324 also looked up diseases that her friends had, which had |
324 also looked up diseases that her friends had, which had |
325 nothing to do with her. Any rational analysis of her query |
325 nothing to do with her. Any rational analysis of her query |
326 data must therefore have concluded, the lady is on her |
326 data must therefore have concluded, the lady is on her |
327 death bed, while she was actually very much alive and kicking. |
327 death bed, while she was actually very much alive and kicking. |
328 |
328 |
|
329 In 2016, Yahoo released the so far largest machine learning |
|
330 dataset to the research community. It includes approximately |
|
331 13.5 TByte of data representing around 100 Billion events from |
|
332 anonymized user-news items, collected by recording |
|
333 interactions of about 20M users from February 2015 to May |
|
334 2015. Yahoo's gracious goal is to promote independent research |
|
335 in the fields of large-scale machine learning and recommender |
|
336 systems. It remains to be seen whether this data will really |
|
337 only be used for that purpose. |
|
338 |
329 \subsubsection*{Differential Privacy} |
339 \subsubsection*{Differential Privacy} |
330 |
340 |
331 Differential privacy is one of the few methods that tries to |
341 Differential privacy is one of the few methods that tries to |
332 achieve forward privacy. The basic idea is to add appropriate |
342 achieve forward privacy. The basic idea is to add appropriate |
333 noise, or errors, to any query of the dataset. The intention |
343 noise, or errors, to any query of the dataset. The intention |