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Springer, 3\u201339. https:\/\/doi.org\/10.1007\/978-3-319-70503-3_1 10.1007\/978-3-319-70503-3_1 Carmit Hazay, Yuval Ishai, and Muthuramakrishnan Venkitasubramaniam. 2017. Actively Secure Garbled Circuits with Constant Communication Overhead in the Plain Model. In Theory of Cryptography - 15th International Conference, TCC 2017, Baltimore, MD, USA, November 12-15, 2017, Proceedings, Part II(Lecture Notes in Computer Science, Vol.\u00a010678), Yael Kalai and Leonid Reyzin (Eds.). Springer, 3\u201339. https:\/\/doi.org\/10.1007\/978-3-319-70503-3_1"},{"unstructured":"Andrew Hilts Christopher Parsons and Jeffrey Knockel. 2016. Every step you fake: a comparative analysis of fitness tracker privacy and security.  Andrew Hilts Christopher Parsons and Jeffrey Knockel. 2016. Every step you fake: a comparative analysis of fitness tracker privacy and security.","key":"e_1_3_2_1_38_1"},{"key":"e_1_3_2_1_39_1","volume-title":"Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, CCS 2017","author":"Hitaj Briland","year":"2017","unstructured":"Briland Hitaj , Giuseppe Ateniese , and Fernando P\u00e9rez-Cruz . 2017 . Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning . In Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, CCS 2017 , Dallas, TX, USA, October 30 - November 03, 2017, Bhavani\u00a0M. Thuraisingham, David Evans, Tal Malkin, and Dongyan Xu (Eds.). ACM, 603\u2013618. https:\/\/doi.org\/10.1145\/3133956.3134012 10.1145\/3133956.3134012 Briland Hitaj, Giuseppe Ateniese, and Fernando P\u00e9rez-Cruz. 2017. Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning. In Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, CCS 2017, Dallas, TX, USA, October 30 - November 03, 2017, Bhavani\u00a0M. Thuraisingham, David Evans, Tal Malkin, and Dongyan Xu (Eds.). ACM, 603\u2013618. https:\/\/doi.org\/10.1145\/3133956.3134012"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_40_1","DOI":"10.1145\/1250790.1250794"},{"key":"e_1_3_2_1_41_1","volume-title":"28th Annual International Cryptology Conference, Santa Barbara, CA, USA, August 17-21, 2008. Proceedings(Lecture Notes in Computer Science, Vol.\u00a05157)","author":"Ishai Yuval","year":"2008","unstructured":"Yuval Ishai , Manoj Prabhakaran , and Amit Sahai . 2008 . Founding Cryptography on Oblivious Transfer - Efficiently. In Advances in Cryptology - CRYPTO 2008 , 28th Annual International Cryptology Conference, Santa Barbara, CA, USA, August 17-21, 2008. Proceedings(Lecture Notes in Computer Science, Vol.\u00a05157) , David\u00a0A. Wagner (Ed.). Springer, 572\u2013591. https:\/\/doi.org\/10.1007\/978-3-540-85174-5_32 10.1007\/978-3-540-85174-5_32 Yuval Ishai, Manoj Prabhakaran, and Amit Sahai. 2008. Founding Cryptography on Oblivious Transfer - Efficiently. In Advances in Cryptology - CRYPTO 2008, 28th Annual International Cryptology Conference, Santa Barbara, CA, USA, August 17-21, 2008. Proceedings(Lecture Notes in Computer Science, Vol.\u00a05157), David\u00a0A. Wagner (Ed.). Springer, 572\u2013591. https:\/\/doi.org\/10.1007\/978-3-540-85174-5_32"},{"unstructured":"Tobias Jeske. 2013. Floating Car Data from Smartphones : What Google and Waze Know About You and How Hackers Can Control Traffic.  Tobias Jeske. 2013. Floating Car Data from Smartphones : What Google and Waze Know About You and How Hackers Can Control Traffic.","key":"e_1_3_2_1_42_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_43_1","DOI":"10.1109\/TIFS.2021.3108434"},{"unstructured":"Jing Ma Si-Ahmed Naas Stephan Sigg and Xixiang Lyu. [n. d.]. Privacy-preserving federated learning based on multi-key homomorphic encryption. International Journal of Intelligent Systems n\/a n\/a ([n. d.]). https:\/\/doi.org\/10.1002\/int.22818 arXiv:https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/int.22818    10.1002\/int.22818\nJing Ma Si-Ahmed Naas Stephan Sigg and Xixiang Lyu. [n. d.]. Privacy-preserving federated learning based on multi-key homomorphic encryption. International Journal of Intelligent Systems n\/a n\/a ([n. d.]). https:\/\/doi.org\/10.1002\/int.22818 arXiv:https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/int.22818","key":"e_1_3_2_1_44_1"},{"key":"e_1_3_2_1_45_1","volume-title":"Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, AISTATS 2017","author":"McMahan Brendan","year":"2017","unstructured":"Brendan McMahan , Eider Moore , Daniel Ramage , Seth Hampson , and Blaise\u00a0Ag\u00fcera y Arcas . 2017 . 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In Proceedings of the 35th International Conference on Machine Learning, ICML 2018, Stockholmsm\u00e4ssan, Stockholm, Sweden, July 10-15, 2018(Proceedings of Machine Learning Research, Vol.\u00a080), Jennifer\u00a0G. Dy and Andreas Krause (Eds.). PMLR, 3518\u20133527. http:\/\/proceedings.mlr.press\/v80\/mhamdi18a.html"},{"key":"e_1_3_2_1_49_1","volume-title":"FLGUARD: Secure and Private Federated Learning. CoRR abs\/2101.02281","author":"Nguyen Thien\u00a0Duc","year":"2021","unstructured":"Thien\u00a0Duc Nguyen , Phillip Rieger , Hossein Yalame , Helen M\u00f6llering , Hossein Fereidooni , Samuel Marchal , Markus Miettinen , Azalia Mirhoseini , Ahmad-Reza Sadeghi , Thomas Schneider , and Shaza Zeitouni . 2021 . FLGUARD: Secure and Private Federated Learning. 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CoRR abs\/1911.02254 ( 2019 ). arxiv:1911.02254http:\/\/arxiv.org\/abs\/1911.02254 Chaoyue Niu, Fan Wu, Shaojie Tang, Lifeng Hua, Rongfei Jia, Chengfei Lv, Zhihua Wu, and Guihai Chen. 2019. Secure Federated Submodel Learning. CoRR abs\/1911.02254 (2019). arxiv:1911.02254http:\/\/arxiv.org\/abs\/1911.02254"},{"key":"e_1_3_2_1_52_1","volume-title":"Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses for Federated Learning. In 28th Annual Network and Distributed System Security Symposium, NDSS 2021","author":"Shejwalkar Virat","year":"2021","unstructured":"Virat Shejwalkar and Amir Houmansadr . 2021 . Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses for Federated Learning. In 28th Annual Network and Distributed System Security Symposium, NDSS 2021 , virtually, February 21-25, 2021. The Internet Society. https:\/\/www.ndss-symposium.org\/ndss-paper\/manipulating-the-byzantine-optimizing-model-poisoning-attacks-and-defenses-for-federated-learning\/ Virat Shejwalkar and Amir Houmansadr. 2021. Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses for Federated Learning. In 28th Annual Network and Distributed System Security Symposium, NDSS 2021, virtually, February 21-25, 2021. The Internet Society. https:\/\/www.ndss-symposium.org\/ndss-paper\/manipulating-the-byzantine-optimizing-model-poisoning-attacks-and-defenses-for-federated-learning\/"},{"key":"e_1_3_2_1_53_1","volume-title":"Membership Inference Attacks Against Machine Learning Models. In 2017 IEEE Symposium on Security and Privacy, SP 2017","author":"Shokri Reza","year":"2017","unstructured":"Reza Shokri , Marco Stronati , Congzheng Song , and Vitaly Shmatikov . 2017 . Membership Inference Attacks Against Machine Learning Models. 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