乐胖代购免代理版

{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T21:18:32Z","timestamp":1730323112914,"version":"3.28.0"},"publisher-location":"New York, NY, USA","reference-count":38,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,11,9]],"date-time":"2021-11-09T00:00:00Z","timestamp":1636416000000},"content-version":"vor","delay-in-days":365,"URL":"http:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100000181","name":"Air Force Office of Scientific Research","doi-asserted-by":"publisher","award":["FA9550- 14-1-0351"],"id":[{"id":"10.13039\/100000181","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,11,9]]},"DOI":"10.1145\/3411495.3421356","type":"proceedings-article","created":{"date-parts":[[2020,11,5]],"date-time":"2020-11-05T23:35:56Z","timestamp":1604619356000},"page":"41-52","update-policy":"http:\/\/dx.doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":14,"title":["GANRED"],"prefix":"10.1145","author":[{"given":"Yuntao","family":"Liu","sequence":"first","affiliation":[{"name":"University of Maryland, College Park, College Park, MD, USA"}]},{"given":"Ankur","family":"Srivastava","sequence":"additional","affiliation":[{"name":"University of Maryland, College Park, College Park, MD, USA"}]}],"member":"320","published-online":{"date-parts":[[2020,11,9]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Csi neural network: Using side-channels to recover your artificial neural network information. arXiv preprint arXiv:1810.09076","author":"Batina Lejla","year":"2018","unstructured":"Lejla Batina , Shivam Bhasin , Dirmanto Jap , and Stjepan Picek . 2018. Csi neural network: Using side-channels to recover your artificial neural network information. arXiv preprint arXiv:1810.09076 ( 2018 ). Lejla Batina, Shivam Bhasin, Dirmanto Jap, and Stjepan Picek. 2018. Csi neural network: Using side-channels to recover your artificial neural network information. arXiv preprint arXiv:1810.09076 (2018)."},{"volume-title":"28th {USENIX} Security Symposium ({USENIX} Security 19). 515--532.","author":"Batina Lejla","unstructured":"Lejla Batina , Shivam Bhasin , Dirmanto Jap , and Stjepan Picek . 2019. {CSI}{NN} : Reverse Engineering of Neural Network Architectures Through Electromagnetic Side Channel . In 28th {USENIX} Security Symposium ({USENIX} Security 19). 515--532. Lejla Batina, Shivam Bhasin, Dirmanto Jap, and Stjepan Picek. 2019. {CSI}{NN}: Reverse Engineering of Neural Network Architectures Through Electromagnetic Side Channel. In 28th {USENIX} Security Symposium ({USENIX} Security 19). 515--532.","key":"e_1_3_2_1_2_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_3_1","DOI":"10.1007\/11894063_16"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_4_1","DOI":"10.1007\/978-3-319-96878-0_17"},{"key":"e_1_3_2_1_5_1","first-page":"35","article-title":"Privacy-preserving classification on deep neural network","volume":"2017","author":"Chabanne Herv\u00e9","year":"2017","unstructured":"Herv\u00e9 Chabanne , Amaury de Wargny , Jonathan Milgram , Constance Morel , and Emmanuel Prouff . 2017 . Privacy-preserving classification on deep neural network . IACR Cryptology ePrint Archive , Vol. 2017 (2017), 35 . Herv\u00e9 Chabanne, Amaury de Wargny, Jonathan Milgram, Constance Morel, and Emmanuel Prouff. 2017. Privacy-preserving classification on deep neural network. IACR Cryptology ePrint Archive, Vol. 2017 (2017), 35.","journal-title":"IACR Cryptology ePrint Archive"},{"key":"e_1_3_2_1_6_1","first-page":"167","article-title":"Analysis of Secure Caches and Timing-Based Side-Channel Attacks","volume":"2019","author":"Deng Shuwen","year":"2019","unstructured":"Shuwen Deng , Wenjie Xiong , and Jakub Szefer . 2019 . Analysis of Secure Caches and Timing-Based Side-Channel Attacks . IACR Cryptology ePrint Archive , Vol. 2019 (2019), 167 . Shuwen Deng, Wenjie Xiong, and Jakub Szefer. 2019. Analysis of Secure Caches and Timing-Based Side-Channel Attacks. IACR Cryptology ePrint Archive, Vol. 2019 (2019), 167.","journal-title":"IACR Cryptology ePrint Archive"},{"key":"e_1_3_2_1_7_1","volume-title":"Stealing Neural Networks via Timing Side Channels. arXiv preprint arXiv:1812.11720","author":"Duddu Vasisht","year":"2018","unstructured":"Vasisht Duddu , Debasis Samanta , D Vijay Rao , and Valentina E Balas . 2018. Stealing Neural Networks via Timing Side Channels. arXiv preprint arXiv:1812.11720 ( 2018 ). Vasisht Duddu, Debasis Samanta, D Vijay Rao, and Valentina E Balas. 2018. Stealing Neural Networks via Timing Side Channels. arXiv preprint arXiv:1812.11720 (2018)."},{"key":"e_1_3_2_1_8_1","volume-title":"International Conference on Machine Learning. 201--210","author":"Gilad-Bachrach Ran","year":"2016","unstructured":"Ran Gilad-Bachrach , Nathan Dowlin , Kim Laine , Kristin Lauter , Michael Naehrig , and John Wernsing . 2016 . Cryptonets: Applying neural networks to encrypted data with high throughput and accuracy . In International Conference on Machine Learning. 201--210 . Ran Gilad-Bachrach, Nathan Dowlin, Kim Laine, Kristin Lauter, Michael Naehrig, and John Wernsing. 2016. Cryptonets: Applying neural networks to encrypted data with high throughput and accuracy. In International Conference on Machine Learning. 201--210."},{"unstructured":"Ian Goodfellow Jean Pouget-Abadie Mehdi Mirza Bing Xu David Warde-Farley Sherjil Ozair Aaron Courville and Yoshua Bengio. 2014. Generative adversarial nets. In Advances in neural information processing systems. 2672--2680. Ian Goodfellow Jean Pouget-Abadie Mehdi Mirza Bing Xu David Warde-Farley Sherjil Ozair Aaron Courville and Yoshua Bengio. 2014. Generative adversarial nets. In Advances in neural information processing systems. 2672--2680.","key":"e_1_3_2_1_9_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_10_1","DOI":"10.1145\/3065913.3065915"},{"key":"e_1_3_2_1_11_1","volume-title":"Privado: Practical and Secure DNN Inference with Enclaves. arXiv preprint arXiv:1810.00602","author":"Grover Karan","year":"2018","unstructured":"Karan Grover , Shruti Tople , Shweta Shinde , Ranjita Bhagwan , and Ramachandran Ramjee . 2018 . Privado: Practical and Secure DNN Inference with Enclaves. arXiv preprint arXiv:1810.00602 (2018). Karan Grover, Shruti Tople, Shweta Shinde, Ranjita Bhagwan, and Ramachandran Ramjee. 2018. Privado: Practical and Secure DNN Inference with Enclaves. arXiv preprint arXiv:1810.00602 (2018)."},{"volume-title":"24th {USENIX} Security Symposium ({USENIX} Security 15). 897--912.","author":"Gruss Daniel","unstructured":"Daniel Gruss , Raphael Spreitzer , and Stefan Mangard . 2015. Cache template attacks: Automating attacks on inclusive last-level caches . In 24th {USENIX} Security Symposium ({USENIX} Security 15). 897--912. Daniel Gruss, Raphael Spreitzer, and Stefan Mangard. 2015. Cache template attacks: Automating attacks on inclusive last-level caches. In 24th {USENIX} Security Symposium ({USENIX} Security 15). 897--912.","key":"e_1_3_2_1_12_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_13_1","DOI":"10.1109\/SP.2016.11"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_14_1","DOI":"10.1109\/SP.2011.22"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_15_1","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_2_1_16_1","volume-title":"Ian Rackow, Kevin Kulda, Dana Dachman-Soled, and Tudor Dumitracs.","author":"Hong Sanghyun","year":"2018","unstructured":"Sanghyun Hong , Michael Davinroy , Yi?itcan Kaya , Stuart Nevans Locke , Ian Rackow, Kevin Kulda, Dana Dachman-Soled, and Tudor Dumitracs. 2018 . Security Analysis of Deep Neural Networks Operating in the Presence of Cache Side-Channel Attacks . arXiv preprint arXiv:1810.03487 (2018). Sanghyun Hong, Michael Davinroy, Yi?itcan Kaya, Stuart Nevans Locke, Ian Rackow, Kevin Kulda, Dana Dachman-Soled, and Tudor Dumitracs. 2018. Security Analysis of Deep Neural Networks Operating in the Presence of Cache Side-Channel Attacks. arXiv preprint arXiv:1810.03487 (2018)."},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_17_1","DOI":"10.1145\/3195970.3196105"},{"key":"e_1_3_2_1_18_1","volume-title":"PRADA: Protecting against DNN Model Stealing Attacks. arXiv preprint arXiv:1805.02628","author":"Juuti Mika","year":"2018","unstructured":"Mika Juuti , Sebastian Szyller , Alexey Dmitrenko , Samuel Marchal , and N Asokan . 2018 . PRADA: Protecting against DNN Model Stealing Attacks. arXiv preprint arXiv:1805.02628 (2018). Mika Juuti, Sebastian Szyller, Alexey Dmitrenko, Samuel Marchal, and N Asokan. 2018. PRADA: Protecting against DNN Model Stealing Attacks. arXiv preprint arXiv:1805.02628 (2018)."},{"unstructured":"Alex Krizhevsky Ilya Sutskever and Geoffrey E Hinton. 2012. Imagenet classification with deep convolutional neural networks. In Advances in neural information processing systems. 1097--1105. Alex Krizhevsky Ilya Sutskever and Geoffrey E Hinton. 2012. Imagenet classification with deep convolutional neural networks. In Advances in neural information processing systems. 1097--1105.","key":"e_1_3_2_1_19_1"},{"key":"e_1_3_2_1_20_1","volume-title":"Mitigating Reverse Engineering Attacks on Deep Neural Networks. In 2019 IEEE Computer Society Annual Symposium on VLSI (ISVLSI). IEEE, 657--662","author":"Liu Yuntao","year":"2019","unstructured":"Yuntao Liu , Dana Dachman-Soled , and Ankur Srivastava . 2019 . Mitigating Reverse Engineering Attacks on Deep Neural Networks. In 2019 IEEE Computer Society Annual Symposium on VLSI (ISVLSI). IEEE, 657--662 . Yuntao Liu, Dana Dachman-Soled, and Ankur Srivastava. 2019. Mitigating Reverse Engineering Attacks on Deep Neural Networks. In 2019 IEEE Computer Society Annual Symposium on VLSI (ISVLSI). IEEE, 657--662."},{"key":"e_1_3_2_1_21_1","volume-title":"Understanding membership inferences on well-generalized learning models. arXiv preprint arXiv:1802.04889","author":"Long Yunhui","year":"2018","unstructured":"Yunhui Long , Vincent Bindschaedler , Lei Wang , Diyue Bu , Xiaofeng Wang , Haixu Tang , Carl A Gunter , and Kai Chen . 2018. Understanding membership inferences on well-generalized learning models. arXiv preprint arXiv:1802.04889 ( 2018 ). Yunhui Long, Vincent Bindschaedler, Lei Wang, Diyue Bu, Xiaofeng Wang, Haixu Tang, Carl A Gunter, and Kai Chen. 2018. Understanding membership inferences on well-generalized learning models. arXiv preprint arXiv:1802.04889 (2018)."},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_22_1","DOI":"10.1109\/SP.2017.12"},{"volume-title":"25th {USENIX} Security Symposium ({USENIX} Security 16). 619--636.","author":"Ohrimenko Olga","unstructured":"Olga Ohrimenko , Felix Schuster , C\u00e9dric Fournet , Aastha Mehta , Sebastian Nowozin , Kapil Vaswani , and Manuel Costa . 2016. Oblivious multi-party machine learning on trusted processors . In 25th {USENIX} Security Symposium ({USENIX} Security 16). 619--636. Olga Ohrimenko, Felix Schuster, C\u00e9dric Fournet, Aastha Mehta, Sebastian Nowozin, Kapil Vaswani, and Manuel Costa. 2016. Oblivious multi-party machine learning on trusted processors. In 25th {USENIX} Security Symposium ({USENIX} Security 16). 619--636.","key":"e_1_3_2_1_23_1"},{"volume-title":"Cryptographers? track at the RSA conference","author":"Osvik Dag Arne","unstructured":"Dag Arne Osvik , Adi Shamir , and Eran Tromer . 2006. Cache attacks and countermeasures: the case of AES . In Cryptographers? track at the RSA conference . Springer , 1--20. Dag Arne Osvik, Adi Shamir, and Eran Tromer. 2006. Cache attacks and countermeasures: the case of AES. In Cryptographers? track at the RSA conference. Springer, 1--20.","key":"e_1_3_2_1_24_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_25_1","DOI":"10.1145\/3052973.3053009"},{"unstructured":"Colin Percival. 2005. Cache missing for fun and profit. Colin Percival. 2005. Cache missing for fun and profit.","key":"e_1_3_2_1_26_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_27_1","DOI":"10.1145\/3195970.3196023"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_28_1","DOI":"10.1109\/SP.2017.41"},{"key":"e_1_3_2_1_29_1","volume-title":"Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556","author":"Simonyan Karen","year":"2014","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_30_1","volume-title":"Slalom: Fast, verifiable and private execution of neural networks in trusted hardware. arXiv preprint arXiv:1806.03287","author":"Tramer Florian","year":"2018","unstructured":"Florian Tramer and Dan Boneh . 2018 . Slalom: Fast, verifiable and private execution of neural networks in trusted hardware. arXiv preprint arXiv:1806.03287 (2018). Florian Tramer and Dan Boneh. 2018. Slalom: Fast, verifiable and private execution of neural networks in trusted hardware. arXiv preprint arXiv:1806.03287 (2018)."},{"volume-title":"25th {USENIX} Security Symposium ({USENIX} Security 16). 601--618.","author":"Tram\u00e8r Florian","unstructured":"Florian Tram\u00e8r , Fan Zhang , Ari Juels , Michael K Reiter , and Thomas Ristenpart . 2016. Stealing machine learning models via prediction apis . In 25th {USENIX} Security Symposium ({USENIX} Security 16). 601--618. Florian Tram\u00e8r, Fan Zhang, Ari Juels, Michael K Reiter, and Thomas Ristenpart. 2016. Stealing machine learning models via prediction apis. In 25th {USENIX} Security Symposium ({USENIX} Security 16). 601--618.","key":"e_1_3_2_1_31_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_32_1","DOI":"10.1145\/3133956.3134038"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_33_1","DOI":"10.1145\/3310273.3323070"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_34_1","DOI":"10.1145\/3274694.3274696"},{"key":"e_1_3_2_1_35_1","volume-title":"Crypto-nets: Neural networks over encrypted data. arXiv preprint arXiv:1412.6181","author":"Xie Pengtao","year":"2014","unstructured":"Pengtao Xie , Misha Bilenko , Tom Finley , Ran Gilad-Bachrach , Kristin Lauter , and Michael Naehrig . 2014 . Crypto-nets: Neural networks over encrypted data. arXiv preprint arXiv:1412.6181 (2014). Pengtao Xie, Misha Bilenko, Tom Finley, Ran Gilad-Bachrach, Kristin Lauter, and Michael Naehrig. 2014. Crypto-nets: Neural networks over encrypted data. arXiv preprint arXiv:1412.6181 (2014)."},{"key":"e_1_3_2_1_36_1","volume-title":"29th USENIX Security Symposium (USENIX Security 20)","author":"Yan Mengjia","year":"2020","unstructured":"Mengjia Yan , Christopher Fletcher , and Josep Torrellas . 2020 . Cache Telepathy: Leveraging Shared Resource Attacks to Learn DNN Architectures . In 29th USENIX Security Symposium (USENIX Security 20) . USENIX Association, Boston, MA. https:\/\/www.usenix.org\/conference\/usenixsecurity20\/presentation\/yan Mengjia Yan, Christopher Fletcher, and Josep Torrellas. 2020. Cache Telepathy: Leveraging Shared Resource Attacks to Learn DNN Architectures. In 29th USENIX Security Symposium (USENIX Security 20). USENIX Association, Boston, MA. https:\/\/www.usenix.org\/conference\/usenixsecurity20\/presentation\/yan"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_37_1","DOI":"10.1109\/HPCA.2018.00024"},{"volume-title":"L3 cache side-channel attack. In 23rd {USENIX} Security Symposium ({USENIX} Security 14). 719--732.","author":"Yarom Yuval","unstructured":"Yuval Yarom and Katrina Falkner . 2014. FLUSH+RELOAD : a high resolution, low noise , L3 cache side-channel attack. In 23rd {USENIX} Security Symposium ({USENIX} Security 14). 719--732. Yuval Yarom and Katrina Falkner. 2014. FLUSH+RELOAD: a high resolution, low noise, L3 cache side-channel attack. In 23rd {USENIX} Security Symposium ({USENIX} Security 14). 719--732.","key":"e_1_3_2_1_38_1"}],"event":{"sponsor":["SIGSAC ACM Special Interest Group on Security, Audit, and Control"],"acronym":"CCS '20","name":"CCS '20: 2020 ACM SIGSAC Conference on Computer and Communications Security","location":"Virtual Event USA"},"container-title":["Proceedings of the 2020 ACM SIGSAC Conference on Cloud Computing Security Workshop"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/abs\/10.1145\/3411495.3421356","content-type":"text\/html","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3411495.3421356","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3411495.3421356","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,11]],"date-time":"2023-01-11T18:20:17Z","timestamp":1673461217000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3411495.3421356"}},"subtitle":["GAN-based Reverse Engineering of DNNs via Cache Side-Channel"],"short-title":[],"issued":{"date-parts":[[2020,11,9]]},"references-count":38,"alternative-id":["10.1145\/3411495.3421356","10.1145\/3411495"],"URL":"https:\/\/doi.org\/10.1145\/3411495.3421356","relation":{},"subject":[],"published":{"date-parts":[[2020,11,9]]},"assertion":[{"value":"2020-11-09","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}