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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.issn2096-4862
dc.identifier.doi10.1186/s42400-018-0006-7
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%.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherSpringer Science and Business Media LLC
dc.relation.ispartofpagefrom4
dc.relation.ispartofissue1
dc.relation.ispartofjournalCybersecurity
dc.relation.ispartofvolume1
dc.subject.fieldofresearchNanotechnology
dc.subject.fieldofresearchcode4018
dc.titleDroidEcho: an in-depth dissection of malicious behaviors in Android applications
dc.typeJournal article
dc.type.descriptionC1 - Articles
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. 4
dcterms.licensehttp://creativecommons.org/licenses/by/4.0/
dc.date.updated2020-10-09T03:35:03Z
dc.description.versionVersion of Record (VoR)
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.
gro.hasfulltextFull Text
gro.griffith.authorBai, Guangdong


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