[freehaven-cvs] Edit 3.2; remove a "we" from the abstract

[nickm@seul.org (Nick Mathewson)]

Update of /home/freehaven/cvsroot/doc/e2e-traffic
In directory moria.mit.edu:/tmp/cvs-serv2059

Modified Files:
	e2e-traffic.tex 
Log Message:
Edit 3.2; remove a "we" from the abstract

Index: e2e-traffic.tex
===================================================================
RCS file: /home/freehaven/cvsroot/doc/e2e-traffic/e2e-traffic.tex,v
retrieving revision 1.32
retrieving revision 1.33
diff -u -d -r1.32 -r1.33
--- e2e-traffic.tex	25 Jan 2004 13:38:45 -0000	1.32
+++ e2e-traffic.tex	25 Jan 2004 14:09:06 -0000	1.33
@@ -48,17 +48,17 @@
 \begin{abstract}
 We extend earlier research on mounting and resisting passive
 long-term end-to-end traffic analysis attacks against anonymous message
-systems.
-We relax the assumptions of earlier attacks by describing how an
+systems
+% We relax the assumptions of earlier attacks
+by describing how an
 eavesdropper can learn sender-receiver connections even when the substrate
 is a network of pool mixes, the attacker is non-global, and senders have
 complex behavior including generating padding messages.
-We describe how an attacker can use extra information about
+Additionally, we describe how an attacker can use extra information about
 message distinguishability to speed the attack.
 Finally, we simulate our attacks for a variety of
-scenarios, focusing on the amount of information needed to link senders and
-recipients.
-%XXXX We should say something about 'we found some good countermeasures.'
+scenarios, focusing on the amount of information needed to link senders to
+their recipients.
 \end{abstract}
 
 %======================================================================
@@ -608,14 +608,14 @@
 %show that these extensions force the attacker to observe an increasingly
 %large number of rounds of traffic.
 
-In this section, rather than talking about how to broaden the attack so it
-works in new situations (at the expensive of needing increased traffic),
-we discuss ways to reduce the amount of traffic required for the attack
+In this section, rather than broadening the attack to
+work in new situations (at the expensive of needing increased traffic),
+we discuss ways to reduce the attack's required amount of traffic
 by incorporating additional information.
 
 \subsubsection{Exploiting message partitioning:}
 %\label{subsubsec:full-linkability}
-The attacker's work can be greatly simplified if some output messages are
+The attacker's work is simplified if some output messages are
 {\it linkable}.  Two messages are linkable if they are
 likelier to originate from the same sender than are two randomly chosen
 messages.  We consider a special case of linkability, in which we discover
@@ -623,14 +623,14 @@
 messages in the same class are likelier to come from the same sender than two
 messages chosen at random.
 
-The easiest case of partitioning is pseudonymity: in a typical
+The easiest scenario for partitioning is pseudonymity: in a typical
 pseudonym service, each sender has one or more pseudonyms and all
 delivered messages are associated with a pseudonym.
 An eavesdropper who can connect senders to their pseudonyms
 could trivially use this information to connect senders and recipients.
-For example, he might treat
-classes of fully linkable messages as virtual message
-destinations.  Instead of collecting observations $\V{o_i}$ of
+To do so, he might treat
+pseudonyms as virtual message
+destinations: instead of collecting observations $\V{o_i}$ of
 recipients who receive messages in round $i$, the attacker now
 collects observations $\V{o_i}$ of linkable classes
 (e.g. pseudonyms) that receive in round $i$.  Since two distinct
@@ -642,13 +642,14 @@
 many senders will send messages in the same class. For
 example, two binary documents written in the same version of MS Word
 are more likely to be written by the same sender than two messages
-selected at random.  These linkages may be more abstract: a
-sophisticated attacker could check for the presence of certain
-keywords and try to link messages based on their textual content.
+selected at random.
+%Linkages may be more abstract: a
+%sophisticated attacker could check for the presence of certain
+%keywords and try to link messages based on their textual content.
 
 To exploit these scenarios, the attacker
-chooses a set of $c$ `partitioning classes' (such as languages or
-patterns of usage), and assigning to each observed output
+chooses a set of $c$ partitioning classes (such as languages or
+patterns of usage), and assigns to each observed output
 message a probability of belonging to each class.  The attacker then
 proceeds as before, but instead of collecting observation
 vectors with elements corresponding the recipients, the attacker now
@@ -690,7 +691,7 @@
 %======================================================================
 \section{Simulation results}
 \label{sec:simulation}
-In Section \ref{subsec:broadening}, we repeatedly claim that each
+In Section~\ref{subsec:broadening}, we repeatedly claim that each
 complication of the sender or the
 network forces the attacker to gather more information. But how much?
 

***********************************************************************
To unsubscribe, send an e-mail to majordomo@seul.org with
unsubscribe freehaven-cvs       in the body. http://freehaven.net/