposed solution to protect the location privacy of mobile nodes suggests to change pseudonyms in regions ...

Springer2009

Prolonging the Hide-and-Seek Game: Optimal Trajectory Privacy for Location-Based Services

Jean-Yves Le Boudec, Jean-Pierre Hubaux, Carmela González Troncoso, Reza Shokri

Human mobility is highly predictable. Individuals tend to only visit a few locations with high frequency, and to move among them in a certain sequence reflecting their habits and daily routine. This predictability has to be taken into account in the design ...

2014

Collaborative Location Privacy

Jean-Pierre Hubaux, Panagiotis Papadimitratos, Reza Shokri

Location-aware smart phones support various location-based services (LBSs): users query the LBS server and learn on the fly about their surroundings. However, such queries give away private information, enabling the LBS to identify and track users. We addr ...

2011

Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks

Volkan Cevher, Reza Shokri, Fanghui Liu, Zhenyu Zhu

We analytically investigate how over-parameterization of models in randomized machine learning algorithms impacts the information leakage about their training data. Specifically, we prove a privacy bound for the KL divergence between model distributions on ...

2023

Evaluating the Privacy Risk of Location-Based Services

Jean-Pierre Hubaux, Julien Freudiger, Reza Shokri

In modern mobile networks, users increasingly share their location with third-parties in return for location-based services. In this way, users obtain services customized to their location. Yet, such communications leak location information about users. Ev ...

Springer-Verlag Berlin2011

A Practical Secure Neighbor Verification Protocol for Wireless Sensor Networks

Jean-Pierre Hubaux, Panagiotis Papadimitratos, Reza Shokri, Marcin Poturalski

Wireless networking relies on a fundamental building block, neighbor discovery (ND). The nature of wireless communications, however, makes attacks against ND easy: An adversary can simply replay or relay (wormhole) packets across the network and mislead di ...

2009

Unraveling an Old Cloak: k-anonymity for Location Privacy

Jean-Pierre Hubaux, Julien Freudiger, Carmela González Troncoso, Reza Shokri

There is a rich collection of literature that aims at protecting the privacy of users querying location-based services. One of the most popular location privacy techniques consists in cloaking users' locations such that k users appear as potential senders ...

ACM2010

On the Tradeoff between Trust and Privacy in Wireless Ad Hoc Networks

Jean-Pierre Hubaux, Reza Shokri

As privacy moves to the center of attention in networked systems, and the need for trust remains a necessity, an important question arises: How do we reconcile the two seemingly contradicting requirements? In this paper, we show that the notion of data-cen ...

Acm Order Department, P O Box 64145, Baltimore, Md 21264 Usa2010

A Distortion-based Metric for Location Privacy

Jean-Pierre Hubaux, Murtuza Jadliwala, Julien Freudiger, Reza Shokri

We propose a novel framework for measuring and evaluating location privacy preserving mechanisms in mobile wireless networks. Within this framework, we first present a formal model of the system, which provides an efficient representation of the network us ...

2009