LPW 2021

The 3rd Location Privacy Workshop (LPW 2021)

to be held in conjunction with the 16 th International Conference on Availability, Reliability and Security
(ARES 2021 – http://www.ares-conference.eu )

August 17 – August 20, 2021

Location and mobility data are highly sensitive, as they can be used to infer a number of other personal and sensitive data on an individual. However, human mobility is highly predictable, and location information is routinely collected by location-aware devices (e.g. smartphones), connected vehicles and smart transportation systems, e-tolling, and cameras with face recognition among others.

Location privacy is a rapidly developing research area, and the second Location Privacy Workshop (LPW) provides a platform for original research and discussion on all technical aspects of privacy and security of location-based services.

Topics of interest include, but are not limited to:

Security of location-aware mobile devices
Privacy-enhancing technologies for location-based services
Privacy and anonymity in (public) transportation systems
Privacy in connected autonomous vehicles
Security of smart mobility applications
Privacy in location-aware social media
Privacy in position-based advertising
Malicious and pervasive tracking

De-anonymization of location traces
Cryptographic protocols and schemes for location information
Data structures for location information
Security and reliability of positioning systems
Location verification and authentication
Location forensics
Data protection techniques for regulatory (GDPR) compliance
Location-based contact tracing

Important Dates
Submission Deadline April 30, 2021
New deadline May 17, 2021
Author Notification June 07, 2021
Proceedings Version June 13, 2021
ARES EU Symposium August 17, 2021
All-Digital Conference August 17 – August 20, 2021
Program Chairs

Paolo Palmieri
University College Cork, Ireland

Luca Calderoni
University of Bologna, Italy

Program Committee Members 2020

Antoine Boutet, INSA de Lyon, France
Matthew Bradbury, Lancaster University, United Kingdom
Zekeriya Erkin, Delft University of Technology, The Netherlands
Sébastien Gambs, Université du Québec à Montréal, Canada
Prosanta Gope, University of Sheffield, United Kingdom
Kimmo Järvinen, University of Helsinki, Finland
Ioannis Krontiris, Huawei European Research Center, Germany
Jun Pang ‒ University of Luxembourg, Luxembourg
Raúl Pardo – IT University of Copenhagen, Denmark
Constantinos Patsakis, University of Piraeus, Greece
Francesco Regazzoni, University of Lugano, Switzerland
Julián Salas Piñón, Universitat Oberta de Catalunya, Spain
George Theodorakopoulos, Cardiff University, United Kingdom
Rolando Trujillo Rasúa, Deakin University, Australia
Isabel Wagner, De Montfort University, United Kingdom

Submission Guidelines

The submission guidelines valid for the workshop are the same as for the ARES conference. They can be found at https://www.ares-conference.eu/conference/submission/ .


The Impact of AI on Location Privacy

Stephen B. Wicker, Professor of Electrical and Computer Engineering at Cornell University, USA

Abstract: Advances in artificial intelligence have made the ready availability of fine-grained location data increasingly problematic.  In this talk we will focus on two branches of AI research – hypothesis testing and constraint satisfaction –  to show the social and legal issues that arise from the availability of location data.  We begin with a review of the collection of increasingly fine-grained location data by cellular service providers. This collection began from the outset with the use of registration messages to associate handsets with location areas, and has evolved through GPS to the potential for “charting” in 5G massive MIMO systems.  We then consider the larger problem of app providers and their collection, packaging, and sale of GPS location data. Though this data is allegedly anonymized, a de-anonymization industry has arisen that eliminates whatever minimal protection existed for the user.  Given the availability of such data sets, we will explore the societal and legal impact of hypothesis testing and constraint satisfaction, showing how advanced AI algorithms eliminate legal protections and create clear and present dangers for the consumer.

Stephen B. Wicker is a Professor of Electrical and Computer Engineering at Cornell University, and a member of the graduate fields of Computer Science and Applied Mathematics. Professor Wicker is the author of Cellular Convergence and the Death of Privacy (Oxford University Press, 2013), Codes, Graphs, and Iterative Decoding (Kluwer, 2002), Turbo Coding (Kluwer, 1999), Error Control Systems for Digital Communication and Storage (Prentice Hall, 1995) and Reed-Solomon Codes and Their Applications (IEEE Press, 1994). He has served as Associate Editor for Coding Theory and Techniques for the IEEE Transactions on Communications , and Associate Editor for the ACM Transactions on Sensor Networks .

From 2005 – 2018 Professor Wicker was the Cornell Principal Investigator for the TRUST Science and Technology Center – a National Science Foundation center dedicated to the development of technologies for securing the nation’s critical infrastructure.  In 2010 Professor Wicker briefed the staff of the Congressional Committee on Science and Technology.  In 2014 he briefed the National Economic Council at the White House on the subject of privacy-aware designs for cellular and the smart grid.  His current research focuses on privacy and security in information systems,  with an emphasis on the legal, social, and ethical impact of design decisions in wireless networks.

In 2011 Professor Wicker was made a Fellow of the IEEE for “contributions to wireless information systems.”