{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T23:24:03Z","timestamp":1780356243291,"version":"3.54.1"},"publisher-location":"New York, NY, USA","reference-count":53,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,11,7]],"date-time":"2022-11-07T00:00:00Z","timestamp":1667779200000},"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":[[2022,11,11]]},"DOI":"10.1145\/3560830.3563724","type":"proceedings-article","created":{"date-parts":[[2022,11,2]],"date-time":"2022-11-02T22:32:41Z","timestamp":1667428361000},"page":"137-147","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Optimising Vulnerability Triage in DAST with Deep Learning"],"prefix":"10.1145","author":[{"given":"Stuart","family":"Millar","sequence":"first","affiliation":[{"name":"Rapid7 LLC, Boston, MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Denis","family":"Podgurskii","sequence":"additional","affiliation":[{"name":"Open Web Application Security Project, Belfast, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dan","family":"Kuykendall","sequence":"additional","affiliation":[{"name":"Rapid7 LLC, Boston, MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jes\u00fas","family":"Mart\u00ednez del Rinc\u00f3n","sequence":"additional","affiliation":[{"name":"Queen's University Belfast, Belfast, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paul","family":"Miller","sequence":"additional","affiliation":[{"name":"Queen's University Belfast, Belfast, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2022,11,7]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"last accessed","author":"Cybercrime Study Cost","year":"2022","unstructured":"2019 Cost of Cybercrime Study . [Online : last accessed June 2022 ]. Ponemon Institute LLC & Accenture . https:\/\/www.accenture.com\/_acnmedia\/PDF-96\/Accenture-2019-Cost-of-Cybercrime-Study-Final.pdf. 2019 Cost of Cybercrime Study. [Online: last accessed June 2022]. Ponemon Institute LLC & Accenture. https:\/\/www.accenture.com\/_acnmedia\/PDF-96\/Accenture-2019-Cost-of-Cybercrime-Study-Final.pdf."},{"key":"e_1_3_2_2_2_1","volume-title":"Cyberwarfare in the C-Suite. [Online: last accessed","year":"2022","unstructured":"2021 Report : Cyberwarfare in the C-Suite. [Online: last accessed June 2022 ]. Cybercrime Magazine & Intrusion, Inc. https:\/\/1c7fab3im83f5gqiow2qqs2k-wpengine.netdna-ssl.com\/wp-content\/uploads\/2021\/01\/Cyberwarfare-2021-Report.pdf. 2021 Report: Cyberwarfare in the C-Suite. [Online: last accessed June 2022]. Cybercrime Magazine & Intrusion, Inc. https:\/\/1c7fab3im83f5gqiow2qqs2k-wpengine.netdna-ssl.com\/wp-content\/uploads\/2021\/01\/Cyberwarfare-2021-Report.pdf."},{"key":"e_1_3_2_2_3_1","volume-title":"Artificial Neural Networks and Machine Learning -- ICANN 2019: Workshop and Special Sessions, , Igor V. Tetko, Vve ra Kru rkov\u00e1","author":"Abreu Jader","unstructured":"Jader Abreu , Luis Fred , David Mac\u00eado , and Cleber Zanchettin . 2019. Hierarchical Attentional Hybrid Neural Networks for Document Classification . In Artificial Neural Networks and Machine Learning -- ICANN 2019: Workshop and Special Sessions, , Igor V. Tetko, Vve ra Kru rkov\u00e1 , Pavel Karpov, and Fabian Theis (Eds.). Springer International Publishing , Cham , 396--402. Jader Abreu, Luis Fred, David Mac\u00eado, and Cleber Zanchettin. 2019. Hierarchical Attentional Hybrid Neural Networks for Document Classification. In Artificial Neural Networks and Machine Learning -- ICANN 2019: Workshop and Special Sessions, , Igor V. Tetko, Vve ra Kru rkov\u00e1, Pavel Karpov, and Fabian Theis (Eds.). Springer International Publishing, Cham, 396--402."},{"key":"e_1_3_2_2_4_1","volume-title":"International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=H1gKYo09tX","author":"Alon Uri","year":"2019","unstructured":"Uri Alon , Shaked Brody , Omer Levy , and Eran Yahav . 2019 . code2seq: Generating Sequences from Structured Representations of Code . In International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=H1gKYo09tX Uri Alon, Shaked Brody, Omer Levy, and Eran Yahav. 2019. code2seq: Generating Sequences from Structured Representations of Code. In International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=H1gKYo09tX"},{"key":"e_1_3_2_2_5_1","volume-title":"The Base-Rate Fallacy and Its Implications for the Difficulty of Intrusion Detection (CCS '99)","author":"Axelsson Stefan","unstructured":"Stefan Axelsson . 1999. The Base-Rate Fallacy and Its Implications for the Difficulty of Intrusion Detection (CCS '99) . Association for Computing Machinery , New York, NY, USA , 1--7. Stefan Axelsson. 1999. The Base-Rate Fallacy and Its Implications for the Difficulty of Intrusion Detection (CCS '99). Association for Computing Machinery, New York, NY, USA, 1--7."},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00051"},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/1541880.1541882"},{"key":"e_1_3_2_2_8_1","volume-title":"Towards the Detection of Inconsistencies in Public Security Vulnerability Reports. In 28th USENIX Security Symposium (USENIX Security 19)","author":"Dong Ying","year":"2019","unstructured":"Ying Dong , Wenbo Guo , Yueqi Chen , Xinyu Xing , Yuqing Zhang , and Gang Wang . 2019 . Towards the Detection of Inconsistencies in Public Security Vulnerability Reports. In 28th USENIX Security Symposium (USENIX Security 19) . USENIX Association, Santa Clara, CA, 869--885. https:\/\/www.usenix.org\/conference\/usenixsecurity19\/presentation\/dong Ying Dong, Wenbo Guo, Yueqi Chen, Xinyu Xing, Yuqing Zhang, and Gang Wang. 2019. Towards the Detection of Inconsistencies in Public Security Vulnerability Reports. In 28th USENIX Security Symposium (USENIX Security 19). USENIX Association, Santa Clara, CA, 869--885. https:\/\/www.usenix.org\/conference\/usenixsecurity19\/presentation\/dong"},{"key":"e_1_3_2_2_9_1","volume-title":"Jesus Martinez-del Rincon, and Dominic Siracusa","author":"Corin Roberto Doriguzzi","year":"2020","unstructured":"Roberto Doriguzzi Corin , Stuart Millar , Sandra Scott-Hayward , Jesus Martinez-del Rincon, and Dominic Siracusa . 2020 . Lucid : A Practical, Lightweight Deep Learning Solution for DDoS Attack Detection. IEEE Transactions on Network and Service Management , Vol. PP ( 02 2020), 1--1. Roberto Doriguzzi Corin, Stuart Millar, Sandra Scott-Hayward, Jesus Martinez-del Rincon, and Dominic Siracusa. 2020. Lucid: A Practical, Lightweight Deep Learning Solution for DDoS Attack Detection. IEEE Transactions on Network and Service Management , Vol. PP (02 2020), 1--1."},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3372297.3417869"},{"key":"e_1_3_2_2_11_1","volume-title":"last accessed","year":"2022","unstructured":"EUR-Lex. [Online : last accessed June 2022 ]. Consolidated text: Regulation (EU) 2016\/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95\/46\/EC (General Data Protection Regulation) (Text with EEA relevance). https:\/\/eur-lex.europa.eu\/legal-content\/EN\/TXT\/?qid=1528874672298&uri=CELEX:02016R0679--20160504. EUR-Lex. [Online: last accessed June 2022]. Consolidated text: Regulation (EU) 2016\/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95\/46\/EC (General Data Protection Regulation) (Text with EEA relevance). https:\/\/eur-lex.europa.eu\/legal-content\/EN\/TXT\/?qid=1528874672298&uri=CELEX:02016R0679--20160504."},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/COMPSAC.2007.43"},{"key":"e_1_3_2_2_13_1","volume-title":"Deep Learning","author":"Goodfellow Ian","unstructured":"Ian Goodfellow , Yoshua Bengio , and Aaron Courville . 2016a. Deep Learning , Chapter 12 Applications, 12.4.2 Neural Language Models. MIT Press . 451--452 pages. http:\/\/www.deeplearningbook.org. Ian Goodfellow, Yoshua Bengio, and Aaron Courville. 2016a. Deep Learning, Chapter 12 Applications, 12.4.2 Neural Language Models. MIT Press. 451--452 pages. http:\/\/www.deeplearningbook.org."},{"key":"e_1_3_2_2_14_1","volume-title":"Deep Learning","author":"Goodfellow Ian","unstructured":"Ian Goodfellow , Yoshua Bengio , and Aaron Courville . 2016b. Deep Learning , Chapter 9 Convolutional Neural Networks. MIT Press . 321--363 pages. http:\/\/www.deeplearningbook.org. Ian Goodfellow, Yoshua Bengio, and Aaron Courville. 2016b. Deep Learning, Chapter 9 Convolutional Neural Networks. MIT Press. 321--363 pages. http:\/\/www.deeplearningbook.org."},{"key":"e_1_3_2_2_15_1","volume-title":"vspace0mmDeep Learning","author":"Goodfellow Ian","unstructured":"Ian Goodfellow , Yoshua Bengio , and Aaron Courville . 2016c. vspace0mmDeep Learning , Chapter 10 Sequence Modeling: Recurrent and Recursive Nets, 10.2 Recurrent Neural Networks. MIT Press . 371--372 pages. http:\/\/www.deeplearningbook.org. Ian Goodfellow, Yoshua Bengio, and Aaron Courville. 2016c. vspace0mmDeep Learning, Chapter 10 Sequence Modeling: Recurrent and Recursive Nets, 10.2 Recurrent Neural Networks. MIT Press. 371--372 pages. http:\/\/www.deeplearningbook.org."},{"key":"e_1_3_2_2_16_1","volume-title":"DEEPVSA: Facilitating Value-set Analysis with Deep Learning for Postmortem Program Analysis. In 28th USENIX Security Symposium (USENIX Security 19)","author":"Guo Wenbo","year":"2019","unstructured":"Wenbo Guo , Dongliang Mu , Xinyu Xing , Min Du , and Dawn Song . 2019 . DEEPVSA: Facilitating Value-set Analysis with Deep Learning for Postmortem Program Analysis. In 28th USENIX Security Symposium (USENIX Security 19) . USENIX Association, Santa Clara, CA, 1787-- 1804. https:\/\/www.usenix.org\/conference\/usenixsecurity19\/presentation\/guo Wenbo Guo, Dongliang Mu, Xinyu Xing, Min Du, and Dawn Song. 2019. DEEPVSA: Facilitating Value-set Analysis with Deep Learning for Postmortem Program Analysis. In 28th USENIX Security Symposium (USENIX Security 19). USENIX Association, Santa Clara, CA, 1787--1804. https:\/\/www.usenix.org\/conference\/usenixsecurity19\/presentation\/guo"},{"key":"e_1_3_2_2_17_1","volume-title":"KDD '18","author":"Gupta Anshul","year":"2018","unstructured":"Anshul Gupta . 2018 . Intelligent code reviews using deep learning , KDD '18 , Deep Learning Day. Anshul Gupta. 2018. Intelligent code reviews using deep learning, KDD '18, Deep Learning Day."},{"key":"e_1_3_2_2_18_1","volume-title":"Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics","author":"Haj-Yahia Zied","unstructured":"Zied Haj-Yahia , Adrien Sieg , and L\u00e9a A. Deleris . 2019. Towards Unsupervised Text Classification Leveraging Experts and Word Embeddings . In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics , Florence, Italy, 371--379. https:\/\/www.aclweb.org\/anthology\/P19--1036 Zied Haj-Yahia, Adrien Sieg, and L\u00e9a A. Deleris. 2019. Towards Unsupervised Text Classification Leveraging Experts and Word Embeddings. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Florence, Italy, 371--379. https:\/\/www.aclweb.org\/anthology\/P19--1036"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/1082983.1083250"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3196494.3196511"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.5555\/3060832.3060845"},{"key":"e_1_3_2_2_22_1","volume-title":"last accessed","author":"Office Information Commissoner's","year":"2022","unstructured":"Information Commissoner's Office . [Online : last accessed June 2022 ]. International transfers after the UK exit from the EU Implementation Period . https:\/\/ico.org.uk\/for-organisations\/guide-to-data-protection\/guide-to-the-general-data-protection-regulation-gdpr\/international-transfers-after-uk-exit\/. Information Commissoner's Office. [Online: last accessed June 2022]. International transfers after the UK exit from the EU Implementation Period. https:\/\/ico.org.uk\/for-organisations\/guide-to-data-protection\/guide-to-the-general-data-protection-regulation-gdpr\/international-transfers-after-uk-exit\/."},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2019.10.033"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1181"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACSAC.2007.20"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2018.2854765"},{"key":"e_1_3_2_2_27_1","volume-title":"Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)","author":"Madasu Avinash","unstructured":"Avinash Madasu and Vijjini Anvesh Rao . 2019. Sequential Learning of Convolutional Features for Effective Text Classification . In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) . Association for Computational Linguistics , Hong Kong , China, 5658--5667. https:\/\/www.aclweb.org\/anthology\/D19--1567 Avinash Madasu and Vijjini Anvesh Rao. 2019. Sequential Learning of Convolutional Features for Effective Text Classification. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, 5658--5667. https:\/\/www.aclweb.org\/anthology\/D19--1567"},{"key":"e_1_3_2_2_28_1","volume-title":"1st International Conference on Learning Representations, ICLR","author":"Mikolov Tom\u00e1","year":"2013","unstructured":"Tom\u00e1 s Mikolov , Kai Chen , Greg Corrado , and Jeffrey Dean . 2013. Efficient Estimation of Word Representations in Vector Space . In 1st International Conference on Learning Representations, ICLR 2013 , Scottsdale, Arizona, USA , May 2--4, 2013, Workshop Track Proceedings, Yoshua Bengio and Yann LeCun (Eds .). Tom\u00e1 s Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013. Efficient Estimation of Word Representations in Vector Space. In 1st International Conference on Learning Representations, ICLR 2013, Scottsdale, Arizona, USA, May 2--4, 2013, Workshop Track Proceedings, Yoshua Bengio and Yann LeCun (Eds.)."},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jisa.2020.102718"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2020.3004266"},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"crossref","unstructured":"Jessica Moore Ben Gelman and David Slater. 2019. A Convolutional Neural Network for Language-Agnostic Source Code Summarization. In ENASE.  Jessica Moore Ben Gelman and David Slater. 2019. A Convolutional Neural Network for Language-Agnostic Source Code Summarization. In ENASE.","DOI":"10.5220\/0007678100150026"},{"key":"e_1_3_2_2_32_1","volume-title":"Recent Advances in Intrusion Detection","author":"Morin Benjamin","unstructured":"Benjamin Morin , Ludovic M\u00e9 , Herv\u00e9 Debar , and Mireille Ducass\u00e9 . 2002. M2D2: A Formal Data Model for IDS Alert Correlation . In Recent Advances in Intrusion Detection , Andreas Wespi, Giovanni Vigna, and Luca Deri (Eds.). Springer Berlin Heidelberg , Berlin, Heidelberg , 115--137. Benjamin Morin, Ludovic M\u00e9, Herv\u00e9 Debar, and Mireille Ducass\u00e9. 2002. M2D2: A Formal Data Model for IDS Alert Correlation. In Recent Advances in Intrusion Detection, Andreas Wespi, Giovanni Vigna, and Luca Deri (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 115--137."},{"key":"e_1_3_2_2_33_1","volume-title":"last accessed","author":"Open Web Application Security OWASP","year":"2022","unstructured":"OWASP Open Web Application Security Project. [Online : last accessed June 2022 ]. Top Ten Web Application Security Risks . https:\/\/owasp.org\/www-project-top-ten\/. OWASP Open Web Application Security Project. [Online: last accessed June 2022]. Top Ten Web Application Security Risks. https:\/\/owasp.org\/www-project-top-ten\/."},{"key":"e_1_3_2_2_34_1","volume-title":"Detecting web attacks with end-to-end deep learning. J Internet Serv Appl","author":"Pan Yao","year":"2019","unstructured":"Yao Pan , Fangzhou Sun , Zhongwei Teng , Jules White , Douglas C. Schmidt , Jacob Staples , and Lee Krause . 2019. Detecting web attacks with end-to-end deep learning. J Internet Serv Appl , Vol. 10 ( 2019 ). Yao Pan, Fangzhou Sun, Zhongwei Teng, Jules White, Douglas C. Schmidt, Jacob Staples, and Lee Krause. 2019. Detecting web attacks with end-to-end deep learning. J Internet Serv Appl , Vol. 10 (2019)."},{"key":"e_1_3_2_2_35_1","volume-title":"Manning","author":"Pennington Jeffrey","year":"2014","unstructured":"Jeffrey Pennington , Richard Socher , and Christopher D . Manning . 2014 . GloVe: Global Vectors for Word Representation. In Empirical Methods in Natural Language Processing (EMNLP) . 1532--1543. http:\/\/www.aclweb.org\/anthology\/D14--1162 Jeffrey Pennington, Richard Socher, and Christopher D. Manning. 2014. GloVe: Global Vectors for Word Representation. In Empirical Methods in Natural Language Processing (EMNLP). 1532--1543. http:\/\/www.aclweb.org\/anthology\/D14--1162"},{"key":"e_1_3_2_2_36_1","volume-title":"Recent Advances in Intrusion Detection","author":"Pietraszek Tadeusz","unstructured":"Tadeusz Pietraszek . 2004. Using Adaptive Alert Classification to Reduce False Positives in Intrusion Detection . In Recent Advances in Intrusion Detection , Erland Jonsson, Alfonso Valdes, and Magnus Almgren (Eds.). Springer Berlin Heidelberg , Berlin, Heidelberg , 102--124. Tadeusz Pietraszek. 2004. Using Adaptive Alert Classification to Reduce False Positives in Intrusion Detection. In Recent Advances in Intrusion Detection, Erland Jonsson, Alfonso Valdes, and Magnus Almgren (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 102--124."},{"key":"e_1_3_2_2_37_1","volume-title":"last accessed","year":"2022","unstructured":"Rapid7. [Online : last accessed June 2022 ]. Under The Hoodie 2020. https:\/\/www.rapid7.com\/research\/report\/under-the-hoodie-2020\/. Rapid7. [Online: last accessed June 2022]. Under The Hoodie 2020. https:\/\/www.rapid7.com\/research\/report\/under-the-hoodie-2020\/."},{"key":"e_1_3_2_2_38_1","volume-title":"Machine Learning for Cyber Security","author":"Rong Wei","unstructured":"Wei Rong , Bowen Zhang , and Xixiang Lv. 2019. Malicious Web Request Detection Using Character-Level CNN . In Machine Learning for Cyber Security , Xiaofeng Chen, Xinyi Huang, and Jun Zhang (Eds.). Springer International Publishing , Cham , 6--16. Wei Rong, Bowen Zhang, and Xixiang Lv. 2019. Malicious Web Request Detection Using Character-Level CNN. In Machine Learning for Cyber Security, Xiaofeng Chen, Xinyi Huang, and Jun Zhang (Eds.). Springer International Publishing, Cham, 6--16."},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/3430360"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1109\/TDSC.2014.2373377"},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/948109.948145"},{"key":"e_1_3_2_2_42_1","doi-asserted-by":"publisher","DOI":"10.1109\/CYBConf.2017.7985745"},{"key":"e_1_3_2_2_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSR.2019.00014"},{"key":"e_1_3_2_2_44_1","volume-title":"last accessed","year":"2022","unstructured":"Verizon. [Online : last accessed June 2022 ]. 2020 Data Breach Investigations Report : Official . https:\/\/enterprise.verizon.com\/resources\/reports\/dbir\/. Verizon. [Online: last accessed June 2022]. 2020 Data Breach Investigations Report: Official. https:\/\/enterprise.verizon.com\/resources\/reports\/dbir\/."},{"key":"e_1_3_2_2_45_1","volume-title":"Mach. Learn. Res.","volume":"11","author":"Vincent Pascal","year":"2010","unstructured":"Pascal Vincent , Hugo Larochelle , Isabelle Lajoie , Yoshua Bengio , and Pierre-Antoine Manzagol . 2010 . Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion. J . Mach. Learn. Res. , Vol. 11 (Dec. 2010), 3371--3408. Pascal Vincent, Hugo Larochelle, Isabelle Lajoie, Yoshua Bengio, and Pierre-Antoine Manzagol. 2010. Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion. J. Mach. Learn. Res. , Vol. 11 (Dec. 2010), 3371--3408."},{"key":"e_1_3_2_2_46_1","volume-title":"Deep Learning","author":"Goodfellow Ian","unstructured":"vspace0mm Ian Goodfellow , Yoshua Bengio , and Aaron Courville . 2016. Deep Learning , Chapter 7 Regularization for Deep Learning, 7.8 Early Stopping. MIT Press . 239--240 pages. http:\/\/www.deeplearningbook.org. vspace0mmIan Goodfellow, Yoshua Bengio, and Aaron Courville. 2016. Deep Learning, Chapter 7 Regularization for Deep Learning, 7.8 Early Stopping. MIT Press. 239--240 pages. http:\/\/www.deeplearningbook.org."},{"key":"e_1_3_2_2_47_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2020.3044773"},{"key":"e_1_3_2_2_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/1368088.1368112"},{"key":"e_1_3_2_2_49_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2900734"},{"key":"e_1_3_2_2_50_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/K15-1021"},{"key":"e_1_3_2_2_51_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2020.3013204"},{"key":"e_1_3_2_2_52_1","volume-title":"SSOScan: Automated Testing of Web Applications for Single Sign-On Vulnerabilities. In 23rd USENIX Security Symposium (USENIX Security 14)","author":"Zhou Yuchen","year":"2014","unstructured":"Yuchen Zhou and David Evans . 2014 . SSOScan: Automated Testing of Web Applications for Single Sign-On Vulnerabilities. In 23rd USENIX Security Symposium (USENIX Security 14) . USENIX Association, San Diego, CA, 495--510. Yuchen Zhou and David Evans. 2014. SSOScan: Automated Testing of Web Applications for Single Sign-On Vulnerabilities. In 23rd USENIX Security Symposium (USENIX Security 14). USENIX Association, San Diego, CA, 495--510."},{"key":"e_1_3_2_2_53_1","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3134089"}],"event":{"name":"CCS '22: 2022 ACM SIGSAC Conference on Computer and Communications Security","location":"Los Angeles CA USA","acronym":"CCS '22","sponsor":["SIGSAC ACM Special Interest Group on Security, Audit, and Control"]},"container-title":["Proceedings of the 15th ACM Workshop on Artificial Intelligence and Security"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3560830.3563724","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3560830.3563724","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:00:34Z","timestamp":1750186834000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3560830.3563724"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11,7]]},"references-count":53,"alternative-id":["10.1145\/3560830.3563724","10.1145\/3560830"],"URL":"https:\/\/doi.org\/10.1145\/3560830.3563724","relation":{},"subject":[],"published":{"date-parts":[[2022,11,7]]},"assertion":[{"value":"2022-11-07","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}