{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,27]],"date-time":"2025-07-27T07:46:02Z","timestamp":1753602362326,"version":"3.37.3"},"reference-count":60,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,12,13]],"date-time":"2021-12-13T00:00:00Z","timestamp":1639353600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,12,13]],"date-time":"2021-12-13T00:00:00Z","timestamp":1639353600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,12,13]],"date-time":"2021-12-13T00:00:00Z","timestamp":1639353600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100007210","name":"RWTH Aachen University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100007210","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,12,13]]},"DOI":"10.1109\/pst52912.2021.9647755","type":"proceedings-article","created":{"date-parts":[[2021,12,21]],"date-time":"2021-12-21T21:08:01Z","timestamp":1640120881000},"page":"1-10","source":"Crossref","is-referenced-by-count":5,"title":["Towards Privacy-Preserving Classification-as-a-Service for DGA Detection"],"prefix":"10.1109","author":[{"given":"Arthur","family":"Drichel","sequence":"first","affiliation":[]},{"given":"Mehdi Akbari","family":"Gurabi","sequence":"additional","affiliation":[]},{"given":"Tim","family":"Amelung","sequence":"additional","affiliation":[]},{"given":"Ulrike","family":"Meyer","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/3372297.3417872"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/62212.62213"},{"key":"ref33","article-title":"Crypten: Secure multi-party computation meets machine learning","author":"knott","year":"2020","journal-title":"NeurIPS Workshop on Privacy Preserving Machine Learning"},{"key":"ref32","article-title":"Private machine learning in tensorflow using secure computation","author":"dahl","year":"2018","journal-title":"arXiv 1810 08130"},{"key":"ref31","article-title":"A generic framework for privacy preserving deep learning","author":"ryffel","year":"2018","journal-title":"arXiv 1811 04017"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1145\/3196494.3196522"},{"key":"ref37","article-title":"Delphi: A cryptographic inference service for neural networks","author":"mishra","year":"2020","journal-title":"USENIX Security Symposium"},{"key":"ref36","article-title":"Mp2ml: A mixed-protocol machine learning framework for private inference","author":"boemer","year":"2020","journal-title":"Availability Reliability and Security"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS.2019.00121"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.2478\/popets-2020-0077"},{"key":"ref60","article-title":"The nonlinearity coefficient-predicting overfitting in deep neural networks","author":"philipp","year":"2018","journal-title":"arXiv 1806 00179"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3134056"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/3310273.3323047"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/DAC.2018.8465894"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3023084"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.csbj.2014.11.005"},{"key":"ref20","article-title":"Privacy-preserving decision trees training and prediction","author":"akavia","year":"2020","journal-title":"European conference on machine learning and principles and practice of knowledge discovery in databases"},{"key":"ref22","article-title":"Sealion: A framework for neural network inference on encrypted data","author":"van elsloo","year":"2019","journal-title":"arXiv 1904 12840"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ISPACS.2018.8923293"},{"key":"ref24","article-title":"Cryptonets: Applying neural networks to encrypted data with high throughput and accuracy","volume":"48","author":"gilad-bachrach","year":"2016","journal-title":"International Conference on Machine Learning"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1155\/2020\/3910250"},{"key":"ref26","article-title":"She: A fast and accurate privacy-preserving deep neural network via leveled tfhe and logarithmic data representation","author":"lou","year":"2019","journal-title":"arXiv 1906 00148"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3045465"},{"key":"ref50","article-title":"A comprehensive measurement study of domain generating malware","author":"plohmann","year":"2016","journal-title":"USENIX Security Symposium"},{"journal-title":"World wide education roaming for research and education","year":"0","key":"ref51"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1016\/j.acha.2019.06.004"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1016\/j.acha.2015.12.005"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1016\/S0893-6080(05)80131-5"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW.2017.96"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-70694-8_15"},{"key":"ref54","article-title":"Pytorch: An imperative style, high-performance deep learning library","volume":"32","author":"paszke","year":"2019","journal-title":"Advances in neural information processing systems"},{"key":"ref53","article-title":"TensorFlow: Large-scale machine learning on heterogeneous systems","author":"abadi","year":"2015","journal-title":"software available from tensorflow org"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1145\/3407023.3409190"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/s11063-017-9666-7"},{"key":"ref11","article-title":"FANCI: Feature-based automated nxdomain classification and intelligence","author":"sch\u00fcppen","year":"2018","journal-title":"USENIX Security Symposium"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-45539-6_22"},{"key":"ref12","article-title":"Predicting domain generation algorithms with long short-term memory networks","author":"woodbridge","year":"2016","journal-title":"arXiv 1611 00791"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2018.8489147"},{"key":"ref14","article-title":"eXpose: A character-level convolutional neural network with embeddings for detecting malicious URLs, file paths and registry keys","author":"saxe","year":"2017","journal-title":"arXiv 1702 08568"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2927075"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/3297280.3297467"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-95729-6_16"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1515\/popets-2016-0043"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-49669-2_10"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3465481.3465749"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3407023.3407030"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/2584679"},{"key":"ref5","article-title":"From throw-away traffic to bots: Detecting the rise of DGA-based malware","author":"antonakakis","year":"2012","journal-title":"USENIX Security Symposium"},{"key":"ref8","article-title":"Winning with dns failures: Strategies for faster botnet detection","author":"yadav","year":"2011","journal-title":"Security and Privacy in Communication Systems"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/INM.2015.7140486"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-49445-6_6"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-08509-8_11"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-32009-5_38"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2015.23113"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.2478\/popets-2019-0035"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-46803-6_12"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-44987-6_18"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/SFCS.1986.25"},{"key":"ref44","article-title":"How to play any mental game","author":"micali","year":"1987","journal-title":"Symposium on Theory of Computing"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-32009-5_49"}],"event":{"name":"2021 18th International Conference on Privacy, Security and Trust (PST)","start":{"date-parts":[[2021,12,13]]},"location":"Auckland, New Zealand","end":{"date-parts":[[2021,12,15]]}},"container-title":["2021 18th International Conference on Privacy, Security and Trust (PST)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9647713\/9647738\/09647755.pdf?arnumber=9647755","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T16:59:50Z","timestamp":1652201990000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9647755\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,13]]},"references-count":60,"URL":"https:\/\/doi.org\/10.1109\/pst52912.2021.9647755","relation":{},"subject":[],"published":{"date-parts":[[2021,12,13]]}}}