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SpamBayes. http:\/\/spambayes.sourceforge.net\/."},{"key":"e_1_3_2_1_7_1","volume-title":"September","author":"Ali M. Q.","year":"2015","unstructured":"M. Q. Ali , A. B. Ashfaq , E. Al-Shaer , and Q. Duan , \" Towards a science of anomaly detection system evasion,\" in IEEE Conference on Communications and Network Security (CNS) , September 2015 . M. Q. Ali, A. B. Ashfaq, E. Al-Shaer, and Q. Duan, \"Towards a science of anomaly detection system evasion,\" in IEEE Conference on Communications and Network Security (CNS), September 2015."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-010-5188-5"},{"key":"e_1_3_2_1_9_1","volume-title":"ICML","author":"Biggio B.","year":"2012","unstructured":"B. Biggio , B. Nelson , and P. Laskov , \" Poisoning attacks against support vector machines,\" in Proceedings of International Conference on Machine Learning, ser . ICML , 2012 . B. Biggio, B. Nelson, and P. 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