Identifying Security Evaluation of Pattern Classifiers Under Attack

Download Now
Provided by: International Journal of Innovative Research in Science, Engineering and Technology (IJIRSET)
Topic: Security
Format: PDF
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 and 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 vulnerabilities, whose exploitation may severely affect their performance, and consequently limit their practical utility. Extending pattern classification theory and design methods to adversarial settings is thus a novel and very relevant research direction, which has not yet been pursued in a systematic way.
Download Now

Find By Topic