Title
A Model for the Study of Privacy Issues in Secure Shell Connections
Abstract
The Secure Shell protocol strives to protect the privacy of its users in several ways. On one hand, the strong encryption and authentication algorithms that it adopts provide guarantees that the data exchanged between two SSH endpoints remain private to third parties. On the other hand, the type of traffic that each SSH channel transports, such as e-mail, remote shell activity, etc., is also supposed to be hidden from any observer that does not possess the necessary keys. This paper introduces a simple but accurate model of the SSH channel which can be used to study the level of privacy that SSH-protected traffic can achieve with respect to the users' activities. We think that the model can facilitate several types of projects. For example, network managers can detect traffic anomalies hidden by SSH connections more easily by relying on the output of our model. Another example, which we present in this paper, is the use of this model to derive accurate fingerprints of the type of applications run through an SSH channel by simply starting from the statistics of captured clear-text traffic. Such fingerprints can then be used to detect what type of activity, i.e., what type of traffic, is going on within an SSH channel, thereby breaking user privacy.
Year
DOI
Venue
2008
10.1109/IAS.2008.46
IAS
Keywords
Field
DocType
accurate model,clear-text traffic,accurate fingerprint,ssh endpoint,privacy issues,remote shell activity,user privacy,ssh-protected traffic,ssh connection,ssh channel transport,ssh channel,secure shell connections,network management,hidden markov models,cryptographic protocols,authentication algorithms,fingerprint recognition,privacy,encryption,cryptography,data privacy,data exchange,classification algorithms,multiplexing,protocols
Cryptographic protocol,Computer science,Cryptography,Computer security,Communication channel,Computer network,Data Authentication Algorithm,Encryption,Secure Shell,Information privacy,ssh-agent
Conference
Volume
Issue
ISSN
4
4
1554-1010
Citations 
PageRank 
References 
0
0.34
10
Authors
3
Name
Order
Citations
PageRank
Maurizio Dusi130318.21
Francesco Gringoli289061.65
Luca Salgarelli393781.17