{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,6]],"date-time":"2024-10-06T01:06:48Z","timestamp":1728176808480},"publisher-location":"Cham","reference-count":39,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030648398"},{"type":"electronic","value":"9783030648404"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-64840-4_2","type":"book-chapter","created":{"date-parts":[[2020,12,4]],"date-time":"2020-12-04T10:06:04Z","timestamp":1607076364000},"page":"31-59","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Maliciously Secure Matrix Multiplication with Applications to Private Deep Learning"],"prefix":"10.1007","author":[{"given":"Hao","family":"Chen","sequence":"first","affiliation":[]},{"given":"Miran","family":"Kim","sequence":"additional","affiliation":[]},{"given":"Ilya","family":"Razenshteyn","sequence":"additional","affiliation":[]},{"given":"Dragos","family":"Rotaru","sequence":"additional","affiliation":[]},{"given":"Yongsoo","family":"Song","sequence":"additional","affiliation":[]},{"given":"Sameer","family":"Wagh","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,12,5]]},"reference":[{"key":"2_CR1","unstructured":"Aly, A., et al.: SCALE-MAMBA v1.2: Documentation (2018)"},{"key":"2_CR2","doi-asserted-by":"crossref","unstructured":"Araki, T., et al.: Optimized honest-majority MPC for malicious adversaries - breaking the 1 billion-gate per second barrier. In: 2017 IEEE Symposium on Security and Privacy, San Jose, CA, USA, 22\u201326 May 2017, pp. 843\u2013862. IEEE Computer Society Press (2017)","DOI":"10.1109\/SP.2017.15"},{"key":"2_CR3","unstructured":"Babenko, A., Lempitsky, V.: Efficient indexing of billion-scale datasets of deep descriptors. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2055\u20132063 (2016)"},{"key":"2_CR4","unstructured":"Barak, A., Escudero, D., Dalskov, A., Keller, M.: Secure evaluation of quantized neural networks. Cryptology ePrint Archive, Report 2019\/131 (2019). https:\/\/eprint.iacr.org\/2019\/131"},{"key":"2_CR5","unstructured":"Baum, C., Cozzo, D., Smart, N.P.: Using topgear in overdrive: A more efficient zkpok for spdz. Cryptology ePrint Archive, Report 2019\/035 (2019). https:\/\/eprint.iacr.org\/2019\/035"},{"key":"2_CR6","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1007\/978-3-642-20465-4_11","volume-title":"Advances in Cryptology \u2013 EUROCRYPT 2011","author":"R Bendlin","year":"2011","unstructured":"Bendlin, R., Damg\u00e5rd, I., Orlandi, C., Zakarias, S.: Semi-homomorphic encryption and multiparty computation. In: Paterson, K.G. (ed.) EUROCRYPT 2011. LNCS, vol. 6632, pp. 169\u2013188. Springer, Heidelberg (2011). https:\/\/doi.org\/10.1007\/978-3-642-20465-4_11"},{"key":"2_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"551","DOI":"10.1007\/978-3-662-45611-8_29","volume-title":"Advances in Cryptology \u2013 ASIACRYPT 2014","author":"F Benhamouda","year":"2014","unstructured":"Benhamouda, F., Camenisch, J., Krenn, S., Lyubashevsky, V., Neven, G.: Better zero-knowledge proofs for lattice encryption and their application to group signatures. In: Sarkar, P., Iwata, T. (eds.) ASIACRYPT 2014. LNCS, vol. 8873, pp. 551\u2013572. Springer, Heidelberg (2014). https:\/\/doi.org\/10.1007\/978-3-662-45611-8_29"},{"key":"2_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"868","DOI":"10.1007\/978-3-642-32009-5_50","volume-title":"Advances in Cryptology \u2013 CRYPTO 2012","author":"Z Brakerski","year":"2012","unstructured":"Brakerski, Z.: Fully homomorphic encryption without modulus switching from classical GapSVP. In: Safavi-Naini, R., Canetti, R. (eds.) CRYPTO 2012. LNCS, vol. 7417, pp. 868\u2013886. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-32009-5_50"},{"issue":"3","key":"2_CR9","first-page":"13","volume":"6","author":"Z Brakerski","year":"2014","unstructured":"Brakerski, Z., Gentry, C., Vaikuntanathan, V.: (Leveled) fully homomorphic encryption without bootstrapping. ACM Trans. Comput. Theory (TOCT) 6(3), 13 (2014)","journal-title":"ACM Trans. Comput. Theory (TOCT)"},{"key":"2_CR10","doi-asserted-by":"crossref","unstructured":"Canetti, R.: Universally composable security: a new paradigm for cryptographic protocols. In: Proceedings of the 42Nd IEEE Symposium on Foundations of Computer Science, FOCS 2001, pp. 136\u2013145 (2001)","DOI":"10.1109\/SFCS.2001.959888"},{"issue":"1","key":"2_CR11","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1007\/s001459910006","volume":"13","author":"R Canetti","year":"2000","unstructured":"Canetti, R.: Security and composition of multiparty cryptographic protocols. J. Cryptol. 13(1), 143\u2013202 (2000)","journal-title":"J. Cryptol."},{"key":"2_CR12","unstructured":"Chase, M., et al.: Security of homomorphic encryption. HomomorphicEncryption.org, Redmond WA, USA, Technical report (2017)"},{"key":"2_CR13","unstructured":"Chen, H., Chillotti, I., Dong, Y., Poburinnaya, O., Razenshteyn, I., Sanns, M.S.R.: Scaling up secure approximate k-nearest neighbors search. arXiv preprint arXiv:1904.02033 (2019)"},{"key":"2_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"409","DOI":"10.1007\/978-3-319-70694-8_15","volume-title":"Advances in Cryptology \u2013 ASIACRYPT 2017","author":"JH Cheon","year":"2017","unstructured":"Cheon, J.H., Kim, A., Kim, M., Song, Y.: Homomorphic encryption for arithmetic of approximate numbers. In: Takagi, T., Peyrin, T. (eds.) ASIACRYPT 2017. LNCS, vol. 10624, pp. 409\u2013437. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-70694-8_15"},{"key":"2_CR15","doi-asserted-by":"crossref","unstructured":"Cock, M.D., Dowsley, R., Nascimento, A.C., Newman, S.C.: Fast, privacy preserving linear regression over distributed datasets based on pre-distributed data. In: Proceedings of the 8th ACM Workshop on Artificial Intelligence and Security, pp. 3\u201314 (2015)","DOI":"10.1145\/2808769.2808774"},{"key":"2_CR16","doi-asserted-by":"crossref","unstructured":"Damg\u00e5rd, I., Escudero, D., Frederiksen, T., Keller, M., Scholl, P., Volgushev, N.: New primitives for actively-secure MPC over rings with applications to private machine learning. In: 2019 IEEE Symposium on Security and Privacy (SP), pp. 1102\u20131120 (2019)","DOI":"10.1109\/SP.2019.00078"},{"key":"2_CR17","unstructured":"Damg\u00e5rd, I.: On\n\n \n \n-protocols. University of Aarhus, Department for Computer Science, Lecture Notes (2002)"},{"key":"2_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-3-642-40203-6_1","volume-title":"Computer Security \u2013 ESORICS 2013","author":"I Damg\u00e5rd","year":"2013","unstructured":"Damg\u00e5rd, I., Keller, M., Larraia, E., Pastro, V., Scholl, P., Smart, N.P.: Practical covertly secure MPC for dishonest majority\u2013or: breaking the SPDZ limits. In: Crampton, J., Jajodia, S., Mayes, K. (eds.) ESORICS 2013. LNCS, vol. 8134, pp. 1\u201318. Springer, Heidelberg (2013). https:\/\/doi.org\/10.1007\/978-3-642-40203-6_1"},{"key":"2_CR19","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"643","DOI":"10.1007\/978-3-642-32009-5_38","volume-title":"Advances in Cryptology \u2013 CRYPTO 2012","author":"I Damg\u00e5rd","year":"2012","unstructured":"Damg\u00e5rd, I., Pastro, V., Smart, N., Zakarias, S.: Multiparty computation from somewhat homomorphic encryption. In: Safavi-Naini, R., Canetti, R. (eds.) CRYPTO 2012. LNCS, vol. 7417, pp. 643\u2013662. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-32009-5_38"},{"key":"2_CR20","unstructured":"Data61. MP-SPDZ (2019). https:\/\/github.com\/data61\/MP-SPDZ"},{"key":"2_CR21","first-page":"144","volume":"2012","author":"J Fan","year":"2012","unstructured":"Fan, J., Vercauteren, F.: Somewhat practical fully homomorphic encryption. IACR Cryptol. ePrint Arch. 2012, 144 (2012)","journal-title":"IACR Cryptol. ePrint Arch."},{"key":"2_CR22","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"554","DOI":"10.1007\/978-3-662-44371-2_31","volume-title":"Advances in Cryptology \u2013 CRYPTO 2014","author":"S Halevi","year":"2014","unstructured":"Halevi, S., Shoup, V.: Algorithms in HElib. In: Garay, J.A., Gennaro, R. (eds.) CRYPTO 2014. LNCS, vol. 8616, pp. 554\u2013571. Springer, Heidelberg (2014). https:\/\/doi.org\/10.1007\/978-3-662-44371-2_31"},{"key":"2_CR23","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1007\/978-3-319-96884-1_4","volume-title":"Advances in Cryptology \u2013 CRYPTO 2018","author":"S Halevi","year":"2018","unstructured":"Halevi, S., Shoup, V.: Faster homomorphic linear transformations in HElib. In: Shacham, H., Boldyreva, A. (eds.) CRYPTO 2018. LNCS, vol. 10991, pp. 93\u2013120. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-96884-1_4"},{"key":"2_CR24","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"2_CR25","doi-asserted-by":"crossref","unstructured":"Jiang, X., Kim, M., Lauter, K., Song, Y.: Secure outsourced matrix computation and application to neural networks. In: ACM Conference on Computer and Communications Security (CCS), pp. 1209\u20131222 (2018)","DOI":"10.1145\/3243734.3243837"},{"key":"2_CR26","doi-asserted-by":"crossref","unstructured":"Keller, M., Orsini, E., Scholl, P.: MASCOT: faster malicious arithmetic secure computation with oblivious transfer. In: Weippl, E.R., Katzenbeisser, S., Kruegel, C., Myers, A.C., Halevi, S. (eds.) ACM CCS 2016: 23rd Conference on Computer and Communications Security, Vienna, Austria, 24\u201328 October 2016, pp. 830\u2013842. ACM Press (2016)","DOI":"10.1145\/2976749.2978357"},{"key":"2_CR27","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"158","DOI":"10.1007\/978-3-319-78372-7_6","volume-title":"Advances in Cryptology \u2013 EUROCRYPT 2018","author":"M Keller","year":"2018","unstructured":"Keller, M., Pastro, V., Rotaru, D.: Overdrive: making SPDZ great again. In: Nielsen, J.B., Rijmen, V. (eds.) EUROCRYPT 2018. LNCS, vol. 10822, pp. 158\u2013189. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-78372-7_6"},{"key":"2_CR28","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: ImageNet classification with deep convolutional neural networks. In: Advances in Neural Information Processing Systems, pp. 1097\u20131105 (2012)"},{"key":"2_CR29","doi-asserted-by":"crossref","unstructured":"Lavin, A., Gray, S.: Fast algorithms for convolutional neural networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4013\u20134021 (2016)","DOI":"10.1109\/CVPR.2016.435"},{"issue":"1","key":"2_CR30","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1109\/72.554195","volume":"8","author":"S Lawrence","year":"1997","unstructured":"Lawrence, S., Giles, C.L., Tsoi, A.C., Back, A.D.: Face recognition: a convolutional neural-network approach. IEEE Trans. Neural Netw. 8(1), 98\u2013113 (1997)","journal-title":"IEEE Trans. Neural Netw."},{"key":"2_CR31","doi-asserted-by":"crossref","unstructured":"Liu, J., Juuti, M., Lu, Y., Asokan, N.: Oblivious neural network predictions via MiniONN transformations. In: Bhavani, M., Thuraisingham, D.E., Tal, M., Xu, D. (eds.) ACM CCS 2017: 24th Conference on Computer and Communications Security, Dallas, TX, USA, 31 October\u20132 November 2017, pp. 619\u2013631. ACM Press (2017)","DOI":"10.1145\/3133956.3134056"},{"key":"2_CR32","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"473","DOI":"10.1007\/978-3-030-12612-4_24","volume-title":"Topics in Cryptology \u2013 CT-RSA 2019","author":"E Makri","year":"2019","unstructured":"Makri, E., Rotaru, D., Smart, N.P., Vercauteren, F.: EPIC: efficient private image classification (or: learning from the masters). In: Matsui, M. (ed.) CT-RSA 2019. LNCS, vol. 11405, pp. 473\u2013492. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-12612-4_24"},{"key":"2_CR33","unstructured":"Mohassel, P., Rindal, P.: ABY$$^3$$: a mixed protocol framework for machine learning. In: Lie, D., Mannan, M., Backes, M., Wang, X.F. (eds.) ACM CCS 2018: 25th Conference on Computer and Communications Security, Toronto, ON, Canada, 15\u201319 October 2018, pp. 35\u201352. ACM Press (2018)"},{"key":"2_CR34","doi-asserted-by":"crossref","unstructured":"Mohassel, P., Zhang, Y.: SecureML: a system for scalable privacy-preserving machine learning. In: 2017 IEEE Symposium on Security and Privacy, San Jose, CA, USA, 22\u201326 May 2017, pp. 19\u201338. IEEE Computer Society Press (2017)","DOI":"10.1109\/SP.2017.12"},{"key":"2_CR35","doi-asserted-by":"crossref","unstructured":"Riazi, M.S., Weinert, C., Tkachenko, O., Songhori, E.M., Schneider, T., Koushanfar, F.: Chameleon: a hybrid secure computation framework for machine learning applications. In: Kim, J., Ahn, G.J., Kim, S., Kim, Y., L\u00f3pez, J., Kim, T. (eds.) ASIACCS 18: 13th ACM Symposium on Information, Computer and Communications Security, Incheon, Republic of Korea, 2\u20136 April 2018, pp. 707\u2013721. ACM Press (2018)","DOI":"10.1145\/3196494.3196522"},{"key":"2_CR36","unstructured":"Microsoft SEAL (release 3.3), Microsoft Research, Redmond, WA (2019).https:\/\/github.com\/Microsoft\/SEAL"},{"key":"2_CR37","doi-asserted-by":"crossref","unstructured":"Wagh, S., Gupta, D., Chandran, N.: SecureNN: 3-party secure computation for neural network training. In: Privacy Enhancing Technologies Symposium (PETS) (2019)","DOI":"10.2478\/popets-2019-0035"},{"key":"2_CR38","doi-asserted-by":"crossref","unstructured":"Zheng, W., Popa, R.A., Gonzalez, J.E., Stoica, I.: Helen: maliciously secure coopetitive learning for linear models. arXiv preprint arXiv:1907.07212 (2019)","DOI":"10.1109\/SP.2019.00045"},{"key":"2_CR39","first-page":"663","volume":"2018","author":"PK Mishra","year":"2018","unstructured":"Mishra, P.K., Rathee, D., Duong, D.H., Yasuda, M.: Fast secure matrix multiplications over ring-based homomorphic encryption. IACR Cryptol. ePrint Arch. 2018, 663 (2018)","journal-title":"IACR Cryptol. ePrint Arch."}],"container-title":["Lecture Notes in Computer Science","Advances in Cryptology \u2013 ASIACRYPT 2020"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-64840-4_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T15:06:12Z","timestamp":1710255972000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-64840-4_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030648398","9783030648404"],"references-count":39,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-64840-4_2","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"5 December 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ASIACRYPT","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on the Theory and Application of Cryptology and Information Security","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Daejeon","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Korea (Republic of)","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 December 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 December 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"asiacrypt2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/asiacrypt.iacr.org\/2020\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"websubrev","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"316","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"85","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"27% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"19","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"The conference will take place virtually due to the COVID-19 pandemic.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}