Security Evaluation of Pattern Classifiers under Attack
نویسندگان
چکیده
منابع مشابه
Security Evaluation of Pattern Classifiers under Attack
Pattern classification systems are commonly used in adversarial applications, like biometric authentication, network intrusion detection, and spam filtering, in which data can be purposely manipulated by humans to undermine their operation. As this adversarial scenario is not taken into account by classical design methods, pattern classification systems may exhibit vulnerabilities,whose exploit...
متن کاملIdentifying Security Evaluation of Pattern Classifiers Under attack
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. As this adversarial scenario is not taken into account by classical design methods, pattern classification systems may exhibit v...
متن کاملSecurity Evaluation of Pattern Classifiers in Adversarial Environments
Pattern classification systems are commonly used in adversarial applications, like biometric authentication, network intrusion detection, and spam filtering, in which data can be purposely manipulated by humans to undermine their operation. As this adversarial scenario is not taken into account by classical design methods, pattern classification systems may exhibit vulnerabilities, whose exploi...
متن کاملA Review on Security Evaluation for Pattern Classifier against Attack
The systems which can be used for pattern classification are used in adversarial application, for example spam filtering, network intrusion detection system, biometric authentication. This adversarial scenario's exploitation may sometimes affect their performance and limit their practical utility. In case of pattern classification conception and contrive methods to adversarial environment ...
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Pattern recognition systems have been increasingly used in security applications, although it is known that carefully crafted attacks can compromise their security. We advocate that simulating a proactive arms race is crucial to identify the most relevant vulnerabilities of pattern recognition systems, and to develop countermeasures in advance, thus improving system security. We summarize a fra...
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ژورنال
عنوان ژورنال: IEEE Transactions on Knowledge and Data Engineering
سال: 2014
ISSN: 1041-4347
DOI: 10.1109/tkde.2013.57