sen-material: comparison handouts/ho07.tex

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 \noindent How disgusting? Even worse, Verizon is not known for
 being the cheapest ISP on the planet (completely the
 contrary), and also not known for providing the fastest
 possible speeds, but rather for being among the few ISPs in
 the US with a quasi-monopolistic ``market distribution''.
 Well, we could go on and on\ldots{}and that has not even
 started us yet with all the naughty things NSA \& Friends are
-up to.
+up to. Why does privacy matter? Nobody, I think, has a
+conclusive answer to this question yet. Maybe the following four
-Why does privacy matter? Nobody, I think, has a conclusive
+notions help with clarifying the overall picture somewhat:
-answer to this question. Maybe the following four notions
-help with clarifying the overall picture somewhat:
 \begin{itemize}
 \item \textbf{Secrecy} is the mechanism used to limit the
 number of principals with access to information (e.g.,
 cryptography or access controls). For example I better
 \end{itemize}
 \noindent While this might provide us with some rough
 definitions, the problem with privacy is that it is an
 extremely fine line what should stay private and what should
-not. For example, since I am working in academia, I am very
+not. For example, since I am working in academia, I am every
-happy to be a digital exhibitionist: I am very happy to
+so often very happy to be a digital exhibitionist: I am very
-disclose all `trivia' related to my work on my personal
+happy to disclose all `trivia' related to my work on my
-web-page. This is a kind of bragging that is normal in
+personal web-page. This is a kind of bragging that is normal
-academia (at least in the field of CS), even expected if you
+in academia (at least in the field of CS), even expected if
-look for a job. I am even happy that Google maintains a
+you look for a job. I am even happy that Google maintains a
 profile about all my academic papers and their citations.
 On the other hand I would be very irritated if anybody I do
 not know had a too close look on my private live---it
 shouldn't be anybody's business. The reason is that knowledge
 is, since recently, a law that allows you to check what
 information is held about you for determining your
 creditworthiness. But this concerns only a very small part of
 the data that is held about me/you.
+Take the example of Stephen Hawking: when he was diagnosed
+with his disease, he was given a life expectancy of two years.
+If an employer would know about such problems, would they have
+employed Hawking? Now he is enjoying his 70+ birthday.
+Clearly personal medical data needs to stay private.
 To cut a long story short, I let you ponder about the two
 statements that often voiced in discussions about privacy:
 \begin{itemize}
 \item \textit{``You have zero privacy anyway. Get over it.''}\\
 article carefully tries to construct an argument that does not
 only attack the nothing-to-hide statement in cases where
 governments \& Co collect people's deepest secrets, or
 pictures of people's naked bodies, but an argument that
 applies also in cases where governments ``only'' collect data
-relevant to, say, preventing terrorism. The fun is of course,
+relevant to, say, preventing terrorism. The fun is of course
-in 2011 we could just not imagine that respected governments
+that in 2011 we could just not imagine that respected
-would do such infantile things as intercepting people's nude
+governments would do such infantile things as intercepting
-photos. Well, since Snowden we know some people at the NSA did
+people's nude photos. Well, since Snowden we know some people
-and then shared such photos among colleagues as ``fringe
+at the NSA did exactly that and then shared such photos among
-benefit''.
+colleagues as ``fringe benefit''.
 \subsubsection*{Re-Identification Attacks}
-Apart from philosophical arguments, there are fortunately also
+Apart from philosophical musings, there are fortunately also
-some real technical problems with privacy implications. The
+some real technical problems with privacy. The problem I want
-problem I want to focus on in this handout is how to safely
+to focus on in this handout is how to safely disclose datasets
-disclose datasets containing potentially private data, say
+containing potentially private data, say health data. What can
-health data. What can go wrong with such disclosures can be
+go wrong with such disclosures can be illustrated with four
-illustrated with four examples:
+well-known examples:
 \begin{itemize}
 \item In 2006, a then young company called Netflix offered a 1
 Mio \$ prize to anybody who could improve their movie
 rating algorithm. For this they disclosed a dataset
 dataset: either by their ratings or by the dates the
 ratings were uploaded. The result was a class-action
 suit against Netflix, which was only recently resolved
 involving a lot of money.
-\item In the 1990ies, medical datasets were often made public for
+\item In the 1990ies, medical datasets were often made public
-research purposes. This was done in anonymised form with
+for research purposes. This was done in anonymised form
-names removed, but birth dates, gender, ZIP-code were
+with names removed, but birth dates, gender, ZIP-code
-retained. In one case where such data was made public
+were retained. In one case where such data about
-about state employees in Massachusetts, the then
+hospital visits of state employees in Massachusetts was
-governor assured the public that the released dataset
+made public, the then governor assured the public that
-protected patient privacy by deleting identifiers. A
+the released dataset protected patient privacy by
-graduate student could not resist and cross-referenced
+deleting identifiers. A graduate student could not
-public voter data with the data about birth dates,
+resist cross-referencing public voter data with the
-gender, ZIP-code. The result was that she could send
+released data including birth dates, gender and
-the governor his own hospital record.
+ZIP-code. The result was that she could send the
+governor his own hospital record. It turns out that
+birth dates, gender and ZIP-code uniquely identify 87\%
+people in the US.
 \item In 2006, AOL published 20 million Web search queries
-collected of 650,000 users (names had been deleted).
+collected from 650,000 users (names had been deleted).
-This was again for research purposes. However, within
+This was again done for research purposes. However,
-days an old lady, Thelma Arnold, from Lilburn, Georgia,
+within days an old lady, Thelma Arnold, from Lilburn,
-(11,596 inhabitants) was identified as user No.~4417749
+Georgia, (11,596 inhabitants) was identified as user
-in this dataset. It turned out that search engine
+No.~4417749 in this dataset. It turned out that search
-queries are windows into people's private lives.
+engine queries are deep windows into people's private
+lives.
 \item Genomic-Wide Association Studies (GWAS) was a public
 database of gene-frequency studies linked to diseases.
 you only needed partial DNA information in order to
 identify whether an individual was part of the study —
 DB closed in 2008
 \end{itemize}

changeset 310	591b62e1f86a
parent 309	b1ba3d88696e
child 311	8befc029ca1e