Please use this identifier to cite or link to this item: https://doi.org/10.1109/ACCESS.2018.2795383
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dc.titleDetecting Malicious Behaviors in JavaScript Applications
dc.contributor.authorMao, J.
dc.contributor.authorBian, J.
dc.contributor.authorBai, G.
dc.contributor.authorWang, R.
dc.contributor.authorChen, Y.
dc.contributor.authorXiao, Y.
dc.contributor.authorLiang, Z.
dc.date.accessioned2021-12-09T05:03:00Z
dc.date.available2021-12-09T05:03:00Z
dc.date.issued2018
dc.identifier.citationMao, J., Bian, J., Bai, G., Wang, R., Chen, Y., Xiao, Y., Liang, Z. (2018). Detecting Malicious Behaviors in JavaScript Applications. IEEE Access 6 : 12284-12294. ScholarBank@NUS Repository. https://doi.org/10.1109/ACCESS.2018.2795383
dc.identifier.issn2169-3536
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/210118
dc.description.abstractJavaScript applications are widely used in a range of scenarios, including Web applications, mobile applications, and server-side applications. On one hand, due to its excellent cross-platform support, Javascript has become the core technology of social network platforms. On the other hand, the flexibility of the JavaScript language makes such applications prone to attacks that inject malicious behaviors. In this paper, we propose a detection technique to identify malicious behaviors in JavaScript applications. Our method models an application's normal behavior on function activation, which is used as a basis to detect attacks. We prototyped our solution on the popular JavaScript engine V8 and used it to detect attacks on the android system. Our evaluation shows the effectiveness of our approach in detecting injection attacks to JavaScript applications. © 2013 IEEE.
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.sourceScopus OA2018
dc.subjectbehavior anomaly detection
dc.subjecthybrid mobile app
dc.subjectJavaScript application
dc.typeArticle
dc.contributor.departmentDEPARTMENT OF COMPUTER SCIENCE
dc.description.doi10.1109/ACCESS.2018.2795383
dc.description.sourcetitleIEEE Access
dc.description.volume6
dc.description.page12284-12294
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