Tensor Methods for Static Malware Analysis
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Author/Creator ORCID
Date
2023-01-01
Type of Work
Department
Computer Science and Electrical Engineering
Program
Computer Science
Citation of Original Publication
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Access limited to the UMBC community. Item may possibly be obtained via Interlibrary Loan through a local library, pending author/copyright holder's permission.
Access limited to the UMBC community. Item may possibly be obtained via Interlibrary Loan thorugh a local library, pending author/copyright holder's permission.
Access limited to the UMBC community. Item may possibly be obtained via Interlibrary Loan through a local library, pending author/copyright holder's permission.
Access limited to the UMBC community. Item may possibly be obtained via Interlibrary Loan thorugh a local library, pending author/copyright holder's permission.
Subjects
Abstract
Tensor decomposition methods have been used in many fields to find latent factors among data. Recent developments have made automatic decomposition feasible and has shown practical use in a network intrusion context. This work explores how tensors can be used in wide scale static malware analysis to provide automatic useful context to human analysts, where other automatic tools usually rely on short and incomprehensible strings of raw bytes.