期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2014
卷号：3
期号：11
页码：3691-3693
出版社：Shri Pannalal Research Institute of Technolgy
摘要：Pattern classification is a branch of machine learning that focuses on recognition of patterns and regularities in data.In adversarial applications like biometric authentication, spam filtering, network intrusion detection the pattern classification systems are used. Pattern classification systems may exhibit vulnerabilities if adversarial scenario is not taken into account. Multimodal biometric systems are more robust to spoofing attacks,as they combine information coming from different biometric traits.In this paper,weevaluate the security of pattern classifiersthat formalizes and generalizes the main ideas proposed in the literature and give examples of its use in three real applications.We propose a framework for evaluation of pattern security,model of adversary for defining any attack scenario.Reported results show that security evaluation can provide a more complete understanding of the classifier's behavior in adversarial environments, and lead to better design choices.
