{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,27]],"date-time":"2026-09-27T03:46:07Z","timestamp":1790480767210,"version":"4.1.0"},"publisher-location":"New York, NY, USA","reference-count":30,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,6,23]],"date-time":"2022-06-23T00:00:00Z","timestamp":1655942400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,6,23]]},"DOI":"10.1145\/3531536.3532950","type":"proceedings-article","created":{"date-parts":[[2022,6,23]],"date-time":"2022-06-23T22:18:44Z","timestamp":1656022724000},"page":"39-50","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["BlindSpot: Watermarking Through Fairness"],"prefix":"10.1145","author":[{"given":"Sofiane","family":"Lounici","sequence":"first","affiliation":[{"name":"SAP Security Research, Mougins, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Melek","family":"\u00d6nen","sequence":"additional","affiliation":[{"name":"EURECOM, Sophia-Antipolis, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Orhan","family":"Ermis","sequence":"additional","affiliation":[{"name":"Luxembourg Institute of Science and Technology (LIST), Luxembourg, Luxembourg"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Slim","family":"Trabelsi","sequence":"additional","affiliation":[{"name":"SAP Security Research, Mougins, France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2022,6,23]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"27th USENIX Security Symposium.","author":"Adi Yossi","year":"2018","unstructured":"Yossi Adi , Carsten Baum , Moustapha Cisse , Benny Pinkas , and Joseph Keshet . 2018 . Turning your weakness into a strength: Watermarking deep neural networks by backdooring . In 27th USENIX Security Symposium. Yossi Adi, Carsten Baum, Moustapha Cisse, Benny Pinkas, and Joseph Keshet. 2018. Turning your weakness into a strength: Watermarking deep neural networks by backdooring. In 27th USENIX Security Symposium."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3437880.3460399"},{"key":"e_1_3_2_1_3_1","volume-title":"Fully homomorphic encryption: Computations with a blindfold","author":"Beunardeau Marc","year":"2016","unstructured":"Marc Beunardeau , Aisling Connolly , Remi Geraud , and David Naccache . 2016. Fully homomorphic encryption: Computations with a blindfold . IEEE Security & Privacy ( 2016 ). Marc Beunardeau, Aisling Connolly, Remi Geraud, and David Naccache. 2016. Fully homomorphic encryption: Computations with a blindfold. IEEE Security & Privacy (2016)."},{"key":"e_1_3_2_1_4_1","volume-title":"A Survey on Model Watermarking Neural Networks. arXiv preprint arXiv:2009.12153","author":"Boenisch Franziska","year":"2020","unstructured":"Franziska Boenisch . 2020. A Survey on Model Watermarking Neural Networks. arXiv preprint arXiv:2009.12153 ( 2020 ). Franziska Boenisch. 2020. A Survey on Model Watermarking Neural Networks. arXiv preprint arXiv:2009.12153 (2020)."},{"key":"e_1_3_2_1_5_1","volume-title":"Fairness in machine learning: A survey. arXiv preprint arXiv:2010.04053","author":"Caton Simon","year":"2020","unstructured":"Simon Caton and Christian Haas . 2020. Fairness in machine learning: A survey. arXiv preprint arXiv:2010.04053 ( 2020 ). Simon Caton and Christian Haas. 2020. Fairness in machine learning: A survey. arXiv preprint arXiv:2010.04053 (2020)."},{"key":"e_1_3_2_1_6_1","unstructured":"D. Dua and C. Graff. 2017. UCI Machine Learning Repository. http:\/\/archive.ics.uci.edu\/ml\/index.php\/.  D. Dua and C. Graff. 2017. UCI Machine Learning Repository. http:\/\/archive.ics.uci.edu\/ml\/index.php\/."},{"key":"e_1_3_2_1_7_1","volume-title":"Evolutionary trigger set generation for dnn black-box watermarking. arXiv preprint arXiv:1906.04411","author":"Guo Jia","year":"2019","unstructured":"Jia Guo and Miodrag Potkonjak . 2019. Evolutionary trigger set generation for dnn black-box watermarking. arXiv preprint arXiv:1906.04411 ( 2019 ). Jia Guo and Miodrag Potkonjak. 2019. Evolutionary trigger set generation for dnn black-box watermarking. arXiv preprint arXiv:1906.04411 (2019)."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/SDS.2019.8768572"},{"key":"e_1_3_2_1_10_1","volume-title":"Entangled Watermarks as a Defense against Model Extraction. arXiv preprint arXiv:2002.12200","author":"Jia Hengrui","year":"2020","unstructured":"Hengrui Jia , Christopher A Choquette-Choo , and Nicolas Papernot . 2020. Entangled Watermarks as a Defense against Model Extraction. arXiv preprint arXiv:2002.12200 ( 2020 ). Hengrui Jia, Christopher A Choquette-Choo, and Nicolas Papernot. 2020. Entangled Watermarks as a Defense against Model Extraction. arXiv preprint arXiv:2002.12200 (2020)."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/EuroSP.2019.00044"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3437880.3460409"},{"key":"e_1_3_2_1_13_1","volume-title":"Learning multiple layers of features from tiny images. Citeseer","author":"Krizhevsky Alex","year":"2009","unstructured":"Alex Krizhevsky . 2009. Learning multiple layers of features from tiny images. Citeseer ( 2009 ). Alex Krizhevsky. 2009. Learning multiple layers of features from tiny images. Citeseer (2009)."},{"key":"e_1_3_2_1_14_1","volume-title":"Watermarking Deep Neural Networks with Greedy Residuals. In International Conference on Machine Learning.","author":"Liu Hanwen","year":"2021","unstructured":"Hanwen Liu , Zhenyu Weng , and Yuesheng Zhu . 2021 . Watermarking Deep Neural Networks with Greedy Residuals. In International Conference on Machine Learning. Hanwen Liu, Zhenyu Weng, and Yuesheng Zhu. 2021. Watermarking Deep Neural Networks with Greedy Residuals. In International Conference on Machine Learning."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.5220\/0010560600002998"},{"key":"e_1_3_2_1_16_1","volume-title":"SoK: How Robust is Image Classification Deep Neural Network Watermarking?(Extended Version). arXiv preprint arXiv:2108.04974","author":"Lukas Nils","year":"2021","unstructured":"Nils Lukas , Edward Jiang , Xinda Li , and Florian Kerschbaum . 2021. SoK: How Robust is Image Classification Deep Neural Network Watermarking?(Extended Version). arXiv preprint arXiv:2108.04974 ( 2021 ). Nils Lukas, Edward Jiang, Xinda Li, and Florian Kerschbaum. 2021. SoK: How Robust is Image Classification Deep Neural Network Watermarking?(Extended Version). arXiv preprint arXiv:2108.04974 (2021)."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"crossref","unstructured":"Ninareh Mehrabi Muhammad Naveed Fred Morstatter and Aram Galstyan. 2020. Exacerbating Algorithmic Bias through Fairness Attacks.  Ninareh Mehrabi Muhammad Naveed Fred Morstatter and Aram Galstyan. 2020. Exacerbating Algorithmic Bias through Fairness Attacks.","DOI":"10.1609\/aaai.v35i10.17080"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00509"},{"key":"e_1_3_2_1_19_1","volume-title":"Pre-trained convolutional neural networks as feature extractors toward improved malaria parasite detection in thin blood smear images. PeerJ","author":"Rajaraman Sivaramakrishnan","year":"2018","unstructured":"Sivaramakrishnan Rajaraman , Sameer K Antani , Mahdieh Poostchi , Kamolrat Silamut , Md A Hossain , Richard J Maude , Stefan Jaeger , and George R Thoma . 2018. Pre-trained convolutional neural networks as feature extractors toward improved malaria parasite detection in thin blood smear images. PeerJ ( 2018 ). Sivaramakrishnan Rajaraman, Sameer K Antani, Mahdieh Poostchi, Kamolrat Silamut, Md A Hossain, Richard J Maude, Stefan Jaeger, and George R Thoma. 2018. Pre-trained convolutional neural networks as feature extractors toward improved malaria parasite detection in thin blood smear images. PeerJ (2018)."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"e_1_3_2_1_21_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 AndrewZisserman. 2014. Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 ( 2014 ). Karen Simonyan and AndrewZisserman. 2014. Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 (2014)."},{"key":"e_1_3_2_1_22_1","volume-title":"Poisoning attacks on algorithmic fairness. arXiv preprint arXiv:2004.07401","author":"Solans David","year":"2020","unstructured":"David Solans , Battista Biggio , and Carlos Castillo . 2020. Poisoning attacks on algorithmic fairness. arXiv preprint arXiv:2004.07401 ( 2020 ). David Solans, Battista Biggio, and Carlos Castillo. 2020. Poisoning attacks on algorithmic fairness. arXiv preprint arXiv:2004.07401 (2020)."},{"key":"e_1_3_2_1_23_1","volume-title":"Samuel Marchal, and N Asokan.","author":"Szyller Sebastian","year":"2019","unstructured":"Sebastian Szyller , Buse Gul Atli , Samuel Marchal, and N Asokan. 2019 . Dawn : Dynamic adversarial watermarking of neural networks. arXiv preprint arXiv:1906.00830 (2019). Sebastian Szyller, Buse Gul Atli, Samuel Marchal, and N Asokan. 2019. Dawn: Dynamic adversarial watermarking of neural networks. arXiv preprint arXiv:1906.00830 (2019)."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.5555\/3241094.3241142"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00474"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3078971.3078974"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2019.00031"},{"key":"e_1_3_2_1_28_1","volume-title":"andWeiqiang Liu","author":"Xue Mingfu","year":"2021","unstructured":"HaoqiWang, Mingfu Xue , Shichang Sun , Yushu Zhang , JianWang , andWeiqiang Liu . 2021 . Detect and remove watermark in deep neural networks via generative adversarial networks. arXiv preprint arXiv:2106.08104 (2021). HaoqiWang, Mingfu Xue, Shichang Sun, Yushu Zhang, JianWang, andWeiqiang Liu. 2021. Detect and remove watermark in deep neural networks via generative adversarial networks. arXiv preprint arXiv:2106.08104 (2021)."},{"key":"e_1_3_2_1_29_1","unstructured":"Han Xiao Kashif Rasul and Roland Vollgraf. 2017. Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.  Han Xiao Kashif Rasul and Roland Vollgraf. 2017. Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms."},{"key":"e_1_3_2_1_30_1","volume-title":"Secure neural network watermarking protocol against forging attack. EURASIP Journal on Image and Video Processing","author":"Zhu Renjie","year":"2020","unstructured":"Renjie Zhu , Xinpeng Zhang , Mengte Shi , and Zhenjun Tang . 2020. Secure neural network watermarking protocol against forging attack. EURASIP Journal on Image and Video Processing ( 2020 ). Renjie Zhu, Xinpeng Zhang, Mengte Shi, and Zhenjun Tang. 2020. Secure neural network watermarking protocol against forging attack. EURASIP Journal on Image and Video Processing (2020)."}],"event":{"name":"IH&MMSec '22: ACM Workshop on Information Hiding and Multimedia Security","location":"Santa Barbara CA USA","acronym":"IH&MMSec '22","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 2022 ACM Workshop on Information Hiding and Multimedia Security"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3531536.3532950","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3531536.3532950","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T18:09:22Z","timestamp":1750183762000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3531536.3532950"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,23]]},"references-count":30,"alternative-id":["10.1145\/3531536.3532950","10.1145\/3531536"],"URL":"https:\/\/doi.org\/10.1145\/3531536.3532950","relation":{},"subject":[],"published":{"date-parts":[[2022,6,23]]},"assertion":[{"value":"2022-06-23","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}