updated
authorChristian Urban <christian dot urban at kcl dot ac dot uk>
Thu, 05 Nov 2015 03:57:27 +0000
changeset 423 11b46fa92a85
parent 422 abe178b3197e
child 424 b59fba19738f
updated
handouts/ho06.pdf
handouts/ho06.tex
handouts/ho07.pdf
handouts/ho07.tex
slides/slides06.pdf
slides/slides06.tex
slides/slides07.pdf
slides/slides07.tex
Binary file handouts/ho06.pdf has changed
--- a/handouts/ho06.tex	Thu Nov 05 02:11:13 2015 +0000
+++ b/handouts/ho06.tex	Thu Nov 05 03:57:27 2015 +0000
@@ -593,8 +593,10 @@
 are.\footnote{\url{http://en.wikipedia.org/wiki/NP_(complexity)}}
 They are the building blocks for zero-knowledge proofs.
 Zero-Knowldege proofs are not yet widely used in production
-systems, but it is slowly gaining ground. One application
-where they pop up are crypto currencies.
+systems, but it is slowly gaining ground. One area of application
+where they pop up is crypto currencies (for example Zerocoins
+or how to make sure a Bitcoin exchange is solvent without
+revealing its assets).
 
 If you want to brush up on the modular logarithm problem,
 the Khan Academy has a nice video:
Binary file handouts/ho07.pdf has changed
--- a/handouts/ho07.tex	Thu Nov 05 02:11:13 2015 +0000
+++ b/handouts/ho07.tex	Thu Nov 05 03:57:27 2015 +0000
@@ -3,7 +3,7 @@
 \usepackage{../graphics}
 
 \begin{document}
-\fnote{\copyright{} Christian Urban, 2014}
+\fnote{\copyright{} Christian Urban, 2014, 2015}
 
 \section*{Handout 7 (Privacy)}
 
@@ -36,7 +36,7 @@
 print (or better the link ``About us'') reveals they set up
 their organisation so that they can also shamelessly sell the
 email addresses they ``harvest''. Everything is of course very
-legal\ldots{}moral?\ldots{}well that is in the eye of the
+legal\ldots{}ethical?\ldots{}well that is in the eye of the
 beholder. See:
 
 \url{http://www.ucas.com/about-us/inside-ucas/advertising-opportunities} 
@@ -119,7 +119,7 @@
 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
-about my private life usually is used against me. As mentioned
+about my private life can often be used against me. As mentioned
 above, public location data might mean I get robbed. If
 supermarkets build a profile of my shopping habits, they will
 use it to \emph{their} advantage---surely not to \emph{my}
@@ -132,7 +132,10 @@
 history data there 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.
+part of the data that is held about me/you. Also
+what about cases where data is wrong or outdated (but do we
+need a right-to be forgotten).
+
 
 To see how private matter can lead really to the wrong
 conclusions, take the example of Stephen Hawking: When he was
@@ -253,11 +256,12 @@
       published data. He was left with data that included all
       ``special'' DNA-markers of the individuals present in
       the original mixture. He essentially deleted the
-      ``background noise'' in the published data. The
-      problem with DNA data is that it is of such a high
-      resolution that even if the mixture contained maybe 100
-      individuals, you can now detect whether an individual
-      was included in the mixture or not.
+      ``background noise'' in the published data. The problem
+      with DNA data is that it is of such a high resolution
+      that even if the mixture contained maybe 100
+      individuals, you can with current technology detect
+      whether an individual was included in the mixture or
+      not.
       
       This result changed completely how DNA data is nowadays
       published for research purposes. After the success of 
@@ -342,9 +346,9 @@
 of Information Law the taxicab dataset of New York and someone
 else showed how easy it is to mine for private information: 
 
-\begin{center}
-\begin{tabular}{p{0.8\textwidth}}
-\url{http://chriswhong.com/open-data/foil_nyc_taxi/}\\
+\begin{center}\small
+\begin{tabular}{p{0.78\textwidth}}
+\url{http://chriswhong.com/open-data/foil_nyc_taxi/}\smallskip\\
 \url{http://research.neustar.biz/2014/09/15/riding-with-the-stars-passenger-privacy-in-the-nyc-taxicab-dataset}
 \end{tabular}
 \end{center}
@@ -359,7 +363,7 @@
 \end{center}
 
 \noindent An article that analyses privacy and shopping habits 
-from a more economic point is available from:
+from a more economic point of view is available from:
 
 \begin{center}
 \url{http://www.dtc.umn.edu/~odlyzko/doc/privacy.economics.pdf}
Binary file slides/slides06.pdf has changed
--- a/slides/slides06.tex	Thu Nov 05 02:11:13 2015 +0000
+++ b/slides/slides06.tex	Thu Nov 05 03:57:27 2015 +0000
@@ -486,7 +486,7 @@
   not yet right\bigskip
 
 \item most likely applied with digital cash 
-  (Bitcoins are not yet good enough)
+  (Bitcoins are not yet good enough, Zerocoins)
 
 \end{itemize}
 
@@ -494,6 +494,8 @@
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
 
+
+
 \end{document}
 
 %%% Local Variables:  
Binary file slides/slides07.pdf has changed
--- a/slides/slides07.tex	Thu Nov 05 02:11:13 2015 +0000
+++ b/slides/slides07.tex	Thu Nov 05 03:57:27 2015 +0000
@@ -20,7 +20,7 @@
 
   \normalsize
   \begin{center}
-  \begin{tabular}{ll}Ch
+  \begin{tabular}{ll}
   Email:  & christian.urban at kcl.ac.uk\\
   Office: & S1.27 (1st floor Strand Building)\\
   Slides: & KEATS (also homework is there)\\
@@ -59,7 +59,7 @@
 
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 \begin{frame}
-\frametitle{UCAS}
+\frametitle{UCAS (a charity)}
 \mbox{}\\[-15mm]\mbox{} 
 \small
 \begin{quote}
@@ -108,18 +108,18 @@
 Some terminology:
 
 \begin{itemize}
-\item \alert{secrecy} is the mechanism used to limit the
+\item \alert{\bf secrecy} is the mechanism used to limit the
       number of principals with access to information (e.g.,
       cryptography or access controls)
 
-\item \alert{confidentiality} is the obligation to protect the
+\item \alert{\bf confidentiality} is the obligation to protect the
       secrets of other people or organizations (secrecy for
       the benefit of an organisation)
 
-\item \alert{anonymity} is the ability to leave no evidence of
-      an activity (e.g., sharing a secret)
+\item \alert{\bf anonymity} is the ability to leave no evidence of
+      an activity (e.g., sharing a secret, whistle blowing)
 
-\item \alert{privacy} is the ability or right to protect your
+\item \alert{\bf privacy} is the ability or right to protect your
       personal secrets (secrecy for the benefit of an
       individual)
 
@@ -375,7 +375,10 @@
 \item could be cross referenced with public voter registration
       data in order to find out what the medical record of the
       governor of Massachusetts was (in 1997 Latanya Sweeney)
+      \bigskip
 
+      \small
+      (his record included diagnoses and prescriptions)
 \end{itemize}
 
 \end{frame}}
@@ -501,14 +504,13 @@
 \item Differential privacy is a ``protocol'' which you run on some dataset \bl{$X$} producing
 some output \bl{$O(X)$}.\bigskip
 
-\item You want to achieve \alert{forward privacy}
+\item You want to achieve \alert{\bf forward privacy}.
 \end{itemize}
 
 \end{frame}}
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 
 
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-\mode<presentation>{
 \begin{frame}[c]
 \frametitle{Differential Privacy}
 
@@ -537,7 +539,7 @@
 \end{center} 
 \end{itemize}
 
-\end{frame}}
+\end{frame}
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 
 
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
@@ -619,13 +621,13 @@
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 
 
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-\begin{frame}[c]
-\frametitle{Tor}
-
-\begin{center}
-??
-\end{center}
-\end{frame}
+%\begin{frame}[c]
+%\frametitle{Tor}
+%
+%\begin{center}
+%??
+%\end{center}
+%\end{frame}
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%