Links for 2015-01-30

  • H.P. Lovecat

    Because there exists no method known to man, more terribly suited to expose the cosmic meaningless of existence than pairing the words of H.P. Lovecraft with seemingly delightful and charming pictures of adorable kittens.

    (tags: lovecraft cthulhu horror funny kittens cats images gif)

  • 8 gdb tricks you should know (Ksplice Blog)

    These are very good — bookmarking for the next time I’m using gdb, probably about 3 years from now

    (tags: c debugging gdb c++ tips coding)

  • EFF’s Game Plan for Ending Global Mass Surveillance

    For years, we’ve been working on a strategy to end mass surveillance of digital communications of innocent people worldwide. Today we’re laying out the plan, so you can understand how all the pieces fit together—that is, how U.S. advocacy and policy efforts connect to the international fight and vice versa. Decide for yourself where you can get involved to make the biggest difference. This plan isn’t for the next two weeks or three months. It’s a multi-year battle that may need to be revised many times as we better understand the tools and authorities of entities engaged in mass surveillance and as more disclosures by whistleblowers help shine light on surveillance abuses.

    (tags: eff privacy nsa surveillance gchq law policy us-politics)

  • No POD

    This group aims to consolidate opposition, give clear information and support letter writing and information awareness against the Dept. of Education’s Primary Online Database.

    (tags: pod ireland privacy data-protection children kids schools)

  • Apple Pay suffering fraud problems

    Fraud in Apple Pay will in time, come to be managed – but the fact that easily available PII can waylay best in class protection should give us all pause.

    (tags: fraud apple apple-pay pii identity-theft)

  • Excellent example of failed “anonymisation” of a dataset

    Fred Logue notes how this failed Mayo TD Michelle Mulherin:

    From recent reports it mow appears that the Department of Education is discussing anonymisation of the Primary Online Database with the Data Protection Commissioner. Well someone should ask Mayo TD Michelle Mulherin how anonymisation is working for her. The Sunday Times reports that Ms Mulherin was the only TD in the Irish parliament on the dates when expensive phone calls were made to a mobile number in Kenya. The details of the calls were released under the Freedom of Information Act in an “anonymised” database. While it must be said the fact that Ms Mulherin was the only TD present on those occasions does not prove she made the calls – the reporting in the press is now raising the possibility that it was her. From a data protection point of view this is a perfect example of the difficulty with anonymisation. Data protection rules apply to personal data which is defined as data relating to a living individual who is or can be identified from the data or from the data in conjunction with other information. Anonymisation is often cited as a means for processing data outside the scope of data protection law but as Ms Mulherin has discovered individuals can be identified using supposedly anonymised data when analysed in conjunction with other data. In the case of the mysterious calls to Kenya even though the released information was “anonymised” to protect the privacy of public representatives, the phone log used in combination with the attendance record of public representatives and information on social media was sufficient to identify individuals and at least raise evidence of association between individuals and certain phone calls. While this may be well and good in terms of accounting for abuses of the phone service it also has worrying implications for the ability of public representatives to conduct their business in private. The bottom line is that anonymisation is very difficult if not impossible as Ms Mulherin has learned to her cost. It certainly is a lot more complex than simply removing names and other identifying features from a single dataset. The more data that there is and the more diverse the sources the greater the risk that individuals can be identified from supposedly anonymised datasets.

    (tags: data anonymisation fred-logue ireland michelle-mulherin tds kenya data-protection privacy)

This entry was posted in Uncategorized. Bookmark the permalink. Both comments and trackbacks are currently closed.