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\renewcommand{\slidecaption}{APP 07, King's College London}

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\begin{frame}[t]

\frametitle{%

  \begin{tabular}{@ {}c@ {}}

  \\

  \LARGE Access Control and \\[-3mm] 

  \LARGE Privacy Policies (7)\\[-6mm] 

  \end{tabular}}\bigskip\bigskip\bigskip

  \normalsize

  \begin{center}

  \begin{tabular}{ll}

  Email:  & christian.urban at kcl.ac.uk\\

  Office: & S1.27 (1st floor Strand Building)\\

  Slides: & KEATS (also homework is there)\\

  \end{tabular}

  \end{center}

\end{frame}

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\begin{frame}[t]

\frametitle{Facebook Privacy}

\begin{itemize}

\item \large Who has a Facebook account?\pause\medskip

\item \large Who keeps the list of friends private?\pause\medskip

\item \large Who knows that this is completely pointless?

\textcolor{gray}{\small (at least at the end of 2013)}\pause\medskip

\end{itemize}

\only<4>{Create a fake account. Send a friend-request.

Facebook answers with ``People you may know'' feature.

Conveniently, it has also a ``see all'' button.}

\only<5>{\small\it ``Our policies explain that changing the

visibility of people on your friend list controls how they

appear on your Timeline, and that your friends may be visible

on other parts of the site, such as in News Feed, Search and

on other people's Timelines. This behavior is something we'll

continue to evaluate to make sure we're providing clarity.'' }

\end{frame}

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\begin{frame}

\frametitle{UCAS}

\mbox{}\\[-15mm]\mbox{} 

\small

\begin{quote}

The Universities and Colleges Admissions Service received more

than \pounds{12m} last year in return for sending targeted advertising

to subscribers as young as 16.

The service, which controls admissions to UK universities and

attracts 700,000 new applicants each year, sells the access

via its commercial arm, Ucas Media.

Vodafone, O2, Microsoft and the private university

accommodation provider Pure Student Living are among those who

have marketed through Ucas, which offers access to over a

million student email addresses\ldots 

Applicants can opt out of receiving direct marketing, but only

at the cost of missing out on education and careers mailings

as well.\bigskip\\

\footnotesize\hfill The Guardian, 12 March 2014

\end{quote}

\end{frame}

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\begin{frame}

\frametitle{Verizon}

\mbox{}\\[-23mm]\mbox{} 

\begin{center}

\includegraphics[scale=0.21]{../pics/verizon.png}

\end{center}

\vfill\footnotesize

\url{http://webpolicy.org/2014/10/24/how-verizons-advertising-header-works}

\end{frame}

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\begin{frame}[c]

\frametitle{Privacy, Anonymity et al}

Some terminology:

\begin{itemize}

\item \alert{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 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{privacy} is the ability or right to protect your personal secrets 

(secrecy for the benefit of an individual)

\end{itemize}

\end{frame}

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\begin{frame}[t]

\frametitle{Privacy vs Anonymity}

\begin{itemize}

\item everybody agrees that anonymity has its uses (e.g., voting, whistleblowers, peer-review, exams)

\end{itemize}\bigskip\bigskip\pause

But privacy?\bigskip\bigskip

``You have zero privacy anyway. Get over it.''\\

\hfill{}Scott Mcnealy (CEO of Sun)\bigskip\\

``If you have nothing to hide, you have nothing to fear.''

\end{frame}

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\begin{frame}[t]

\frametitle{Privacy}

Private data can be often used against me

\begin{itemize}

\item if my location data becomes public, thieves will switch off their phones and help themselves in my home

\item if supermarkets can build a profile of what I buy, they can use it to their advantage (banks - mortgages)

\item my employer might not like my opinions\bigskip\pause

\item one the other hand, Freedom-of-Information Act 

\item medical data should be private, but medical research needs data

\end{itemize}

\end{frame}

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\begin{frame}[t]

\frametitle{Privacy Problems}

\begin{itemize}

\item Apple takes note of every Siri dictation (sent over the 

  Internet to Apple; retained for 2 years)

\item markets often only work, if data is restricted (to build trust)

\item social networks can reveal data about you 

\item have you tried the collusion (lightbeam?) extension for FireFox?

\item I do use Dropbox, store cards

\end{itemize}

\begin{textblock}{5}(12,9.9)

\includegraphics[scale=0.2]{../pics/gattaca.jpg}\\

\small Gattaca (1997)

\end{textblock}

\end{frame}

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\begin{frame}[t]

\frametitle{Privacy}

\begin{minipage}{1.05\textwidth}

\begin{itemize}

\item we \alert{do} want that government data is made public (free maps for example)

\item we \alert{do not} want that medical data becomes public (similarly tax data, school 

records, job offers)\bigskip

\item personal information can potentially lead to fraud 

(identity theft)

\end{itemize}\pause

{\bf ``The reality'':}

\only<2>{\begin{itemize}

\item London Health Programmes lost in 2011 unencrypted

      details of more than 8 million people (no names, but

      postcodes and details such as gender, age and ethnic

      origin)

\end{itemize}}

\only<3>{\begin{itemize}

\item also in 2011, Sony got hacked: over 1M users' personal

      information, including passwords, email addresses, home

      addresses, dates of birth, and all Sony opt-in data

      associated with their accounts.

\end{itemize}}

\only<4>{\begin{itemize}

\item in 2007, Gordon Brown needed to apologise for the loss

      of tax data of 25M  people

\end{itemize}}

\end{minipage}

\end{frame}

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\begin{frame}[c]

\frametitle{Privacy and Big Data}

\mbox{}\\[-16mm]\mbox{}

Selected sources of ``Big Data'':\smallskip{}

\begin{itemize}

\item Facebook 

\begin{itemize}

\item 40+ Billion photos (100 PB)

\item 6 Billion messages daily (5 - 10 TB)

\item 900 Million users  

\end{itemize}

\item Common Crawl

\begin{itemize}

\item covers 3.8 Billion webpages (2012 dataset)

\item 50 TB of data

\end{itemize}

\item Google

\begin{itemize}

\item 20 PB daily (2008)

\end{itemize}

\item Twitter

\begin{itemize}

\item 15 Million active users in the UK; 500M Teets per day

\item a company called Datasift is allowed to mine all tweets since 2010

\item they charge 10k per month for other companies to target advertisement

\end{itemize}

\end{itemize}\pause

\end{frame}}

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\mode<presentation>{

\begin{frame}[c]

\frametitle{Cookies\ldots}

``We have published a new cookie policy. It explains what cookies are 

and how we use them on our site. To learn more about cookies and 

their benefits, please view our cookie policy.\medskip

If you'd like to disable cookies on this device, please view our information 

pages on 'How to manage cookies'. Please be aware that parts of the 

site will not function correctly if you disable cookies. \medskip

By closing this 

message, you consent to our use of cookies on this device in accordance 

with our cookie policy unless you have disabled them.''

\end{frame}}

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\mode<presentation>{

\begin{frame}[c]

\frametitle{Scare Tactics}

The actual policy reads:\bigskip

``As we explain in our Cookie Policy, cookies help you to get the most 

out of our websites.\medskip

If you do disable our cookies you may find that certain sections of our 

website do not work. For example, you may have difficulties logging in 

or viewing articles.''

\end{frame}}

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\mode<presentation>{

\begin{frame}[c]

\frametitle{Netflix Prize}

Anonymity is \alert{necessary} for privacy, but \alert{not} enough!\bigskip

\begin{itemize}

\item Netflix offered in 2006 (and every year until 2010) a 1 Mio \$ prize for improving their movie rating algorithm

\item dataset contained 10\% of all Netflix users (appr.~500K)

\item names were removed, but included numerical ratings as well as times of rating

\item some information was \alert{perturbed} (i.e., slightly modified)

\end{itemize}

\hfill{\bf\alert{All OK?}}

\end{frame}}

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\mode<presentation>{

\begin{frame}[c]

\frametitle{Re-identification Attacks}

Two researchers analysed the data: 

\begin{itemize}

\item with 8 ratings (2 of them can be wrong) and corresponding dates that can have a margin 14-day error, 98\% of the

records can be identified

\item for 68\% only two ratings and dates are sufficient (for movie ratings outside the top 500)\bigskip\pause

\item they took 50 samples from IMDb (where people can reveal their identity)

\item 2 of them uniquely identified entries in the Netflix database (either by movie rating or by dates)

\end{itemize}

\end{frame}}

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\mode<presentation>{

\begin{frame}[c]

\frametitle{Re-identification Attacks}

\begin{itemize}

\item in 1990 insurance databases were made public with names removed, but  birth dates, 

gender, ZIP-code were retained\medskip

\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

\end{itemize}

\end{frame}}

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\mode<presentation>{

\begin{frame}[c]

\frametitle{}

\begin{itemize}

\item Birth data, postcode and gender (unique for\\ 87\% of the US population)

\item Preferences in movies (99\% of 500K for 8 ratings)

\end{itemize}\bigskip

Therefore best practices / or even law (HIPAA, EU): 

\begin{itemize}

\item only year dates (age group for 90 years or over), 

\item no postcodes (sector data is OK, similarly in the US)\\

\textcolor{gray}{no names, addresses, account numbers, licence plates}

\item disclosure information needs to be retained for 5 years

\end{itemize}

\end{frame}}

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\mode<presentation>{

\begin{frame}<2>[c]

\frametitle{\large How to Safely Disclose Information?}

\only<1>{

\begin{itemize}

\item Assume you make a survey of 100 randomly chosen people.

\item Say 99\% of the surveyed people in the 10 - 40 age group have seen the

Gangnam video on youtube.\bigskip

\item What can you infer about the rest of the population? 

\end{itemize}}

\only<2>{

\begin{itemize}

\item Is it possible to re-identify data later, if more data is released? \bigskip\bigskip\pause

\item Not even releasing only  aggregate information prevents re-identification attacks.

(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}}

\end{frame}}

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\mode<presentation>{

\begin{frame}<2>[c]

\frametitle{\Large We cannot exclude all Harm}

\begin{itemize}

\item Analysis of a given data set teaches us that smoking causes cancer. 

Mary, a smoker, is harmed by this analysis: her insurance premiums rise. 

Mary’s premiums rise whether or not her data are in the data set. In other words, 

Mary is harmed by the finding smoking causes cancer.\bigskip

\item \ldots of course she is also helped; she might quit smoking

\end{itemize}

\end{frame}}

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\mode<presentation>{

\begin{frame}<2>[c]

\frametitle{Differential Privacy}

\begin{itemize}

\item Goal: Nothing about an individual should be learnable from the database that 

cannot be learned without access to the database.\pause\bigskip

\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}

\end{itemize}

\end{frame}}

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\mode<presentation>{

\begin{frame}[c]

\frametitle{Differential Privacy}

\begin{center}

User\;\;\;\;    

\begin{tabular}{c}

tell me \bl{$f(x)$} $\Rightarrow$\\

$\Leftarrow$ \bl{$f(x) + \text{noise}$}

\end{tabular}

\;\;\;\;\begin{tabular}{@{}c}

Database\\

\bl{$x_1, \ldots, x_n$}

\end{tabular}

\end{center}

\begin{itemize}

\item \bl{$f(x)$} can be released, if \bl{$f$} is insensitive to

individual entries  \bl{$x_1, \ldots, x_n$}\\

\item Intuition: whatever is learned from the dataset would be learned regardless of whether

\bl{$x_i$} participates\bigskip\pause 

\item Noised needed in order to prevent queries:\\ Christian's salary $=$ 

\begin{center}

\bl{\large$\Sigma$} all staff $-$  \bl{\large$\Sigma$} all staff $\backslash$ Christian

\end{center} 

\end{itemize}

\end{frame}}

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\mode<presentation>{

\begin{frame}[c]

\frametitle{Example}

\begin{center}

\begin{tabular}{l|l}

Name	 & Has the disease?\\\hline

Alice          & yes\\ 

Bob     	 & no\\

Charlie	 & yes\\

Eve	         & no\\

Chandler	 & yes\\

\end{tabular}

\end{center}

How many people have a disease?

\end{frame}}

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\mode<presentation>{

\begin{frame}[c]

\frametitle{Adding Noise}