Four short links: 25 February 2015

Bricking Cars, Mapping Epigenome, Machine Learning from Encrypted Data, and Phone Privacy

  1. Remotely Bricking Cars (BoingBoing) — story from 2010 where an intruder illegally accessed Texas Auto Center’s Web-based remote vehicle immobilization system and one by one began turning off their customers’ cars throughout the city.
  2. Beginning to Map the Human Epigenome (MIT) — Kellis and his colleagues report 111 reference human epigenomes and study their regulatory circuitry, in a bid to understand their role in human traits and diseases. (The paper itself.)
  3. Machine Learning Classification over Encrypted Data (PDF) — It is worth mentioning that our work on privacy-preserving classification is complementary to work on differential privacy in the machine learning community. Our work aims to hide each user’s input data to the classification phase, whereas differential privacy seeks to construct classifiers/models from sensitive user training data that leak a bounded amount of information about each individual in the training data set. See also The Morning Paper’s unpacking of it.
  4. Privacy of Phone Audio (Reddit) — unconfirmed report from Redditor I started a new job today with Walk N’Talk Technologies. I get to listen to sound bites and rate how the text matches up with what is said in an audio clip and give feed back on what should be improved. At first, I though these sound bites were completely random. Then I began to notice a pattern. Soon, I realized that I was hearing peoples commands given to their mobile devices. Guys, I’m telling you, if you’ve said it to your phone, it’s been recorded…and there’s a damn good chance a 3rd party is going to hear it.
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