updated
authorChristian Urban <christian dot urban at kcl dot ac dot uk>
Mon, 17 Nov 2014 18:49:13 +0000
changeset 314 e01f55e7485a
parent 313 1d243ac51078
child 315 7bd723cb9b32
updated
handouts/ho07.pdf
handouts/ho07.tex
hws/hw05.pdf
hws/hw05.tex
Binary file handouts/ho07.pdf has changed
--- a/handouts/ho07.tex	Fri Nov 14 23:04:40 2014 +0000
+++ b/handouts/ho07.tex	Mon Nov 17 18:49:13 2014 +0000
@@ -1,16 +1,17 @@
 \documentclass{article}
 \usepackage{../style}
+\usepackage{../graphics}
 
 \begin{document}
 
 \section*{Handout 7 (Privacy)}
 
 The first motor car was invented around 1886. For ten years,
-until 1896, the law in the UK and elsewhere required a person
-to walk in front of any moving car waving a red flag. Cars
-were such a novelty that most people did not know what to make
-of them. The person with the red flag was intended to warn the
-public, for example horse owners, about the impending
+until 1896, the law in the UK (and elsewhere) required a
+person to walk in front of any moving car waving a red flag.
+Cars were such a novelty that most people did not know what to
+make of them. The person with the red flag was intended to
+warn the public, for example horse owners, about the impending
 novelty---a car. In my humble opinion, we are at the same
 stage of development with privacy. Nobody really knows what it
 is about or what it is good for. All seems very hazy. There
@@ -18,23 +19,24 @@
 which address problems with privacy, but even if they are well
 intentioned, they either back-fire or are already obsolete
 because of newer technologies. The result is that the world of
-``privacy'' looks a little bit like the old Wild West.
+``privacy'' looks a little bit like the old Wild
+West---lawless and mythical.
 
 For example, UCAS, a charity set up to help students with
 applying to universities, has a commercial unit that happily
 sells your email addresses to anybody who forks out enough
-money in order to be able to bombard you with spam. Yes, you
-can opt out very often in such ``schemes'', but in case of
-UCAS any opt-out will limit also legit emails you might
-actually be interested in.\footnote{The main objectionable
-point, in my opinion, is that the \emph{charity} everybody has
-to use for HE applications has actually very honourable goals
-(e.g.~assist applicants in gaining access to universities),
-but the small 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 beholder. See:
+money for bombarding you with spam. Yes, you can opt out very
+often from such ``schemes'', but in case of UCAS any opt-out
+will limit also legit emails you might actually be interested
+in.\footnote{The main objectionable point, in my opinion, is
+that the \emph{charity} everybody has to use for HE
+applications has actually very honourable goals (e.g.~assist
+applicants in gaining access to universities), but the small
+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
+beholder. See:
 
 \url{http://www.ucas.com/about-us/inside-ucas/advertising-opportunities} 
 or
@@ -53,10 +55,10 @@
 this request, that is you.
  
 \begin{center}
-\includegraphics[scale=0.19]{../pics/verizon.png}
+\includegraphics[scale=0.17]{../pics/verizon.png}
 \end{center}
 
-\noindent How disgusting? Even worse, Verizon is not known for
+\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
@@ -137,25 +139,25 @@
 two years. If employers 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.
-A movie which has this topic as its main focus is Gattaca from
-1997, in case you like to watch
-it.\footnote{\url{http://www.imdb.com/title/tt0119177/}}
-
 
 To cut a long story short, I let you ponder about the two
-statements that are often voiced in discussions about privacy:
+statements which are often voiced in discussions about privacy:
 
 \begin{itemize}
-\item \textit{``You have zero privacy anyway. Get over it.''}
-\mbox{}\hfill{}{\small{}by Scott Mcnealy (CEO of Sun)}
+\item \textit{``You have zero privacy anyway. Get over 
+it.''}\\
+\mbox{}\hfill{}{\small{}(by Scott Mcnealy, former CEO of Sun)}
 
 \item \textit{``If you have nothing to hide, you have nothing 
 to fear.''}
 \end{itemize}
  
-\noindent If you want to read up further on this topic, I can
-recommend the following article that appeared in 2011 in the
-Chronicle of Higher Education
+\noindent If you like to watch a movie which has this topic as
+its main focus I recommend \emph{Gattaca} from
+1997.\footnote{\url{http://www.imdb.com/title/tt0119177/}} If
+you want to read up on this topic, I can recommend the
+following article that appeared in 2011 in the Chronicle of
+Higher Education:
 
 \begin{center} 
 \url{http://chronicle.com/article/Why-Privacy-Matters-Even-if/127461/} 
@@ -281,39 +283,74 @@
 also looked up diseases that her friends had, which had
 nothing to do with her. Any rational analysis of her query
 data must therefore have concluded, the lady is on her
-deathbed, while she was actually very much alive and kicking.
+death bed, while she was actually very much alive and kicking.
 
 \subsubsection*{Differential Privacy}
 
-Differential privacy is one of the few methods, that tries to 
-achieve forward privacy with large datasets. The basic idea
-is to add appropriate noise, or errors, to any query of the
-dataset. The intention is to make the result of a query 
-insensitive to individual entries in the database. The hope is
-that the added error does not eliminate the ``signal'' one is 
-looking for by querying the dataset.
-
-
+Differential privacy is one of the few methods that tries to
+achieve forward privacy. The basic idea is to add appropriate
+noise, or errors, to any query of the dataset. The intention
+is to make the result of a query insensitive to individual
+entries in the database. That means the results are
+approximately the same no matter if a particular individual is
+in the dataset or not. The hope is that the added error does
+not eliminate the ``signal'' one is looking for in the
+dataset.
 
-\begin{center}
-User\;\;\;\;    
-\begin{tabular}{c}
-tell me $f(x)$ $\Rightarrow$\\
-$\Leftarrow$ $f(x) + \text{noise}$
-\end{tabular}
-\;\;\;\;\begin{tabular}{@{}c}
-Database\\
-$x_1, \ldots, x_n$
-\end{tabular}
-\end{center}
+%\begin{center}
+%User\;\;\;\;    
+%\begin{tabular}{c}
+%tell me $f(x)$ $\Rightarrow$\\
+%$\Leftarrow$ $f(x) + \text{noise}$
+%\end{tabular}
+%\;\;\;\;\begin{tabular}{@{}c}
+%Database\\
+%$x_1, \ldots, x_n$
+%\end{tabular}
+%\end{center}
+%
+%\begin{center}
+%\begin{tabular}{l|l}
+%Staff & Salary\\\hline
+%$PM$ & \pounds{107}\\
+%$PF$ & \pounds{102}\\
+%$LM_1$ & \pounds{101}\\
+%$LF_2$ & \pounds{97}\\
+%$LM_3$ & \pounds{100}\\
+%$LM_4$ & \pounds{99}\\
+%$LF_5$ & \pounds{98}
+%\end{tabular}
+%\end{center}
+%
+%
+%\begin{center}
+%\begin{tikzpicture} 
+%\begin{axis}[symbolic y coords={salary},
+%             ytick=data,
+%             height=3cm]
%\addplot+[jump mark mid] coordinates
%{(0,salary)   (0.1,salary) 
% (0.4,salary) (0.5,salary)  
% (0.8,salary) (0.9,salary)};
%\end{axis}
%\end{tikzpicture}
+%\end{center}
+%
+%\begin{tikzpicture}[outline/.style={draw=#1,fill=#1!20}]
%  \node [outline=red]            {red box};
%  \node [outline=blue] at (0,-1) {blue box};
%\end{tikzpicture}
 
 \ldots
 
 
 \subsubsection*{Further Reading}
 
+Two cool articles about how somebody obtained via the Freedom
+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/}\\
+\url{http://research.neustar.biz/2014/09/15/riding-with-the-stars-passenger-privacy-in-the-nyc-taxicab-dataset}
+\end{tabular}
+\end{center}
+
+\noindent 
 A readable article about how supermarkets mine your shopping
-habits (especially how they prey on young exhausted families
+habits (especially how they prey on new exhausted parents
 ;o) appeared in 2012 in the New York Times:
 
 \begin{center}
@@ -349,6 +386,8 @@
 http://chronicle.com/article/Why-Privacy-Matters-Even-if/127461/
 http://repository.cmu.edu/cgi/viewcontent.cgi?article=1077&context=hcii
 https://josephhall.org/papers/NYU-MCC-1303-S2012_privacy_syllabus.pdf
+http://www.jetlaw.org/wp-content/uploads/2014/06/Bambauer_Final.pdf
+
 %%% Local Variables: 
 %%% mode: latex
 %%% TeX-master: t
Binary file hws/hw05.pdf has changed
--- a/hws/hw05.tex	Fri Nov 14 23:04:40 2014 +0000
+++ b/hws/hw05.tex	Mon Nov 17 18:49:13 2014 +0000
@@ -69,12 +69,12 @@
 key transponder: 
 
 \begin{enumerate}
-\item $C$ generates a random number $r$
-\item $C$ calculates $(F,G) = \{r\}_K$
-\item $C \to T$: $r, F$
-\item $T$ calculates $(F',G') = \{r\}_K$
+\item $C$ generates a random number $N$
+\item $C$ calculates $(F,G) = \{N\}_K$
+\item $C \to T$: $N, F$
+\item $T$ calculates $(F',G') = \{N\}_K$
 \item $T$ checks that $F = F'$
-\item $T \to C$: $r, G'$
+\item $T \to C$: $N, G'$
 \item $C$ checks that $G = G'$
 \end{enumerate}