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dc.contributor.authorHung, Yu-Hsinen_US
dc.contributor.authorLi, Hong-Weien_US
dc.contributor.authorWu, Yu-Sungen_US
dc.contributor.authorJheng, Bing-Jhongen_US
dc.contributor.authorHuang, Yen-Nunen_US
dc.date.accessioned2019-12-13T01:12:52Z-
dc.date.available2019-12-13T01:12:52Z-
dc.date.issued2018-01-01en_US
dc.identifier.isbn978-1-5386-6553-4en_US
dc.identifier.issn2325-6648en_US
dc.identifier.urihttp://dx.doi.org/10.1109/DSN-W.2018.00037en_US
dc.identifier.urihttp://hdl.handle.net/11536/153298-
dc.description.abstractDue to increasing complexity in security attacks, it is no longer sufficient to rely on generic network-level and system-level events for attack detection. We propose the hybrid-mode information flow tracking (HIT) system to reveal application-level events by integrating static information analysis (IFA) and dynamic information flow tracking (DIFT) into the applications. Preliminary results indicate the effectiveness of the approach in detecting sensitive data leakage with a modest performance overhead.en_US
dc.language.isoen_USen_US
dc.subjectdecoupled dynamic information flow trackingen_US
dc.subjectstatic information flow analysisen_US
dc.subjecttaint propagationen_US
dc.subjectapplication logic vulnerabilitiesen_US
dc.subjectonline systemen_US
dc.subjectanomaly detectionen_US
dc.titleHIT: Hybrid-mode Information Flow Tracking with Taint Semantics Extraction and Replayen_US
dc.typeProceedings Paperen_US
dc.identifier.doi10.1109/DSN-W.2018.00037en_US
dc.identifier.journal2018 48TH ANNUAL IEEE/IFIP INTERNATIONAL CONFERENCE ON DEPENDABLE SYSTEMS AND NETWORKS WORKSHOPS (DSN-W)en_US
dc.citation.spage75en_US
dc.citation.epage76en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000494277000026en_US
dc.citation.woscount0en_US
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