[9156] in cryptography@c2.net mail archive
Timing Analysis of Keystrokes and Timing Attacks on SSH
daemon@ATHENA.MIT.EDU (Perry E. Metzger)
Wed Aug 22 11:38:29 2001
To: cryptography@wasabisystems.com
From: "Perry E. Metzger" <perry@piermont.com>
Date: 22 Aug 2001 11:37:39 -0400
Message-ID: <87elq4ksvw.fsf@snark.piermont.com>
What I find really neat here is that up until now, serious traffic
analysis has been fairly neglected in the open crypto community. Is
this the start of things to come?
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Date: Wed, 22 Aug 2001 08:53:30 -0600
From: aleph1@securityfocus.com
To: secpapers@securityfocus.com
Cc: secureshell@securityfocus.com
Subject: Timing Analysis of Keystrokes and Timing Attacks on SSH
Message-ID: <20010822085330.J3366@securityfocus.com>
Mime-Version: 1.0
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Timing Analysis of Keystrokes and Timing Attacks on SSH
Dawn Xiaodong Song, David Wagner, Xuqing Tian
University of California, Berkeley
SSH is designed to provide a security channel between two hosts. Despite the
encryption and authentication mechanisms it uses, SSH has two weakness:
First, the transmitted packets are padded only to an eight-byte boundary (if
a block cipher is in use), which reveals the approximate size of the
original data. Second, in interactive mode, every individual keystroke that
a user types is sent to the remote machine in a separate IP packet
immediately after the key is pressed, which leaks the interkeystroke timing
information of users' typing. In this paper, we show how these seemingly
minor weaknesses result in serious security risks.
First we show that even very simply statistical techniques suffice to
reveal sensitive information such as the length of users' passwords or even
root passwords. More importantly, we further show that using more advanced
statistical techniques on timing information collected from the network,
the eavesdropped can learn significant information about what users type in
SSH sessions. In particular, we perform a statistical study of users'
typing patterns and show that these patterns reveal information about the
keys typed. By developing a Hidden Markov Model and our key sequence
prediction algorithm, we can predict key sequences from the interkeystroke
timings. We further develop and attacker system, Herbivore, which tried to
learn users' passwords by monitoring SSH sessions. By collecting timing
information on the network, Herbivore can speed up exhaustive search for
passwords by a factor of 50. We also propose some countermeasures.
In general our results apply not only to SSH, but also to general class of
protocols for encrypting interactive traffic. We show that timing leaks
open a new set of security risks, and hence caution must be taken when
designing this type of protocol.
http://paris.cs.berkeley.edu/~dawnsong/papers/ssh-timing.pdf
-
Elias Levy
SecurityFocus
http://www.securityfocus.com/
Si vis pacem, para bellum
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