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Tracked Without a Trace : Linking Sessions of Users by U..:

, In: Proceedings of the 2016 ACM Workshop on Artificial Intelligence and Security,

Kirchler, Matthias ; Herrmann, Dominik ; Lindemann, Jens. - p. 23-34 , 2016

Link: https://dl.acm.org/doi/10.1145/2996758.2996770

RT 
T1 <cTitle>Proceedings of the 2016 ACM Workshop on Artificial Intelligence and Security</cTitle>: T1 <Title>Tracked Without a Trace				: Linking Sessions of Users by Unsupervised Learning of Patterns in Their DNS Traffic</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-2996770&Exemplar=1&LAN=DE
				
A1 Kirchler, Matthias
A1 Herrmann, Dominik
A1 Lindemann, Jens
A1 Kloft, Marius
PB ACM
YR 2016
K1 attack
K1 behavioral fingerprints
K1 clustering
K1 k-means
K1 privacy
K1 Security and privacy
K1 Security services
K1 Pseudonymity, anonymity and untraceability
K1 Computing methodologies
K1 Machine learning
K1 Learning paradigms
K1 Unsupervised learning
K1 Cluster analysis
K1 Networks
K1 Network properties
K1 Network security
K1 Network services
K1 Naming and addressing
K1 General and reference
K1 Cross-computing tools and techniques
K1 Empirical studies
SP 23
OP 34
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/2996758.2996770
DO https://dl.acm.org/doi/10.1145/2996758.2996770
SF ELIB - SuUB Bremen

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