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AntiPhish - lessons learnt

Invited talk
 
: Bergholz, A.

:
Preprint urn:nbn:de:0011-n-1051297 (16 KByte PDF)
MD5 Fingerprint: 9c94a045824e064f3278887eeaf7d8d9
Copyright Association for Computing Machinery (ACM)
Created on: 22.10.2009


Chen, H.; Dacier, M.; Moens, M.-F.; Paaß, G.; Yang, C.C. ; Association for Computing Machinery -ACM-, Special Interest Group on Knowledge Discovery and Data Mining -SIGKDD-:
Proceedings of the ACM SIGKDD Workshop on CyberSecurity and Intelligence Informatics, CSI-KDD : June 28, 2009, Paris, France. Held in conjunction with SIGKDD '09
New York: ACM, 2009
ISBN: 978-1-60558-669-4
pp.1-2
Workshop on CyberSecurity and Intelligence Informatics (CSI-KDD) <2009, Paris>
International Conference on Knowledge Discovery and Data Mining (KDD) <15, 2009, Paris>
English
Conference Paper, Electronic Publication
Fraunhofer IAIS ()
Phishing; machine learning; filtering; adaptive learning

Abstract
Computer supported communication and infrastructure are integral parts of modern economy. Their security is of incredible importance to a wide variety of practical domains ranging from Internet service providers to the banking industry and e-commerce, from corporate networks to the intelligence community. The CSI-KDD workshop focuses on novel knowledge discovery methods addressing CyberSecurity and intelligence issues as well as innovative applications demonstrating the effectiveness of data mining in solving real-world security problems. The challenge for novel methods originates from the emergence of new types of contents and protocols, and only an integrated view on all modes promises optimal results. Innovative applications are essential as IT-communication as well as computer-supported technical and social infrastructure have an extremely complex structure and require a comprehensive approach to prevent criminal activities.

: http://publica.fraunhofer.de/documents/N-105129.html