{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T13:18:58Z","timestamp":1753881538228,"version":"3.41.2"},"reference-count":23,"publisher":"World Scientific Pub Co Pte Ltd","issue":"12","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2022,9,30]]},"abstract":"<jats:p> Adversarial attacks can fool convolutional networks and make the systems vulnerable to fraud and deception. How to defend against malicious attacks is a critical challenge in practice. Adversarial attacks are often conducted by adding tiny perturbations on images to cause network misclassification. Noise reduction can defend the attacks; however, it is not suited for all the cases. Considering that different models have different tolerance abilities on adversarial attacks, we develop a novel detecting module to remove noise by adaptive process and detect adversarial attacks without modifying the models. Experimental results show that by comparing the classification results on adversarial samples of MNIST and two subclasses of ImageNet datasets, our models can successfully remove most of the noise and obtain detection accuracies of 97.71% and 92.96%, respectively. Furthermore, our adaptive module can be assembled into different networks to achieve detection accuracies of 70.83% and 71.96%, respectively, on the white-box adversarial attacks of ResNet18 and SCD01MLP images. The best accuracy of 62.5% is obtained for both networks when dealing with the black-box attacks. <\/jats:p>","DOI":"10.1142\/s021800142252022x","type":"journal-article","created":{"date-parts":[[2022,7,9]],"date-time":"2022-07-09T03:27:15Z","timestamp":1657337235000},"source":"Crossref","is-referenced-by-count":3,"title":["Adaptive Image Reconstruction for Defense Against Adversarial Attacks"],"prefix":"10.1142","volume":"36","author":[{"given":"Yanan","family":"Yang","sequence":"first","affiliation":[{"name":"Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1507-0285","authenticated-orcid":false,"given":"Frank Y.","family":"Shih","sequence":"additional","affiliation":[{"name":"Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102, USA"},{"name":"Department of Computer Science and Information Engineering, Asia University, Taichung 413, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"I-Cheng","family":"Chang","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Engineering, National Dong Hwa University, Hualien 974, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2022,8,26]]},"reference":[{"first-page":"39","volume-title":"Proc. IEEE Symp. Security and Privacy","author":"Carlini N.","key":"S021800142252022XBIB001"},{"key":"S021800142252022XBIB002","doi-asserted-by":"publisher","DOI":"10.1109\/18.857799"},{"volume-title":"Proc. 2015 Int. Conf. Learning Representations","author":"Goodfellow I.","key":"S021800142252022XBIB003"},{"first-page":"770","volume-title":"Proc. IEEE Conf. Computer Vision and Pattern Recognition","author":"He K.","key":"S021800142252022XBIB004"},{"first-page":"1778","volume-title":"Proc. IEEE\/CVF Conf. Computer Vision and Pattern Recognition","author":"Liao F.","key":"S021800142252022XBIB005"},{"first-page":"1","volume-title":"6th Int. Conf. Learning Representations","author":"Madry A.","key":"S021800142252022XBIB006"},{"first-page":"2574","volume-title":"Proc. IEEE Conf. Computer Vision and Pattern Recognition","author":"Moosavi-Dezfooli S.-M.","key":"S021800142252022XBIB007"},{"key":"S021800142252022XBIB008","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2919463"},{"first-page":"372","volume-title":"Proc. IEEE European Symp. Security and Privacy","author":"Papernot N.","key":"S021800142252022XBIB009"},{"key":"S021800142252022XBIB011","doi-asserted-by":"publisher","DOI":"10.1145\/3052973.3053009"},{"first-page":"582","volume-title":"Proc. 2016 IEEE Symp. Security and Privacy","author":"Papernot N.","key":"S021800142252022XBIB012"},{"first-page":"1","volume-title":"2018 IEEE Int. Conf. Multimedia and Expo","author":"Shi Y.","key":"S021800142252022XBIB013"},{"volume-title":"Proc. 2014 Int. Conf. Learning Representations","author":"Szegedy C.","key":"S021800142252022XBIB014"},{"first-page":"1","volume-title":"Proc. IEEE Conf. Computer Vision and Pattern Recognition","author":"Szegedy C.","key":"S021800142252022XBIB015"},{"key":"S021800142252022XBIB016","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-007-9044-5"},{"key":"S021800142252022XBIB017","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.nuclphysa.2019.03.001","volume":"986","author":"Wang J.","year":"2019","journal-title":"Nucl. Phys. A"},{"first-page":"501","volume-title":"Proc. IEEE\/CVF Conf. Computer Vision and Pattern Recognition","author":"Xie C.","key":"S021800142252022XBIB018"},{"volume-title":"Proc. Network and Distributed System Security Symp.","author":"Xu W.","key":"S021800142252022XBIB019"},{"key":"S021800142252022XBIB020","doi-asserted-by":"publisher","DOI":"10.1142\/S0218001422540052"},{"first-page":"2456","volume-title":"Proc. IEEE Int. Conf. Bioinformatics and Biomedicine","author":"Yang Z.","key":"S021800142252022XBIB021"},{"key":"S021800142252022XBIB022","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3021729"},{"key":"S021800142252022XBIB023","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3092582"},{"key":"S021800142252022XBIB024","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3086596"}],"container-title":["International Journal of Pattern Recognition and Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S021800142252022X","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,17]],"date-time":"2022-10-17T10:17:16Z","timestamp":1666001836000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/10.1142\/S021800142252022X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,26]]},"references-count":23,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2022,9,30]]}},"alternative-id":["10.1142\/S021800142252022X"],"URL":"https:\/\/doi.org\/10.1142\/s021800142252022x","relation":{},"ISSN":["0218-0014","1793-6381"],"issn-type":[{"type":"print","value":"0218-0014"},{"type":"electronic","value":"1793-6381"}],"subject":[],"published":{"date-parts":[[2022,8,26]]},"article-number":"2252022"}}