From 4cd77dc989c7b1410312102c69a80f930e192ef6 Mon Sep 17 00:00:00 2001
From: Tobias Eidelpes <tobias@eidelpes.info>
Date: Tue, 7 Jul 2020 15:08:18 +0200
Subject: [PATCH] Add section outline for second chapter

---
 defences.tex   | 60 ++++++++++++++++++++++++++++++++++++++++++++++++++
 references.bib | 14 ++++++------
 2 files changed, 67 insertions(+), 7 deletions(-)

diff --git a/defences.tex b/defences.tex
index e69de29..b1fd581 100644
--- a/defences.tex
+++ b/defences.tex
@@ -0,0 +1,60 @@
+\chapter{Defenses against Tracking}%
+\label{chap:defenses against tracking}
+
+The proliferation of tracking across the web has led to the development of a
+myriad of tools that each have their own advantages and disadvantages. Some
+tracking methods can be easily mitigated by changing browser settings or by
+disabling certain technologies. More often than not, these methods not only stop
+or limit tracking but also severely hamper the internet experience for end
+users. Especially some of the more advanced tools require user input to know
+which items to block and which to let through. This in turn requires expertise
+that few regular internet users possess, further complicating defending against
+tracking. This chapter introduces methods and tools that have been proven to be
+effective against tracking on the web. It is split into two parts, with the
+first surveying techniques that can be applied to limit tracking and the second
+presenting tools to managing tracking on the web. The focus lies on defending
+against the methods discussed in chapter~\ref{chap:tracking methods}.
+
+\section{Techniques}
+\label{sec:techniques}
+
+The aim of this section is to present comparatively simple techniques that a
+user can employ to limit tracking. The benefit of these methods is that they are
+built into modern browsers and therefore do not require specific user knowledge.
+Although their implementations vary from one browser to another, the basic idea
+remains the same.
+
+\subsection{Opt-out}
+\label{subsec:Opt-out}
+
+\subsection{Clearing Browser History}
+\label{subsec:Clearing Browser History}
+
+\subsection{Private Browsing Mode}
+\label{subsec:Private Browsing Mode}
+
+\subsection{Do Not Track}
+\label{subsec:Do Not Track}
+
+\subsection{Privacy-focused Search Engines}
+\label{subsec:Privacy-focused Search Engines}
+
+\section{Tools}
+\label{sec:tools}
+
+\subsection{Blacklists}
+\label{subsec:blacklists}
+
+\subsection{TOR}
+\label{subsec:tor}
+
+\subsection{Virtual Private Networks}
+\label{subsec:virtual private networks}
+
+\subsection{Privacy Badger}
+\label{subsec:privacy badger}
+
+\subsection{Request Policy}
+\label{subsec:Request Policy}
+
+
diff --git a/references.bib b/references.bib
index b98d2fa..6b4e7a9 100644
--- a/references.bib
+++ b/references.bib
@@ -182,17 +182,17 @@
   number = {1}
 }
 
-@article{beigiProtectingUserPrivacy2018,
+@inproceedings{beigiProtectingUserPrivacy2019,
   title = {Protecting {{User Privacy}}: {{An Approach}} for {{Untraceable Web Browsing History}} and {{Unambiguous User Profiles}}},
   shorttitle = {Protecting {{User Privacy}}},
+  booktitle = {Proceedings of the {{Twelfth ACM International Conference}} on {{Web Search}} and {{Data Mining}}},
   author = {Beigi, Ghazaleh and Guo, Ruocheng and Nou, Alexander and Zhang, Yanchao and Liu, Huan},
-  year = {2018},
-  month = nov,
-  url = {http://arxiv.org/abs/1811.09340},
-  urldate = {2019-08-22},
+  year = {2019},
+  month = jan,
+  pages = {213--221},
+  address = {{Melbourne VIC, Australia}},
   abstract = {The overturning of the Internet Privacy Rules by the Federal Communications Commissions (FCC) in late March 2017 allows Internet Service Providers (ISPs) to collect, share and sell their customers' Web browsing data without their consent. With third-party trackers embedded on Web pages, this new rule has put user privacy under more risk. The need arises for users on their own to protect their Web browsing history from any potential adversaries. Although some available solutions such as Tor, VPN, and HTTPS can help users conceal their online activities, their use can also significantly hamper personalized online services, i.e., degraded utility. In this paper, we design an effective Web browsing history anonymization scheme, PBooster, aiming to protect users' privacy while retaining the utility of their Web browsing history. The proposed model pollutes users' Web browsing history by automatically inferring how many and what links should be added to the history while addressing the utility-privacy trade-off challenge. We conduct experiments to validate the quality of the manipulated Web browsing history and examine the robustness of the proposed approach for user privacy protection.},
-  archiveprefix = {arXiv},
-  eprintclass = {cs}
+  series = {{{WSDM}} '19}
 }
 
 @article{belloroKnowWhatYou2018,