{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T01:10:37Z","timestamp":1740100237610,"version":"3.37.3"},"reference-count":44,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,7,18]],"date-time":"2021-07-18T00:00:00Z","timestamp":1626566400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,7,18]],"date-time":"2021-07-18T00:00:00Z","timestamp":1626566400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province, China","doi-asserted-by":"publisher","award":["2018A030313203"],"award-info":[{"award-number":["2018A030313203"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2018ZD32"],"award-info":[{"award-number":["2018ZD32"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,7,18]]},"DOI":"10.1109\/ijcnn52387.2021.9533763","type":"proceedings-article","created":{"date-parts":[[2021,9,20]],"date-time":"2021-09-20T21:27:41Z","timestamp":1632173261000},"page":"1-8","source":"Crossref","is-referenced-by-count":3,"title":["Distribution-based Adversarial Filter Feature Selection against Evasion Attack"],"prefix":"10.1109","author":[{"given":"Patrick P. K.","family":"Chan","sequence":"first","affiliation":[{"name":"South China University of Technology,School of Computer Science and Engineering,Guangzhou,China"}]},{"given":"YuanChao","family":"Liang","sequence":"additional","affiliation":[{"name":"South China University of Technology,School of Computer Science and Engineering,Guangzhou,China"}]},{"given":"Fei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Henan Normal University,College of Computer and Information Engineering,Xinxiang,China"}]},{"given":"Daniel S.","family":"Yeung","sequence":"additional","affiliation":[{"name":"Henan Normal University,College of Computer and Information Engineering,Hong Kong"}]}],"member":"263","reference":[{"key":"ref39","first-page":"1","article-title":"Information gain and a general measure of correlation","author":"t","year":"1983","journal-title":"Biometrika"},{"key":"ref38","first-page":"1","article-title":"Supervised feature selection algorithm via discriminative ridge regression","author":"zhang","year":"2017","journal-title":"World Wide Web"},{"key":"ref33","doi-asserted-by":"crossref","first-page":"3273","DOI":"10.1016\/j.neucom.2010.04.003","article-title":"A new wrapper feature selection approach using neural network","volume":"73","author":"kabir","year":"2008","journal-title":"Neurocomputing"},{"key":"ref32","article-title":"Feature selection and classification - a probabilistic wrapper approach","author":"liu","year":"1996","journal-title":"International Conference on Industrial & Engineering Applications of Artificial Intelligence & Expert Systems"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/SAINT.2010.50"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2008.2005601"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1162\/NECO_a_00816"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2015.02.003"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/1015330.1015364"},{"key":"ref34","doi-asserted-by":"crossref","first-page":"13","DOI":"10.5120\/169-295","article-title":"Feature subset selection problem using wrapper approach in supervised learning","volume":"1","author":"karegowda","year":"2010","journal-title":"International Journal of Computer Applications"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/0262-8856(95)01057-2"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4613-9617-8_2"},{"key":"ref11","doi-asserted-by":"crossref","DOI":"10.1145\/1014052.1014066","article-title":"Adver-sarial classification","author":"dalvi","year":"2004","journal-title":"ACM SIGKDD International Conference on Knowledge Discovery and Data Mining"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/s13042-010-0007-7"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICWAPR.2017.8076696"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2866197"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.23919\/DATE.2019.8715141"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2015.2415032"},{"key":"ref17","first-page":"s0957417417306590","article-title":"Quantifying the resilience of machine learning classifiers used for cyber security","volume":"92","author":"katzir","year":"2017","journal-title":"Expert Systems with Applications"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/SSCI.2017.8280924"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2018.8489246"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2005.159"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/SPW.2019.00033"},{"key":"ref27","first-page":"1157","article-title":"An introduction to variable and feature selection","volume":"3","author":"guyon","year":"2003","journal-title":"Journal of Machine Learning Research"},{"key":"ref3","article-title":"Learning a secure classifier against evasion attack","author":"khorshidpour","year":"2017","journal-title":"IEEE International Conference on Data Mining Workshops"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-30217-6_18"},{"key":"ref29","article-title":"Feature selection for high-dimensional data: A fast correlation-based filter solution","author":"lei","year":"2003","journal-title":"Twentieth International Conference on International Conference on Machine Learning"},{"key":"ref5","article-title":"Have you stolen my model? evasion attacks against deep neural network watermarking techniques","author":"hitaj","year":"2018","journal-title":"ArXiv Preprint"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2017.06.032"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/EISIC.2017.21"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2014.08.081"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/MILCOM.2017.8170807"},{"key":"ref1","article-title":"Evasion attacks against machine learning at test time","author":"biggio","year":"2013","journal-title":"Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/0734-189X(85)90055-6"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/MIC.2011.112"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-010-5188-5"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/2484313.2484327"},{"journal-title":"Behavior of Machine Learning Algorithms in Adversarial Environments","year":"2010","author":"a","key":"ref24"},{"journal-title":"Wasserstein gan and the kantorovich-rubinstein duality","year":"0","author":"herrmann","key":"ref41"},{"key":"ref23","first-page":"1689","article-title":"Is feature selection secure against training data poisoning?","author":"xiao","year":"2015","journal-title":"International Conference on Machine Learning"},{"key":"ref44","article-title":"A stability index for feature selection","author":"kuncheva","year":"2007","journal-title":"Conference on Iasted International Multi-conference Artificial Intelligence & Applications"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.3233\/IDA-1997-1302"},{"key":"ref43","article-title":"Trec 2005 spam track overview","author":"cormack","year":"2005","journal-title":"Proceedings of the Fourteenth Text REtrieval Conference TREC 2005"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/s13042-016-0629-5"}],"event":{"name":"2021 International Joint Conference on Neural Networks (IJCNN)","start":{"date-parts":[[2021,7,18]]},"location":"Shenzhen, China","end":{"date-parts":[[2021,7,22]]}},"container-title":["2021 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9533266\/9533267\/09533763.pdf?arnumber=9533763","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,9]],"date-time":"2023-11-09T02:49:04Z","timestamp":1699498144000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9533763\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,18]]},"references-count":44,"URL":"https:\/\/doi.org\/10.1109\/ijcnn52387.2021.9533763","relation":{},"subject":[],"published":{"date-parts":[[2021,7,18]]}}}