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DNN Model Zoo. https:\/\/github.com\/BVLC\/caffe\/wiki\/Model-Zoo\/."},{"key":"e_1_3_2_1_5_1","volume-title":"Digital image steganography: Survey and analysis of current methods. Signal processing 90, 3","author":"Cheddad Abbas","year":"2010","unstructured":"Abbas Cheddad , Joan Condell , Kevin Curran , and Paul Mc\u00a0Kevitt . 2010. Digital image steganography: Survey and analysis of current methods. Signal processing 90, 3 ( 2010 ), 727\u2013752. Abbas Cheddad, Joan Condell, Kevin Curran, and Paul Mc\u00a0Kevitt. 2010. Digital image steganography: Survey and analysis of current methods. Signal processing 90, 3 (2010), 727\u2013752."},{"key":"e_1_3_2_1_6_1","unstructured":"Xinyun Chen Chang Liu Bo Li Kimberly Lu and Dawn Song. 2017. Targeted backdoor attacks on deep learning systems using data poisoning. arXiv preprint arXiv:1712.05526(2017).  Xinyun Chen Chang Liu Bo Li Kimberly Lu and Dawn Song. 2017. Targeted backdoor attacks on deep learning systems using data poisoning. arXiv preprint arXiv:1712.05526(2017)."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2002.1039052"},{"key":"e_1_3_2_1_9_1","volume-title":"International Workshop on Information Hiding. Springer, 355\u2013372","author":"Dumitrescu Sorina","year":"2002","unstructured":"Sorina Dumitrescu , Xiaolin Wu , and Zhe Wang . 2002 . Detection of LSB steganography via sample pair analysis . In International Workshop on Information Hiding. Springer, 355\u2013372 . Sorina Dumitrescu, Xiaolin Wu, and Zhe Wang. 2002. Detection of LSB steganography via sample pair analysis. In International Workshop on Information Hiding. Springer, 355\u2013372."},{"key":"e_1_3_2_1_10_1","volume-title":"Robust Physical-World Attacks on Deep Learning Models. arXiv preprint arXiv:1707.08945 1","author":"Evtimov Ivan","year":"2017","unstructured":"Ivan Evtimov , Kevin Eykholt , Earlence Fernandes , Tadayoshi Kohno , Bo Li , Atul Prakash , Amir Rahmati , and Dawn Song . 2017. Robust Physical-World Attacks on Deep Learning Models. arXiv preprint arXiv:1707.08945 1 ( 2017 ). Ivan Evtimov, Kevin Eykholt, Earlence Fernandes, Tadayoshi Kohno, Bo Li, Atul Prakash, Amir Rahmati, and Dawn Song. 2017. Robust Physical-World Attacks on Deep Learning Models. arXiv preprint arXiv:1707.08945 1 (2017)."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/1232454.1232466"},{"key":"e_1_3_2_1_12_1","volume-title":"Deep learning","author":"Goodfellow Ian","unstructured":"Ian Goodfellow , Yoshua Bengio , and Aaron Courville . 2016. Deep learning . MIT press . Ian Goodfellow, Yoshua Bengio, and Aaron Courville. 2016. Deep learning. MIT press."},{"key":"e_1_3_2_1_13_1","unstructured":"Ian\u00a0J Goodfellow Jonathon Shlens and Christian Szegedy. 2014. Explaining and harnessing adversarial examples. arXiv preprint arXiv:1412.6572(2014).  Ian\u00a0J Goodfellow Jonathon Shlens and Christian Szegedy. 2014. Explaining and harnessing adversarial examples. arXiv preprint arXiv:1412.6572(2014)."},{"key":"e_1_3_2_1_14_1","unstructured":"Google. 2018. Google Cloud Machine Learning. https:\/\/cloud.google.com\/products\/machine-learning\/.  Google. 2018. Google Cloud Machine Learning. https:\/\/cloud.google.com\/products\/machine-learning\/."},{"key":"e_1_3_2_1_15_1","volume-title":"Badnets: Identifying vulnerabilities in the machine learning model supply chain. arXiv preprint arXiv:1708.06733(2017).","author":"Gu Tianyu","year":"2017","unstructured":"Tianyu Gu , Brendan Dolan-Gavitt , and Siddharth Garg . 2017 . Badnets: Identifying vulnerabilities in the machine learning model supply chain. arXiv preprint arXiv:1708.06733(2017). Tianyu Gu, Brendan Dolan-Gavitt, and Siddharth Garg. 2017. Badnets: Identifying vulnerabilities in the machine learning model supply chain. arXiv preprint arXiv:1708.06733(2017)."},{"key":"e_1_3_2_1_16_1","unstructured":"Song Han Huizi Mao and William\u00a0J Dally. 2015. Deep compression: Compressing deep neural networks with pruning trained quantization and huffman coding. arXiv preprint arXiv:1510.00149(2015).  Song Han Huizi Mao and William\u00a0J Dally. 2015. Deep compression: Compressing deep neural networks with pruning trained quantization and huffman coding. arXiv preprint arXiv:1510.00149(2015)."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_2_1_18_1","volume-title":"Reducing the dimensionality of data with neural networks. science 313, 5786","author":"Hinton E","year":"2006","unstructured":"Geoffrey\u00a0 E Hinton and Ruslan\u00a0 R Salakhutdinov . 2006. Reducing the dimensionality of data with neural networks. science 313, 5786 ( 2006 ), 504\u2013507. Geoffrey\u00a0E Hinton and Ruslan\u00a0R Salakhutdinov. 2006. Reducing the dimensionality of data with neural networks. science 313, 5786 (2006), 504\u2013507."},{"key":"e_1_3_2_1_19_1","volume-title":"Mobilenets: Efficient convolutional neural networks for mobile vision applications. arXiv preprint arXiv:1704.04861(2017).","author":"Howard G","year":"2017","unstructured":"Andrew\u00a0 G Howard , Menglong Zhu , Bo Chen , Dmitry Kalenichenko , Weijun Wang , Tobias Weyand , Marco Andreetto , and Hartwig Adam . 2017 . Mobilenets: Efficient convolutional neural networks for mobile vision applications. arXiv preprint arXiv:1704.04861(2017). Andrew\u00a0G Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, and Hartwig Adam. 2017. 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Squeezenet: Alexnet-level accuracy with 50x fewer parameters and< 0.5 mb model size. arXiv preprint arXiv:1602.07360(2016). Forrest\u00a0N Iandola, Song Han, Matthew\u00a0W Moskewicz, Khalid Ashraf, William\u00a0J Dally, and Kurt Keutzer. 2016. Squeezenet: Alexnet-level accuracy with 50x fewer parameters and< 0.5 mb model size. arXiv preprint arXiv:1602.07360(2016)."},{"key":"e_1_3_2_1_22_1","unstructured":"Facebook Inc.2017. Open Neural Network Exchange (ONNX). https:\/\/onnx.ai\/.  Facebook Inc.2017. Open Neural Network Exchange (ONNX). https:\/\/onnx.ai\/."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2018.00057"},{"key":"e_1_3_2_1_24_1","volume-title":"Transactions on","author":"Kharrazi Mehdi","unstructured":"Mehdi Kharrazi , Husrev\u00a0 T Sencar , and Nasir Memon . 2006. Improving steganalysis by fusion techniques: A case study with image steganography . In Transactions on Data Hiding and Multimedia Security I. Springer , 123\u2013137. Mehdi Kharrazi, Husrev\u00a0T Sencar, and Nasir Memon. 2006. Improving steganalysis by fusion techniques: A case study with image steganography. In Transactions on Data Hiding and Multimedia Security I. Springer, 123\u2013137."},{"key":"e_1_3_2_1_25_1","unstructured":"Alex Krizhevsky Ilya Sutskever and Geoffrey\u00a0E Hinton. 2012. Imagenet classification with deep convolutional neural networks. In Advances in neural information processing systems. 1097\u20131105.  Alex Krizhevsky Ilya Sutskever and Geoffrey\u00a0E Hinton. 2012. Imagenet classification with deep convolutional neural networks. In Advances in neural information processing systems. 1097\u20131105."},{"key":"e_1_3_2_1_26_1","volume-title":"Deep learning. Nature 521, 7553","author":"LeCun Yann","year":"2015","unstructured":"Yann LeCun , Yoshua Bengio , and Geoffrey Hinton . 2015. Deep learning. Nature 521, 7553 ( 2015 ), 436\u2013444. Yann LeCun, Yoshua Bengio, and Geoffrey Hinton. 2015. Deep learning. Nature 521, 7553 (2015), 436\u2013444."},{"key":"e_1_3_2_1_27_1","first-page":"142","article-title":"A survey on image steganography and steganalysis","volume":"2","author":"Li Bin","year":"2011","unstructured":"Bin Li , Junhui He , Jiwu Huang , and Yun\u00a0Qing Shi . 2011 . A survey on image steganography and steganalysis . Journal of Information Hiding and Multimedia Signal Processing 2 , 2(2011), 142 \u2013 172 . Bin Li, Junhui He, Jiwu Huang, and Yun\u00a0Qing Shi. 2011. A survey on image steganography and steganalysis. Journal of Information Hiding and Multimedia Signal Processing 2, 2(2011), 142\u2013172.","journal-title":"Journal of Information Hiding and Multimedia Signal Processing"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCD.2017.16"},{"key":"e_1_3_2_1_30_1","unstructured":"MalwareWiki. 2018. Fork Bomb. http:\/\/malware.wikia.com\/wiki\/Fork_Bomb\/.  MalwareWiki. 2018. Fork Bomb. http:\/\/malware.wikia.com\/wiki\/Fork_Bomb\/."},{"key":"e_1_3_2_1_31_1","volume-title":"Steganography: A safe haven for malware. https:\/\/securityintelligence.com\/steganography-a-safe-haven-for-malware\/.","author":"McMillen D","year":"2017","unstructured":"D McMillen . 2017 . Steganography: A safe haven for malware. https:\/\/securityintelligence.com\/steganography-a-safe-haven-for-malware\/. (2017). D McMillen. 2017. Steganography: A safe haven for malware. https:\/\/securityintelligence.com\/steganography-a-safe-haven-for-malware\/. (2017)."},{"key":"e_1_3_2_1_32_1","unstructured":"Metadefender. 2019. Multiple Security Engines. http:\/\/www.metadefender.com\/.  Metadefender. 2019. Multiple Security Engines. http:\/\/www.metadefender.com\/."},{"key":"e_1_3_2_1_33_1","unstructured":"Microsoft. 2018. Microsoft Azure Machine Learning. https:\/\/azure.microsoft.com\/en-us\/services\/machine-learning\/.  Microsoft. 2018. Microsoft Azure Machine Learning. https:\/\/azure.microsoft.com\/en-us\/services\/machine-learning\/."},{"key":"e_1_3_2_1_34_1","unstructured":"Yuval Nativ. 2015. theZoo aka Malware DB. http:\/\/thezoo.morirt.com\/.  Yuval Nativ. 2015. theZoo aka Malware DB. http:\/\/thezoo.morirt.com\/."},{"key":"e_1_3_2_1_35_1","volume-title":"2016 IEEE European Symposium on. IEEE, 372\u2013387","author":"Papernot Nicolas","year":"2016","unstructured":"Nicolas Papernot , Patrick McDaniel , Somesh Jha , Matt Fredrikson , Z\u00a0Berkay Celik , and Ananthram Swami . 2016 . The limitations of deep learning in adversarial settings. In Security and Privacy (EuroS&P) , 2016 IEEE European Symposium on. IEEE, 372\u2013387 . Nicolas Papernot, Patrick McDaniel, Somesh Jha, Matt Fredrikson, Z\u00a0Berkay Celik, and Ananthram Swami. 2016. The limitations of deep learning in adversarial settings. In Security and Privacy (EuroS&P), 2016 IEEE European Symposium on. IEEE, 372\u2013387."},{"key":"e_1_3_2_1_36_1","volume-title":"Alphago: Mastering the ancient game of go with machine learning. Research Blog","author":"Silver David","year":"2016","unstructured":"David Silver and Demis Hassabis . 2016 . Alphago: Mastering the ancient game of go with machine learning. Research Blog (2016). David Silver and Demis Hassabis. 2016. Alphago: Mastering the ancient game of go with machine learning. Research Blog (2016)."},{"key":"e_1_3_2_1_37_1","unstructured":"Karen Simonyan and Andrew Zisserman. 2014. Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556(2014).  Karen Simonyan and Andrew Zisserman. 2014. Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556(2014)."},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3134077"},{"key":"e_1_3_2_1_39_1","volume-title":"International Conference on Information Security and Cryptology. Springer, 496\u2013515","author":"Suarez-Tangil Guillermo","year":"2014","unstructured":"Guillermo Suarez-Tangil , Juan\u00a0 E Tapiador , and Pedro Peris-Lopez . 2014 . Stegomalware: Playing hide and seek with malicious components in smartphone apps . In International Conference on Information Security and Cryptology. Springer, 496\u2013515 . Guillermo Suarez-Tangil, Juan\u00a0E Tapiador, and Pedro Peris-Lopez. 2014. Stegomalware: Playing hide and seek with malicious components in smartphone apps. In International Conference on Information Security and Cryptology. Springer, 496\u2013515."},{"key":"e_1_3_2_1_40_1","volume-title":"AITP 2016","author":"Szegedy Christian","year":"2016","unstructured":"Christian Szegedy . 2016 . An overview of deep learning . AITP 2016 (2016). Christian Szegedy. 2016. An overview of deep learning. AITP 2016 (2016)."},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"e_1_3_2_1_43_1","unstructured":"Tensorflow. 2019. TensorFlow models are programs. https:\/\/github.com\/tensorflow\/tensorflow\/blob\/master\/SECURITY.md\/.  Tensorflow. 2019. TensorFlow models are programs. https:\/\/github.com\/tensorflow\/tensorflow\/blob\/master\/SECURITY.md\/."},{"key":"e_1_3_2_1_44_1","unstructured":"Florian Tram\u00e8r Nicolas Papernot Ian Goodfellow Dan Boneh and Patrick McDaniel. 2017. The Space of Transferable Adversarial Examples. arXiv preprint arXiv:1704.03453(2017).  Florian Tram\u00e8r Nicolas Papernot Ian Goodfellow Dan Boneh and Patrick McDaniel. 2017. The Space of Transferable Adversarial Examples. arXiv preprint arXiv:1704.03453(2017)."},{"key":"e_1_3_2_1_45_1","unstructured":"Samir Vaidya. 2019. OpenStego. https:\/\/github.com\/syvaidya\/openstego\/.  Samir Vaidya. 2019. OpenStego. https:\/\/github.com\/syvaidya\/openstego\/."},{"key":"e_1_3_2_1_46_1","volume-title":"International workshop on information hiding. Springer, 61\u201376","author":"Westfeld Andreas","year":"1999","unstructured":"Andreas Westfeld and Andreas Pfitzmann . 1999 . Attacks on steganographic systems . In International workshop on information hiding. Springer, 61\u201376 . Andreas Westfeld and Andreas Pfitzmann. 1999. Attacks on steganographic systems. In International workshop on information hiding. 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