{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T16:25:44Z","timestamp":1783095944332,"version":"3.54.6"},"publisher-location":"Singapore","reference-count":26,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819706686","type":"print"},{"value":"9789819706693","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-981-97-0669-3_8","type":"book-chapter","created":{"date-parts":[[2024,2,28]],"date-time":"2024-02-28T21:20:16Z","timestamp":1709155216000},"page":"83-92","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Untargeted Code Authorship Evasion with\u00a0Seq2Seq Transformation"],"prefix":"10.1007","author":[{"given":"Soohyeon","family":"Choi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rhongho","family":"Jang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"DaeHun","family":"Nyang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Mohaisen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,2,29]]},"reference":[{"key":"8_CR1","unstructured":"Abuhamad, M., AbuHmed, T., Mohaisen, A., Nyang, D.: Tree-sitter-CPP (2021). https:\/\/github.com\/tree-sitter\/tree-sitter-cpp"},{"key":"8_CR2","unstructured":"Abuhamad, M., AbuHmed, T., Mohaisen, A., Nyang, D.: Google Code Jam (2023). https:\/\/codingcompetitions.withgoogle.com\/codejam\/archive"},{"key":"8_CR3","doi-asserted-by":"publisher","unstructured":"Abuhamad, M., AbuHmed, T., Mohaisen, A., Nyang, D.: Large-scale and language-oblivious code authorship identification. In: Proceedings of the ACM SIGSAC Conference on Computer and Communications Security, CCS, pp. 101\u2013114 (2018). https:\/\/doi.org\/10.1145\/3243734.3243738","DOI":"10.1145\/3243734.3243738"},{"issue":"3","key":"8_CR4","doi-asserted-by":"publisher","first-page":"25","DOI":"10.2478\/popets-2020-0044","volume":"2020","author":"M Abuhamad","year":"2020","unstructured":"Abuhamad, M., AbuHmed, T., Nyang, D., Mohaisen, D.: Multi-$$\\chi $$: identifying multiple authors from source code files. Proc. Priv. Enhanc. Technol. 2020(3), 25\u201341 (2020). https:\/\/doi.org\/10.2478\/popets-2020-0044","journal-title":"Proc. Priv. Enhanc. Technol."},{"key":"8_CR5","doi-asserted-by":"publisher","unstructured":"Ahmad, W.U., Chakraborty, S., Ray, B., Chang, K.: Unified pre-training for program understanding and generation. In: Proceedings of the Conference of Human Language Technologies, NAACL-HLT, pp. 2655\u20132668 (2021). https:\/\/doi.org\/10.18653\/v1\/2021.naacl-main.211","DOI":"10.18653\/v1\/2021.naacl-main.211"},{"key":"8_CR6","doi-asserted-by":"crossref","unstructured":"Alasmary, H., et al.: Soteria: detecting adversarial examples in control flow graph-based malware classifiers. In: 40th IEEE International Conference on Distributed Computing Systems, ICDCS, pp. 888\u2013898. IEEE (2020)","DOI":"10.1109\/ICDCS47774.2020.00089"},{"issue":"5","key":"8_CR7","doi-asserted-by":"publisher","first-page":"8977","DOI":"10.1109\/JIOT.2019.2925929","volume":"6","author":"H Alasmary","year":"2019","unstructured":"Alasmary, H., et al.: Analyzing and detecting emerging internet of things malware: a graph-based approach. IEEE Internet Things J. 6(5), 8977\u20138988 (2019)","journal-title":"IEEE Internet Things J."},{"key":"8_CR8","doi-asserted-by":"publisher","unstructured":"Allamanis, M., Barr, E.T., Bird, C., Sutton, C.: Learning natural coding conventions. In: ACM SIGSOFT International Symposium on Foundations of Software Engineering, FSE, pp. 281\u2013293 (2014). https:\/\/doi.org\/10.1145\/2635868.2635883","DOI":"10.1145\/2635868.2635883"},{"key":"8_CR9","doi-asserted-by":"crossref","unstructured":"Aone, C., Okurowski, M.E., Gorlinsky, J.: Trainable, scalable summarization using robust nlp and machine learning. In: Annual Meeting of the Association for Computational Linguistics, COLING-ACL, pp. 62\u201366 (1998). https:\/\/aclanthology.org\/P98-1009\/","DOI":"10.3115\/980845.980856"},{"key":"8_CR10","doi-asserted-by":"publisher","unstructured":"Ayanouz, S., Abdelhakim, B.A., Benahmed, M.: A smart chatbot architecture based NLP and machine learning for health care assistance. In: ACM International Conference on Networking, Information Systems & Security, NISS, pp. 78:1\u201378:6 (2020). https:\/\/doi.org\/10.1145\/3386723.3387897","DOI":"10.1145\/3386723.3387897"},{"key":"8_CR11","unstructured":"CodeXGLUE, M.: General Language Understanding Evaluation benchmark for CODE (2023). https:\/\/microsoft.github.io\/CodeXGLUE\/"},{"key":"8_CR12","unstructured":"code imitator: Github:code-imitator. https:\/\/github.com\/EQuiw\/code-imitator"},{"key":"8_CR13","unstructured":"Islam, A.C., et al.: De-anonymizing programmers via code stylometry. In: USENIX Security Symposium, pp. 255\u2013270 (2015). https:\/\/www.usenix.org\/conference\/usenixsecurity15\/technical-sessions\/presentation\/caliskan-islam"},{"key":"8_CR14","unstructured":"Khan, W., Daud, A., Nasir, J.A., Amjad, T.: A survey on the state-of-the-art machine learning models in the context of NLP. Kuwait J. Sci. 43(4) (2016). https:\/\/journalskuwait.org\/kjs\/index.php\/KJS\/article\/view\/946"},{"key":"8_CR15","doi-asserted-by":"crossref","unstructured":"Rangarajan, A.K., Purushothaman, R.: Disease classification in eggplant using pre-trained VGG16 and MSVM. Sci. Rep. 10(1), 1\u201311 (2020). https:\/\/www.nature.com\/articles\/s41598-020-59108-x","DOI":"10.1038\/s41598-020-59108-x"},{"key":"8_CR16","unstructured":"Le Glaz, A., et\u00a0al.: Machine learning and natural language processing in mental health: systematic review. JMIR 23(5), e15708 (2021). https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC8132982\/"},{"key":"8_CR17","doi-asserted-by":"publisher","unstructured":"Li, Z., Chen, Q.G., Chen, C., Zou, Y., Xu, S.: RoPGen: towards robust code authorship attribution via automatic coding style transformation. In: IEEE\/ACM International Conference on Software Engineering, ICSE, pp. 1906\u20131918 (2022). https:\/\/doi.org\/10.1145\/3510003.3510181","DOI":"10.1145\/3510003.3510181"},{"key":"8_CR18","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1016\/j.cose.2015.04.001","volume":"52","author":"A Mohaisen","year":"2015","unstructured":"Mohaisen, A., Alrawi, O., Mohaisen, M.: AMAL: high-fidelity, behavior-based automated malware analysis and classification. Comput. Secur. 52, 251\u2013266 (2015)","journal-title":"Comput. Secur."},{"key":"8_CR19","unstructured":"Oliinyk, V., Vysotska, V., Burov, Y., Mykich, K., Fernandes, V.B.: Propaganda detection in text data based on NLP and machine learning. In: Proceedings of the International Workshop on Modern Machine Learning Technologies and Data Science, MoMLeT+DS (2020). http:\/\/ceur-ws.org\/Vol-2631\/paper10.pdf"},{"key":"8_CR20","unstructured":"Phan, L.N., et al.: CoTexT: multi-task learning with code-text transformer. CoRR abs\/2105.08645 (2021). https:\/\/arxiv.org\/abs\/2105.08645"},{"key":"8_CR21","unstructured":"Quiring, E., Maier, A., Rieck, K.: Misleading authorship attribution of source code using adversarial learning. In: 28th USENIX Security Symposium (USENIX Security 19), pp. 479\u2013496 (2019)"},{"key":"8_CR22","unstructured":"Raffel, C., et al.: Exploring the limits of transfer learning with a unified text-to-text transformer. J. Mach. Learn. Res. 21, 140:1\u2013140:67 (2020). http:\/\/jmlr.org\/papers\/v21\/20-074.html"},{"key":"8_CR23","doi-asserted-by":"publisher","unstructured":"Rezende, E.R.S.D., Ruppert, G.C.S., Carvalho, T., Ramos, F., de Geus, P.L.: Malicious software classification using transfer learning of ResNet-50 deep neural network. In: International Conference on Machine Learning and Applications, ICMLA, pp. 1011\u20131014 (2017). https:\/\/doi.org\/10.1109\/ICMLA.2017.00-19","DOI":"10.1109\/ICMLA.2017.00-19"},{"key":"8_CR24","unstructured":"StructCoder: Github:structcoder. https:\/\/github.com\/reddy-lab-code-research\/StructCoder"},{"key":"8_CR25","doi-asserted-by":"publisher","unstructured":"Tipirneni, S., Zhu, M., Reddy, C.K.: StructCoder: structure-aware transformer for code generation. CoRR (2022). https:\/\/doi.org\/10.48550\/arXiv.2206.05239","DOI":"10.48550\/arXiv.2206.05239"},{"key":"8_CR26","doi-asserted-by":"crossref","unstructured":"Torrey, L., Shavlik, J.: Transfer learning. In: Handbook of Research on Machine Learning Applications and Trend, pp. 242\u2013264 (2010). https:\/\/ftp.cs.wisc.edu\/machine-learning\/shavlik-group\/torrey.handbook09.pdf","DOI":"10.4018\/978-1-60566-766-9.ch011"}],"container-title":["Lecture Notes in Computer Science","Computational Data and Social Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-0669-3_8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,28]],"date-time":"2024-02-28T21:23:38Z","timestamp":1709155418000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-0669-3_8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819706686","9789819706693"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-0669-3_8","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"29 February 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CSoNet","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computational Data and Social Networks","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hanoi","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Vietnam","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 December 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 December 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"csonet2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/csonet-conf.github.io\/csonet23\/index.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Easy Chair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"64","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":"23","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":"14","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":"36% - 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":"2.7","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":"2.0","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 four extended abstracts are also included in this proceedings.","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)"}}]}}