{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T10:58:13Z","timestamp":1783940293266,"version":"3.55.0"},"publisher-location":"Cham","reference-count":34,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030289539","type":"print"},{"value":"9783030289546","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-28954-6_7","type":"book-chapter","created":{"date-parts":[[2019,9,9]],"date-time":"2019-09-09T23:08:50Z","timestamp":1568070530000},"page":"121-144","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":164,"title":["Towards Reverse-Engineering Black-Box Neural Networks"],"prefix":"10.1007","author":[{"given":"Seong Joon","family":"Oh","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bernt","family":"Schiele","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mario","family":"Fritz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2019,9,10]]},"reference":[{"issue":"3","key":"7_CR1","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1504\/IJSN.2015.071829","volume":"10","author":"G Ateniese","year":"2015","unstructured":"Ateniese, G., Mancini, L.V., Spognardi, A., Villani, A., Vitali, D., Felici, G.: Hacking smart machines with smarter ones: how to extract meaningful data from machine learning classifiers. Int. J. Secur. Netw. 10(3), 137\u2013150 (2015)","journal-title":"Int. J. Secur. Netw."},{"key":"7_CR2","doi-asserted-by":"crossref","unstructured":"Caruana, R., Lou, Y., Gehrke, J., Koch, P., Sturm, M., Elhadad, N.: Intelligible models for healthcare: predicting pneumonia risk and hospital 30-day readmission. In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1721\u20131730. ACM (2015)","DOI":"10.1145\/2783258.2788613"},{"key":"7_CR3","doi-asserted-by":"crossref","unstructured":"Chen, P.Y., Zhang, H., Sharma, Y., Yi, J., Hsieh, C.J.: Zoo: Zeroth order optimization based black-box attacks to deep neural networks without training substitute models. In: Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security, pp. 15\u201326. ACM, New York (2017)","DOI":"10.1145\/3128572.3140448"},{"key":"7_CR4","unstructured":"Dabkowski, P., Gal, Y.: Real time image saliency for black box classifiers. In: Advances in Neural Information Processing Systems, pp. 6967\u20136976 (2017)"},{"key":"7_CR5","doi-asserted-by":"crossref","unstructured":"Fong, R.C., Vedaldi, A.: Interpretable explanations of black boxes by meaningful perturbation. In: 2017 IEEE International Conference on Computer Vision (ICCV), pp. 3449\u20133457. IEEE (2017)","DOI":"10.1109\/ICCV.2017.371"},{"key":"7_CR6","unstructured":"Goodfellow, I.J., Shlens, J., Szegedy, C.: Explaining and harnessing adversarial examples. In: International Conference on Learning Representations (2015)"},{"key":"7_CR7","unstructured":"Hayes, J., Danezis, G.: Machine learning as an adversarial service: learning black-box adversarial examples. CoRR abs\/1708.05207 (2017)"},{"key":"7_CR8","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"7_CR9","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-319-46493-0_1","volume-title":"Computer Vision \u2013 ECCV 2016","author":"LA Hendricks","year":"2016","unstructured":"Hendricks, L.A., Akata, Z., Rohrbach, M., Donahue, J., Schiele, B., Darrell, T.: Generating visual explanations. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9908, pp. 3\u201319. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46493-0_1"},{"key":"7_CR10","doi-asserted-by":"crossref","unstructured":"Huang, G., Liu, Z., Van Der Maaten, L., Weinberger, K.Q.: Densely connected convolutional networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4700\u20134708 (2017)","DOI":"10.1109\/CVPR.2017.243"},{"key":"7_CR11","unstructured":"Iandola, F.N., Moskewicz, M.W., Ashraf, K., Han, S., Dally, W.J., Keutzer, K.: SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and $$<$$1mb model size. CoRR abs\/1602.07360 (2017)"},{"key":"7_CR12","series-title":"Proceedings of Machine Learning Research","first-page":"448","volume-title":"Proceedings of the 32nd International Conference on Machine Learning","author":"S Ioffe","year":"2015","unstructured":"Ioffe, S., Szegedy, C.: Batch normalization: accelerating deep network training by reducing internal covariate shift. In: Bach, F., Blei, D. (eds.) Proceedings of the 32nd International Conference on Machine Learning. Proceedings of Machine Learning Research, vol. 37, pp. 448\u2013456. PMLR, Lille (2015). http:\/\/proceedings.mlr.press\/v37\/ioffe15.html"},{"key":"7_CR13","unstructured":"Kamruzzaman, S.M., Islam, M.M.: An algorithm to extract rules from artificial neural networks for medical diagnosis problems. CoRR abs\/1009.4566 (2010)"},{"key":"7_CR14","doi-asserted-by":"publisher","first-page":"2278","DOI":"10.1109\/5.726791","volume":"86","author":"Y LeCun","year":"1998","unstructured":"LeCun, Y., Bottou, L., Bengio, Y., Haffner, P.: Gradient-based learning applied to document recognition. Proc. IEEE 86, 2278\u20132324 (1998)","journal-title":"Proc. IEEE"},{"issue":"3","key":"7_CR15","doi-asserted-by":"publisher","first-page":"1350","DOI":"10.1214\/15-AOAS848","volume":"9","author":"B Letham","year":"2015","unstructured":"Letham, B., Rudin, C., McCormick, T.H., Madigan, D., et al.: Interpretable classifiers using rules and bayesian analysis: building a better stroke prediction model. Ann. Appl. Stat. 9(3), 1350\u20131371 (2015)","journal-title":"Ann. Appl. Stat."},{"issue":"3","key":"7_CR16","doi-asserted-by":"crossref","first-page":"30:31","DOI":"10.1145\/3236386.3241340","volume":"16","author":"ZC Lipton","year":"2018","unstructured":"Lipton, Z.C.: The mythos of model interpretability. Queue 16(3), 30:31\u201330:57 (2018)","journal-title":"Queue"},{"key":"7_CR17","unstructured":"Liu, Y., Chen, X., Liu, C., Song, D.: Delving into transferable adversarial examples and black-box attacks. In: International Conference on Learning Representations (2017)"},{"key":"7_CR18","first-page":"2579","volume":"9","author":"L Maaten van der","year":"2008","unstructured":"van der Maaten, L., Hinton, G.: Visualizing high-dimensional data using t-SNE. J. Mach. Learn. Res. 9, 2579\u20132605 (2008)","journal-title":"J. Mach. Learn. Res."},{"key":"7_CR19","doi-asserted-by":"crossref","unstructured":"Mahendran, A., Vedaldi, A.: Understanding deep image representations by inverting them. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5188\u20135196 (2015)","DOI":"10.1109\/CVPR.2015.7299155"},{"key":"7_CR20","doi-asserted-by":"crossref","unstructured":"Moosavi-Dezfooli, S.M., Fawzi, A., Fawzi, O., Frossard, P.: Universal adversarial perturbations. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1765\u20131773 (2017)","DOI":"10.1109\/CVPR.2017.17"},{"key":"7_CR21","doi-asserted-by":"crossref","unstructured":"Narodytska, N., Kasiviswanathan, S.P.: Simple black-box adversarial perturbations for deep networks. CoRR abs\/1612.06299 (2017)","DOI":"10.1109\/CVPRW.2017.172"},{"key":"7_CR22","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1007\/BF01448847","volume":"100","author":"J Neumann","year":"1928","unstructured":"Neumann, J.: Zur Theorie der Gesellschaftsspiele. Math. Ann. 100, 295\u2013320 (1928). http:\/\/eudml.org\/doc\/159291","journal-title":"Math. Ann."},{"key":"7_CR23","doi-asserted-by":"crossref","unstructured":"Oh, S.J., Augustin, M., Schiele, B., Fritz, M.: Towards reverse-engineering black-box neural networks. In: International Conference on Learning Representations (ICLR) (2018)","DOI":"10.1007\/978-3-030-28954-6_7"},{"key":"7_CR24","doi-asserted-by":"crossref","unstructured":"Oh, S.J., Fritz, M., Schiele, B.: Adversarial image perturbation for privacy protection a game theory perspective. In: 2017 IEEE International Conference on Computer Vision (ICCV), pp. 1491\u20131500. IEEE (2017)","DOI":"10.1109\/ICCV.2017.165"},{"key":"7_CR25","unstructured":"Papernot, N., McDaniel, P., Goodfellow, I.: Transferability in machine learning: from phenomena to black-box attacks using adversarial samples. CoRR abs\/1605.07277 (2016)"},{"key":"7_CR26","doi-asserted-by":"crossref","unstructured":"Papernot, N., McDaniel, P., Goodfellow, I., Jha, S., Celik, Z.B., Swami, A.: Practical black-box attacks against machine learning. In: Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security, pp. 506\u2013519. ACM (2017)","DOI":"10.1145\/3052973.3053009"},{"key":"7_CR27","doi-asserted-by":"crossref","unstructured":"Poursaeed, O., Katsman, I., Gao, B., Belongie, S.: Generative adversarial perturbations. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4422\u20134431 (2018)","DOI":"10.1109\/CVPR.2018.00465"},{"key":"7_CR28","doi-asserted-by":"crossref","unstructured":"Ribeiro, M.T., Singh, S., Guestrin, C.: Why should I trust you?: Explaining the predictions of any classifier. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1135\u20131144. ACM (2016)","DOI":"10.1145\/2939672.2939778"},{"key":"7_CR29","doi-asserted-by":"crossref","unstructured":"Shokri, R., Stronati, M., Song, C., Shmatikov, V.: Membership inference attacks against machine learning models. In: 2017 IEEE Symposium on Security and Privacy (SP), pp. 3\u201318. IEEE (2017)","DOI":"10.1109\/SP.2017.41"},{"key":"7_CR30","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. In: International Conference on Learning Representations (2015)"},{"key":"7_CR31","unstructured":"Simonyan, K., Vedaldi, A., Zisserman, A.: Deep inside convolutional networks: visualising image classification models and saliency maps. CoRR abs\/1312.6034 (2013)"},{"key":"7_CR32","unstructured":"Szegedy, C., et al.: Intriguing properties of neural networks. In: International Conference on Learning Representations (2014)"},{"key":"7_CR33","unstructured":"Tram\u00e8r, F., Zhang, F., Juels, A., Reiter, M.K., Ristenpart, T.: Stealing machine learning models via prediction APIs. In: 25th $$\\{$$USENIX$$\\}$$ Security Symposium ($$\\{$$USENIX$$\\}$$ Security 16), pp. 601\u2013618 (2016)"},{"key":"7_CR34","unstructured":"Yosinski, J., Clune, J., Nguyen, A.M., Fuchs, T.J., Lipson, H.: Understanding neural networks through deep visualization. CoRR abs\/1506.06579 (2015)"}],"container-title":["Lecture Notes in Computer Science","Explainable AI: Interpreting, Explaining and Visualizing Deep Learning"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-28954-6_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,1,19]],"date-time":"2021-01-19T18:58:20Z","timestamp":1611082700000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-28954-6_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030289539","9783030289546"],"references-count":34,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-28954-6_7","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"10 September 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}