Titlebook: Computational Intelligence in Security for Information Systems 2010; Proceedings of the 3 Álvaro Herrero,Emilio Corchado,Ángel Alonso Confe

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https://doi.org/10.1007/978-3-322-81984-0olution. We demonstrate the ability of genetic programming to evolve useful fuzzy classifiers on a real world case in which a classifier detecting faulty products in an industrial production process is evolved.

visual-cortex

1867-5662 held in León, Spain, on November 11th-12th, 2010.Written by rd The 3 International Conference on Computational Intelligence in Security for Information Systems (CISIS 2010) provided a broad and interdisciplinary forum to present the most recent developments in several very active scientific areas su

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Arndt Kaminski Ph.D,Carsten Rahlf,Inga Vosseatures that are induced from a protocol state machine. The second one is relying on the underlying parse trees of messages. Both approaches are passive. We provide a performance analysis on the SIP protocol. Important application domains of our work consist in network intrusion detection and security assessment.

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Conflict

https://doi.org/10.1007/978-3-642-05474-7nisations and users assets. In this paper, we present the first Threat Modelling approach in Online Social Networks that intends to identify the threats and vulnerabilities that can be exploited. Next, we define what we call the . (CoR), a graphical definition of every security aspect involved in the threat modelling.

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Lipreading Using ,–Gram Feature Vector defined using six cubic curves. The visual parameters are used to build .-gram feature vectors. Two sets of classification experiments are performed with the .-gram feature vectors: using the hidden Markov model and using multiple data mining algorithms in WEKA, a tool widely used by researchers. Preliminary results show encouraging results.

Lumbar-Spine

Semi-supervised Fingerprinting of Protocol Messageseatures that are induced from a protocol state machine. The second one is relying on the underlying parse trees of messages. Both approaches are passive. We provide a performance analysis on the SIP protocol. Important application domains of our work consist in network intrusion detection and security assessment.