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dc.contributor.authorMeng, G
dc.contributor.authorFeng, R
dc.contributor.authorBai, G
dc.contributor.authorChen, K
dc.contributor.authorLiu, Y
dc.date.accessioned2020-10-09T04:39:01Z
dc.date.available2020-10-09T04:39:01Z
dc.date.issued2018
dc.identifier.issn2096-4862en_US
dc.identifier.doi10.1186/s42400-018-0006-7en_US
dc.identifier.urihttp://hdl.handle.net/10072/398266
dc.description.abstractA precise representation for attacks can benefit the detection of malware in both accuracy and efficiency. However, it is still far from expectation to describe attacks precisely on the Android platform. In addition, new features on Android, such as communication mechanisms, introduce new challenges and difficulties for attack detection. In this paper, we propose abstract attack models to precisely capture the semantics of various Android attacks, which include the corresponding targets, involved behaviors as well as their execution dependency. Meanwhile, we construct a novel graph-based model called the inter-component communication graph (ICCG) to describe the internal control flows and inter-component communications of applications. The models take into account more communication channel with a maximized preservation of their program logics. With the guidance of the attack models, we propose a static searching approach to detect attacks hidden in ICCG. To reduce false positive rate, we introduce an additional dynamic confirmation step to check whether the detected attacks are false alarms. Experiments show that DroidEcho can detect attacks in both benchmark and real-world applications effectively and efficiently with a precision of 89.5%.en_US
dc.description.peerreviewedYesen_US
dc.languageEnglish
dc.language.isoeng
dc.publisherSpringer Science and Business Media LLCen_US
dc.relation.ispartofpagefrom4en_US
dc.relation.ispartofissue1en_US
dc.relation.ispartofjournalCybersecurityen_US
dc.relation.ispartofvolume1en_US
dc.subject.fieldofresearchNanotechnologyen_US
dc.subject.fieldofresearchcode1007en_US
dc.titleDroidEcho: an in-depth dissection of malicious behaviors in Android applicationsen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Articlesen_US
dcterms.bibliographicCitationMeng, G; Feng, R; Bai, G; Chen, K; Liu, Y, DroidEcho: an in-depth dissection of malicious behaviors in Android applications, Cybersecurity, 2018, 1 (1), pp. 4en_US
dcterms.licensehttp://creativecommons.org/licenses/by/4.0/en_US
dc.date.updated2020-10-09T03:35:03Z
dc.description.versionVersion of Record (VoR)en_US
gro.rights.copyright© The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.en_US
gro.hasfulltextFull Text
gro.griffith.authorBai, Guangdong


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