May 22, 2017

Archives for January 2015

Anonymous programmers can be identified by analyzing coding style

Every programmer learns to code in a unique way which results in distinguishing “fingerprints” in coding style. These fingerprints can be used to compare the source code of known programmers with an anonymous piece of source code to find out which one of the known programmers authored the anonymous code. This method can aid in finding malware programmers or detecting cases of plagiarism. In a recent paper, we studied this question, which we call source-code authorship attribution. We introduced a principled method with a robust feature set and achieved a breakthrough in accuracy.

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Shaping Wi-Fi’s future: the wireless-mobile convergence

According to recent news, Comcast is being sued because it is taking advantage of users’ resources to build up its own nationwide Wi-Fi network. Since mid-2013 the company has been updating consumers’ routers by installing new firmware that makes the router partially devoted to the “home-user” network and partially devoted to the “mobile-user” network (a Comcast service named Xfinity WiFi). In fact, the same network infrastructure offers two different kinds of connection: the first one covers a comparatively restricted (local) area and stays under the relative control of the private end-user; the second kind of connection is “shared” between Comcast customers and covers a wider area, compatible with the range of national mobile carriers. In other words: the last mile of data transmission is being made mostly by a group of home based routers (or access points) that offers two different Internet connection services, the local “private” network and the metropolitan “shared” network.

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Verizon's tracking header: Can they do better?

Verizon’s practice of injecting a unique ID into the HTTP headers of traffic originating on their wireless network has alarmed privacy advocates and researchers. Jonathan Mayer detailed how this header is already being used by third-parties to create zombie cookies. In this post, I summarize just how much information Verizon collects and shares under their marketing programs. I’ll show how the implementation of the header makes previous tracking methods trivial and explore the possibility of a more secure design.

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