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by Pavlos Efraimidis

PrivacyStreams Helps Developers Create Privacy Friendly Apps | Carnegie Mellon School of Computer Science

PrivacyStreams Helps Developers Create Privacy Friendly Apps

Decision To Share Personal Data Need Not Be All or Nothing

A smartphone app that uses the raw feed from a device’s microphone or accesses its contact list can raise red flags for a user concerned about privacy. In many cases, however, the app doesn’t need all the details that users find most sensitive.

Researchers at Carnegie Mellon and Peking universities have addressed this dilemma by creating a service, PrivacyStreams, that enables app developers to access the smartphone data they need for app functionality while assuring users that their private information isn’t being sold to an online marketer or otherwise revealed.

A sleep-monitoring app, for instance, might need to access the smartphone’s microphone, but only to register loudness, not to monitor conversations. An app developer could simply sample the microphone feed every minute or so, use software in the PrivacyStreams library to transform the raw data to loudness and then send just the loudness data back to the smartphone for use by the app.

Source: PrivacyStreams Helps Developers Create Privacy Friendly Apps | Carnegie Mellon School of Computer Science

by Pavlos Efraimidis

European Commission : CORDIS : News and Events : How you handle your phone gives away more than you think

European Commission

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The EU-funded AMBER (Enhanced Mobile Biometrics) project has done just this. The project has shown it can identify gender by breaking down gestures and analysing the way in which users swipe screens using multiple datasets. In a recently published paper the team detail the software and protocol used for data collection, the feature set extracted and subsequent machine learning analysis. The results of this exploratory analysis have confirmed the possibility of sex prediction from the swipe gesture data, obtaining an encouraging 78% accuracy rate using swipe gesture data from two different directions.

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Source: European Commission : CORDIS : News and Events : How you handle your phone gives away more than you think

by Pavlos Efraimidis

Sexism and Shopping: Female Players Get Most of the Odd Questions at the U.S. Open – The New York Times

A study casts a light not just on gender bias, but also on how algorithms work.

The tennis finals of the United States Open are Saturday for the women and Sunday for the men. On the court, except for the number of sets, they all face the same rules. When they walk off the court, though, the game changes.

Source: Sexism and Shopping: Female Players Get Most of the Odd Questions at the U.S. Open – The New York Times

by Pavlos Efraimidis

The political blogosphere and the 2004 U.S. election: divided they blog

PoliticalBlogosphere2004In this paper, we study the linking patterns and discussion topics of political bloggers. Our aim is to measure the degree of interaction between liberal and conservative blogs, and to uncover any differences in the structure of the two communities. Specifically, we analyze the posts of 40 “A-list” blogs over the period of two months preceding the U.S. Presidential Election of 2004, to study how often they referred to one another and to quantify the overlap in the topics they discussed, both within the liberal and conservative communities, and also across communities. We also study a single day snapshot of over 1,000 political blogs. This snapshot captures blogrolls (the list of links to other blogs frequently found in sidebars), and presents a more static picture of a broader blogosphere. Most significantly, we find differences in the behavior of liberal and conservative blogs, with conservative blogs linking to each other more frequently and in a denser pattern.

http://dx.doi.org/10.1145/1134271.1134277