[freehaven-cvs] Tighenten the end of 3.1 and the start of 3.2

[nickm@seul.org (Nick Mathewson)]

Update of /home/freehaven/cvsroot/doc/e2e-traffic
In directory moria.mit.edu:/tmp/cvs-serv27452

Modified Files:
	e2e-traffic.tex 
Log Message:
Tighenten the end of 3.1 and the start of 3.2

Index: e2e-traffic.tex
===================================================================
RCS file: /home/freehaven/cvsroot/doc/e2e-traffic/e2e-traffic.tex,v
retrieving revision 1.48
retrieving revision 1.49
diff -u -d -r1.48 -r1.49
--- e2e-traffic.tex	2 May 2004 22:40:20 -0000	1.48
+++ e2e-traffic.tex	2 May 2004 23:02:07 -0000	1.49
@@ -564,23 +564,22 @@
 
 A non-global attacker's characteristics depend on which parts of the
 network he can observe.  If the attacker
-eavesdrops on a fraction of the {\it mixes} in the system, he
+eavesdrops on a fraction of the {\it mixes}, he
  receives a sample\footnote{But possibly a biased
   sample, depending on Alice's path selection algorithm.} of the
 messages entering or leaving the system. If such an attacker can see some
-messages from Alice and some messages to her recipients, he can still
-converge on the same $\B{O}$ and thus the same estimation of Alice's
-behavior, but the attack will require more rounds of observation.
+messages from Alice and some messages to her recipients, he can guess
+Alice's recipients, but will require more rounds of observation.
 
 Alternatively, an attacker who eavesdrops on a fraction of the {\it
-  users} in the system receives {\it all} of the messages sent to or
+  users} receives {\it all} messages sent to or
 from those users but no messages sent to or from other users.  So long
 as one of these users is Alice, the network (to such an attacker) is as
 if the messages sent by Alice to
 unobserved recipients were dummy messages.  Now the attack converges
-as before, but with only information concerning the observed
-recipients:  the attacker learns which of the observed recipients
-receive messages from Alice, and which do not.
+only against observed recipients: the attacker learns
+which of observed recipients
+get messages from Alice, and which do not.
 
 \subsubsection{Time-variant background traffic:}
 %\label{subsubsec:time-variant}
@@ -607,7 +606,7 @@
 Finally, we note that an attacker can find recipients as well as senders by
 using slightly more storage and the same computational cost.
 
-Suppose the attacker wishes to know who is sending
+Suppose the attacker wants to know who is sending
 anonymous messages to a given recipient Bob.  The analysis remains the
 same: the attacker compares sender behavior in rounds from which Bob
 probably receives messages with behavior in rounds from which Bob
@@ -626,20 +625,20 @@
 %In Section~\ref{sec:simulation} we will
 %show that these extensions force the attacker to observe an increasingly
 %large number of rounds of traffic.
-
-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
+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 required amount of traffic
 by incorporating additional information.
 
 \subsubsection{Partitioning messages:}
 %\label{subsubsec:full-linkability}
-The attacker's work is simplified if some output messages are
-{\it linkable}.  Two messages are linkable if they are
+The attack is simplified if some output messages are
+{\it linkable}---that is, 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
-linkage by {\it partitioning} messages into separate classes such that
-messages in the same class are likelier to come from the same sender than two
+messages.  We consider a special case of linkability, in which we can
+{\it partition} messages into separate classes such that
+messages in the same class are likelier to have the same sender than
 messages chosen at random.
 
 For example, in a typical

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