{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T03:38:01Z","timestamp":1743133081046,"version":"3.40.3"},"publisher-location":"Cham","reference-count":11,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030324087"},{"type":"electronic","value":"9783030324094"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","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":[[2019]]},"DOI":"10.1007\/978-3-030-32409-4_31","type":"book-chapter","created":{"date-parts":[[2019,10,27]],"date-time":"2019-10-27T20:03:00Z","timestamp":1572206580000},"page":"493-497","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A Performance-Sensitive Malware Detection System on Mobile Platform"],"prefix":"10.1007","author":[{"given":"Ruitao","family":"Feng","sequence":"first","affiliation":[]},{"given":"Yang","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Shangwei","family":"Lin","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,10,28]]},"reference":[{"unstructured":"Schlegel, R., Zhang, K., Zhou, X.Y., Intwala, M., Kapadia, A., Wang, X.: Soundcomber: a stealthy and context-aware sound trojan for smartphones. In: NDSS, vol. 11, pp. 17\u201333, February 2011","key":"31_CR1"},{"unstructured":"Zhou, Y., Wang, Z., Zhou, W., Jiang, X.: Hey, you, get off of my market: detecting malicious apps in official and alternative android markets. In: NDSS, vol. 25, No. 4, pp. 50\u201352, February 2012","key":"31_CR2"},{"unstructured":"Yan, L.K., Yin, H.: DroidScope: seamlessly reconstructing the OS and dalvik semantic views for dynamic android malware analysis. In: Presented as part of the 21st USENIX Security Symposium (USENIX Security 12), pp. 569\u2013584 (2012)","key":"31_CR3"},{"doi-asserted-by":"crossref","unstructured":"Wu, C., Zhou, Y., Patel, K., Liang, Z., Jiang, X. AirBag: Boosting smartphone resistance to malware infection, In: NDSS, February 2014","key":"31_CR4","DOI":"10.14722\/ndss.2014.23164"},{"doi-asserted-by":"crossref","unstructured":"Arzt, S., Rasthofer, S., Fritz, C., Bodden, E., Bartel, A., Klein, J., McDaniel, P.: FlowDroid: Precise context, flow, field, object-sensitive and lifecycle-aware taint analysis for android apps. ACM SIGPLAN Not. 49(6), 259\u2013269 (2014)","key":"31_CR5","DOI":"10.1145\/2666356.2594299"},{"doi-asserted-by":"crossref","unstructured":"Li, L., et al.: IccTa: Detecting inter-component privacy leaks in android apps. In: Proceedings of the 37th International Conference on Software Engineering-Volume 1, pp. 280\u2013291. IEEE Press, May 2015","key":"31_CR6","DOI":"10.1109\/ICSE.2015.48"},{"doi-asserted-by":"crossref","unstructured":"Wong, M.Y., Lie, D.: IntelliDroid: a targeted input generator for the dynamic analysis of android malware. In: NDSS, vol. 16, pp. 21\u201324, February 2016","key":"31_CR7","DOI":"10.14722\/ndss.2016.23118"},{"doi-asserted-by":"crossref","unstructured":"Arp, D., Spreitzenbarth, M., Hubner, M., Gascon, H., Rieck, K.: DREBIN: effective and explainable detection of Android malware in your pocket. In: NDSS (2014)","key":"31_CR8","DOI":"10.14722\/ndss.2014.23247"},{"key":"31_CR9","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1007\/978-3-319-11203-9_10","volume-title":"Computer Security - ESORICS 2014","author":"C Yang","year":"2014","unstructured":"Yang, C., Xu, Z., Gu, G., Yegneswaran, V., Porras, P.: DroidMiner: automated mining and characterization of fine-grained malicious behaviors in android applications. In: Kuty\u0142owski, M., Vaidya, J. (eds.) ESORICS 2014. LNCS, vol. 8712, pp. 163\u2013182. Springer, Cham (2014). \n                      https:\/\/doi.org\/10.1007\/978-3-319-11203-9_10"},{"doi-asserted-by":"crossref","unstructured":"Chen, S., Xue, M., Tang, Z., Xu, L., Zhu, H.: Stormdroid: A streaminglized machine learning-based system for detecting android malware. In Proceedings of the 11th ACM on Asia Conference on Computer and Communications Security, pp. 377\u2013388. ACM, May 2016","key":"31_CR10","DOI":"10.1145\/2897845.2897860"},{"doi-asserted-by":"crossref","unstructured":"Chen, S., Xue, M., Fan, L., Hao, S., Xu, L., Zhu, H., and Li, B. (2018). Automated poisoning attacks and defenses in malware detection systems: An adversarial machine learning approach. computers & security, 73, 326\u2013344","key":"31_CR11","DOI":"10.1016\/j.cose.2017.11.007"}],"container-title":["Lecture Notes in Computer Science","Formal Methods and Software Engineering"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-32409-4_31","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,11,1]],"date-time":"2019-11-01T22:08:09Z","timestamp":1572646089000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-32409-4_31"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030324087","9783030324094"],"references-count":11,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-32409-4_31","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"28 October 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICFEM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Formal Engineering Methods","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shenzhen","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":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 November 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 November 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icfem2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/csse.szu.edu.cn\/icfem2019\/","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":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"94","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":"28","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":"30% - 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":"4","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)"}}]}}