{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T23:03:52Z","timestamp":1743116632088,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":21,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789811951930"},{"type":"electronic","value":"9789811951947"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-981-19-5194-7_7","type":"book-chapter","created":{"date-parts":[[2022,8,9]],"date-time":"2022-08-09T23:03:17Z","timestamp":1660086197000},"page":"80-93","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Survey of Malware Classification Methods Based on Data Flow Graph"],"prefix":"10.1007","author":[{"given":"Tingting","family":"Jiang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lingling","family":"Cui","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zedong","family":"Lin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Faming","family":"Lu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,8,10]]},"reference":[{"key":"7_CR1","unstructured":"AV-TEST anti-virus testing agency static analysis report. https:\/\/www.avtest.org\/de\/statistiken\/malweare"},{"key":"7_CR2","unstructured":"Yan, L.: Detection and classification of malicious programs based on deep learning. Xidian University"},{"key":"7_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11416-015-0261-z","volume":"13","author":"A Damodaran","year":"2017","unstructured":"Damodaran, A., Troia, F.D., Visaggio, C.A., Austin, T.H., Stamp, M.: A comparison of static, dynamic, and hybrid analysis for malware detection. J. Comput. Virol. Hack. Tech. 13, 1\u201312 (2017)","journal-title":"J. Comput. Virol. Hack. Tech."},{"issue":"5","key":"7_CR4","first-page":"18","volume":"58","author":"W Jialai","year":"2021","unstructured":"Jialai, W., Chao, Z., Xuyan, Q., et al.: Overview of intelligent detection of malware on windows platform. J. Comput. Res. Dev. 58(5), 18 (2021)","journal-title":"J. Comput. Res. Dev."},{"issue":"3","key":"7_CR5","first-page":"1","volume":"16","author":"M Bat-Erdene","year":"2016","unstructured":"Bat-Erdene, M., Park, H., Li, H., Lee, H., Choi, M.S.: Entropy analysis to classify unknown packing algorithms for malware detection. Int. J. Inf. Secur. 16(3), 1\u201322 (2016)","journal-title":"Int. J. Inf. Secur."},{"key":"7_CR6","doi-asserted-by":"crossref","unstructured":"Cesare, S., Xiang, Y.: A fast flowgraph based classification system for packed and polymorphic malware on the Endhost. In: IEEE International Conference on Advanced Information Networking & Applications. IEEE (2010)","DOI":"10.1109\/AINA.2010.121"},{"key":"7_CR7","unstructured":"Zhou, Y., Lu, T., Du, Y., Guo, R., Bao, Y., Li, Mo: Detection and analysis of windows malicious code based on thread fusion features. Comput. Eng. Appl. 1\u201311 (2020)"},{"key":"7_CR8","first-page":"14","volume":"6","author":"X Min","year":"2009","unstructured":"Min, X., Tianfu, Z.: Malicious code detection method based on behavioral features. Netw. Inform. 6, 14\u201316 (2009)","journal-title":"Netw. Inform."},{"key":"7_CR9","doi-asserted-by":"crossref","unstructured":"W\u00fcchner, T., Ochoa, M., Pretschner, A.: Malware detection with quantitative data flow graphs. In: Proceedings of the 9th ACM symposium on Information, computer and communications security (ASIA CCS\u201914), pp. 271\u2013282. Association for Computing Machinery, New York, NY, USA (2014)","DOI":"10.1145\/2590296.2590319"},{"issue":"3","key":"7_CR10","first-page":"7","volume":"6","author":"Y Pin","year":"2020","unstructured":"Pin, Y., Yue, Z., Lei, Z.: Malware code family classification based on attribute data flow graph. Inform. Secur. Res. 6(3), 7 (2020)","journal-title":"Inform. Secur. Res."},{"key":"7_CR11","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1007\/978-3-319-20550-2_6","volume-title":"Detection of Intrusions and Malware, and Vulnerability Assessment","author":"T W\u00fcchner","year":"2015","unstructured":"W\u00fcchner, T., Ochoa, M., Pretschner, A.: Robust and effective malware detection through quantitative data flow graph metrics. In: Almgren, M., Gulisano, V., Maggi, F. (eds.) Detection of Intrusions and Malware, and Vulnerability Assessment, pp. 98\u2013118. Springer International Publishing, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-20550-2_6"},{"issue":"11","key":"7_CR12","first-page":"12","volume":"31","author":"W Jie","year":"2020","unstructured":"Jie, W., Changqing, W.: Malware detection method based on subgraph similarity. J. Softw. 31(11), 12 (2020)","journal-title":"J. Softw."},{"key":"7_CR13","unstructured":"Hamilton, W., Ying, Z., Leskovee, J.: Inductive representation learning on large graphs. In: Advance in Neural Information Processing Systems, pp. 1024\u20131034. MIT Press, Cambridge, MA (2017)"},{"issue":"1","key":"7_CR14","first-page":"171","volume":"33","author":"Z Wang","year":"2022","unstructured":"Wang, Z., Shen, H., Cao, G., Cheng, X.: A review of graph classification research. J. Softw. 33(1), 171\u2013192 (2022)","journal-title":"J. Softw."},{"key":"7_CR15","doi-asserted-by":"crossref","unstructured":"Christodorescu, M., Jha, S., Kruegel, C.: Mining specifications of malicious behavior. In: Proc. of the 1st India Software Engineering Conf., pp. 5\u221214. ACM, New York (2008)","DOI":"10.1145\/1342211.1342215"},{"key":"7_CR16","doi-asserted-by":"crossref","unstructured":"Park, Y., Reeves, D.S., Stamp, M.: Deriving common malware behavior through graph clustering. In: Proc. of the 6th ACM Symp. on Information, Computer and Communications Security, pp. 497\u2212502. ACM, New York (2011)","DOI":"10.1145\/1966913.1966986"},{"key":"7_CR17","doi-asserted-by":"crossref","unstructured":"Fan, M., et al.: Frequent subgraph based familial classification of android malware. In: IEEE International Symposium on Software Reliability Engineering. IEEE (2016)","DOI":"10.1109\/ISSRE.2016.14"},{"key":"7_CR18","unstructured":"Kwon, J.-H, Lee, J.H., Jeong, H.-C., Lee, H.: Metamorphic malware detection using subgraph matching. J. Korea Inst. Inform. Secur. Cryptology 21(2) (2011)"},{"key":"7_CR19","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1109\/TNNLS.2020.2978386","volume":"32","author":"Z Wu","year":"2019","unstructured":"Wu, Z., Pan, S., Chen, F., Long, G., Zhang, C., Yu, P.S.: A comprehensive survey on graph neural networks. IEEE Trans. Neural Netw. Learn. Syst. 32, 4\u201324 (2019)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"7_CR20","first-page":"4","volume":"32","author":"FTN Kip","year":"2016","unstructured":"Kip, F.T.N., Welling, M.: Semi-supervised classification with graph convolutional networks. IEEE Trans. Neural Netw. Learn. Syst. 32, 4\u201324 (2016)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"7_CR21","doi-asserted-by":"publisher","unstructured":"Schranko de Oliveira, A., Sassi, R.J.: Behavioral malware detection using deep graph convolutional neural networks. TechRxiv. Preprint (2019). https:\/\/doi.org\/10.36227\/techrxiv.10043099.v1","DOI":"10.36227\/techrxiv.10043099.v1"}],"container-title":["Communications in Computer and Information Science","Data Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-19-5194-7_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T15:13:30Z","timestamp":1710256410000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-19-5194-7_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9789811951930","9789811951947"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-981-19-5194-7_7","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"10 August 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICPCSEE","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference of Pioneering Computer Scientists, Engineers and Educators","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chengdu","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":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 August 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 August 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icpcsee2022","order":10,"name":"conference_id","label":"Conference ID","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":"261","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":"65","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":"26","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":"25% - 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","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)"}}]}}