Automate the tracing of Windows System Calls to identify malicious activities

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dc.contributor.advisorNicholas, Charles
dc.contributor.authorGoenka, Siddhant
dc.contributor.departmentComputer Science and Electrical Engineering
dc.contributor.programComputer Science
dc.date.accessioned2021-01-29T18:13:51Z
dc.date.available2021-01-29T18:13:51Z
dc.date.issued2019-01-01
dc.description.abstractWe describe the problems addressed by various malware or malicious applications on the Microsoft Windows Operating System. Our work focuses on automatic the dynamic malware analysis by intercepting Windows system calls that help to cover a larger range of malware, including the newly evolved fileless variants. Intercepting system calls allow us to monitor malicious activities in a way that malicious behavior can be easily identified without the manual efforts of disassembling binaries. The results will show how our work can help in automating the process of API Hooking for the open source community to detect Byzantine behaviors, rather than focusing on improving the detection mechanism.
dc.formatapplication:pdf
dc.genretheses
dc.identifierdoi:10.13016/m2nbhs-botu
dc.identifier.other12016
dc.identifier.urihttp://hdl.handle.net/11603/20915
dc.languageen
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Theses and Dissertations Collection
dc.relation.ispartofUMBC Graduate School Collection
dc.relation.ispartofUMBC Student Collection
dc.sourceOriginal File Name: Goenka_umbc_0434M_12016.pdf
dc.subjectAPI hooking
dc.subjectFileless Malware
dc.subjectMalware
dc.subjectMalware Analysis
dc.subjectsystem calls
dc.subjectWindows
dc.titleAutomate the tracing of Windows System Calls to identify malicious activities
dc.typeText
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