{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T17:19:00Z","timestamp":1743095940464,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":17,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811590306"},{"type":"electronic","value":"9789811590313"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-981-15-9031-3_5","type":"book-chapter","created":{"date-parts":[[2020,9,25]],"date-time":"2020-09-25T07:04:29Z","timestamp":1601017469000},"page":"52-61","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Generating Adversarial Malware Examples with API Semantics-Awareness for Black-Box Attacks"],"prefix":"10.1007","author":[{"given":"Xiaowei","family":"Peng","sequence":"first","affiliation":[]},{"given":"Hequn","family":"Xian","sequence":"additional","affiliation":[]},{"given":"Qian","family":"Lu","sequence":"additional","affiliation":[]},{"given":"Xiuqing","family":"Lu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,9,22]]},"reference":[{"key":"5_CR1","first-page":"29","volume":"53","author":"Z Kai","year":"2017","unstructured":"Kai, Z., Shifei, D.: Advances in image super-resolution reconstruction. Comput. Eng. Appl. 53, 29\u201335 (2017)","journal-title":"Comput. Eng. Appl."},{"key":"5_CR2","unstructured":"Lin, Y., Han, X., Xie, R., Liu, Z., Sun, M.: Knowledge Representation Learning: A Quantitative Review (2018). arXiv e-prints \narXiv:1812.10901"},{"key":"5_CR3","unstructured":"Szegedy, C., Zaremba, W., Sutskever, I., Bruna, J., Erhan, D., Goodfellow, I., Fergus, R.: Intriguing properties of neural networks (2013). arXiv preprint \narXiv:1312.6199"},{"key":"5_CR4","unstructured":"Demetrio, L., Biggio, B., Lagorio, G., Roli, F., Armando, A.: Explaining vulnerabilities of deep learning to adversarial malware binaries (2019)"},{"key":"5_CR5","unstructured":"Goodfellow, I.J., Shlens, J., Szegedy, C.: Explaining and harnessing adversarial examples (2014). arXiv preprint \narXiv:1412.6572"},{"key":"5_CR6","unstructured":"Hu, W., Tan, Y.: Generating adversarial malware examples for black-box attacks based on gan (2017). arXiv preprint \narXiv:1702.05983"},{"key":"5_CR7","doi-asserted-by":"crossref","unstructured":"Chen, P.-Y., Zhang, H., Sharma, Y., Yi, J., Hsieh, C.-J.: Zoo: Zeroth order optimization based black-box attacks to deep neural networks without training substitute models. In: Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security, pp. 15\u201326 (2017)","DOI":"10.1145\/3128572.3140448"},{"key":"5_CR8","doi-asserted-by":"crossref","unstructured":"Duarte-Garcia, H.L., Morales-Medina, C.D., Hernandez-Suarez, A., Sanchez-Perez, G., Toscano-Medina, K., Perez-Meana, H., Sanchez, V.: A Semi-supervised learning methodology for malware categorization using weighted word embeddings. In: 2019 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW), pp. 238\u2013246. IEEE (2019)","DOI":"10.1109\/EuroSPW.2019.00033"},{"key":"5_CR9","unstructured":"Johnson, R., Zhang, T.: Supervised and semi-supervised text categorization using one-hot LSTM for region embeddings. Stat. 1050 (2016)"},{"key":"5_CR10","first-page":"433","volume":"57","author":"DS Du Peng","year":"2020","unstructured":"Du Peng, D.S.: A DGA domain name detection method based on deep learning models with mixed word embedding. J. Comput. Res. Dev. 57, 433 (2020)","journal-title":"J. Comput. Res. Dev."},{"key":"5_CR11","unstructured":"Zhang, Y., Gan, Z., Carin, L.: Generating text via adversarial training. In: NIPS workshop on Adversarial Training (2016)"},{"key":"5_CR12","unstructured":"Weigelt, S., Landh\u00e4u\u00dfer, M., Blersch, M.: How to Prepare an API for Programming in Natural Language (2019)"},{"key":"5_CR13","doi-asserted-by":"crossref","unstructured":"Papernot, N., McDaniel, P., Goodfellow, I., Jha, S., Celik, Z.B., Swami, A.: Practical black-box attacks against machine learning. In: Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security, pp. 506\u2013519 (2017)","DOI":"10.1145\/3052973.3053009"},{"key":"5_CR14","unstructured":"Papernot, N., McDaniel, P., Goodfellow, I.: Transferability in machine learning: from phenomena to black-box attacks using adversarial samples (2016). arXiv preprint \narXiv:1605.07277"},{"key":"5_CR15","doi-asserted-by":"publisher","first-page":"35403","DOI":"10.1109\/ACCESS.2020.2974752","volume":"8","author":"N Martins","year":"2020","unstructured":"Martins, N., Cruz, J.M., Cruz, T., Abreu, P.H.J.I.A.: Adversarial machine learning applied to intrusion and malware scenarios: a systematic review. IEEE Access 8, 35403\u201335419 (2020)","journal-title":"IEEE Access"},{"issue":"3","key":"5_CR16","doi-asserted-by":"publisher","first-page":"717","DOI":"10.1007\/s00607-019-00768-7","volume":"102","author":"S Wang","year":"2019","unstructured":"Wang, S., Zhou, W., Jiang, C.: A survey of word embeddings based on deep learning. Computing 102(3), 717\u2013740 (2019). \nhttps:\/\/doi.org\/10.1007\/s00607-019-00768-7","journal-title":"Computing"},{"key":"5_CR17","doi-asserted-by":"crossref","unstructured":"Wang, Z., Liu, Z., Chen, Z., Hu, H., Lian, S.: A neural virtual anchor synthesizer based on seq2seq and gan models. In: 2019 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct), pp. 233\u2013236. IEEE (2019)","DOI":"10.1109\/ISMAR-Adjunct.2019.00-40"}],"container-title":["Communications in Computer and Information Science","Security and Privacy in Social Networks and Big Data"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-15-9031-3_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,9,25]],"date-time":"2020-09-25T07:06:44Z","timestamp":1601017604000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-981-15-9031-3_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9789811590306","9789811590313"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-981-15-9031-3_5","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"22 September 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SocialSec","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on Security and Privacy in Social Networks and Big Data","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Tianjin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","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":"26 September 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 September 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"socialsec2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/nsclab.org\/socialsec2020\/","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":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"111","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":"38","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":"34% - 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":"5.6","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}