News 2020

Security & Privacy

Aastha Mehta accepts faculty position at University of British Columbia

September 2020
Aastha Mehta, a doctoral student in the Distributed Systems group and the Security & Privacy group, has accepted a position as a tenure-track assistant professor in the Department of Computer Science at University of British Columbia, Vancouver, Canada. Congratulations Aastha!

Aastha's research interests span systems security, data privacy, operating systems, and distributed systems. She has worked on building systems for ensuring policy compliance and for mitigating network side-channel leaks in online services. You can find out more about her work at https://people.mpi-sws.org/~aasthakm/.
Aastha Mehta, a doctoral student in the Distributed Systems group and the Security & Privacy group, has accepted a position as a tenure-track assistant professor in the Department of Computer Science at University of British Columbia, Vancouver, Canada. Congratulations Aastha!

Aastha's research interests span systems security, data privacy, operating systems, and distributed systems. She has worked on building systems for ensuring policy compliance and for mitigating network side-channel leaks in online services. You can find out more about her work at https://people.mpi-sws.org/~aasthakm/.
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Redmiles' research on ethical adoption of COVID19 apps gains international media attention

Research by MPI-SWS faculty member Elissa Redmiles and collaborators at Microsoft Research, the University of Zurich, the University of Maryland and Johns Hopkins University was featured in the New York Times, Scientific American (article 1article 2), Wired (article 1article 2), STAT News, and other venues.

The articles cover two papers: (1) Redmiles' paper in ACM Digital Government: Research and Practice proposing a framework and empirical validation through a large-scale survey of the attributes of COVID19 apps that may compel users to adopt them, ...
Research by MPI-SWS faculty member Elissa Redmiles and collaborators at Microsoft Research, the University of Zurich, the University of Maryland and Johns Hopkins University was featured in the New York Times, Scientific American (article 1article 2), Wired (article 1article 2), STAT News, and other venues.


The articles cover two papers: (1) Redmiles' paper in ACM Digital Government: Research and Practice proposing a framework and empirical validation through a large-scale survey of the attributes of COVID19 apps that may compel users to adopt them, such as the benefits of the apps both to individual users and to their community, the accuracy with which they detect exposures, potential privacy leaks, and the costs of using the apps; and (2) a preprint paper by Redmiles and her collaborators that develops predictive models of COVID19 app adoption based on an app's level of accuracy and privacy protection.


These works are part of a larger project Redmiles leads on ethical adoption of COVID 19 apps: https://covidadoptionproject.mpi-sws.org/.
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Article on the failure of Differential Privacy reaches 1000 views

January 2020
On January 9, 2020, MPI-SWS faculty member Paul Francis published the article Dear Differential Privacy: Put Up or Shut Up, on Medium. The article, which has now reached 1000 views, describes the failure of Differential Privacy as the basis for data protection in the Facebook / Social Sciences One project.

The Facebook / Social Sciences One project is an attempt to release Facebook data on URL sharing to researchers so as to better understand the role of Facebook in influencing elections. ...
On January 9, 2020, MPI-SWS faculty member Paul Francis published the article Dear Differential Privacy: Put Up or Shut Up, on Medium. The article, which has now reached 1000 views, describes the failure of Differential Privacy as the basis for data protection in the Facebook / Social Sciences One project.

The Facebook / Social Sciences One project is an attempt to release Facebook data on URL sharing to researchers so as to better understand the role of Facebook in influencing elections. The project raised 11 million dollars from private funders, and research grants were awarded to twelve research teams around the world. Facebook decided to use Differential Privacy as the means of anonymizing the data. After one year, however, Facebook had not supplied the data. When the funders threatened to pull the funding, Facebook did release a dataset, but the quality of the data was so poor that the proposed research could not be done.

Francis' article describes how and why the data release failed, discusses the shortcomings of Differential Privacy, and calls on the privacy research community to expand the scope of what passes for valid data anonymity research.
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