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ETD Abstract Container

Abstract Header

Towards a Malware Language for Use with BERT Transformer—An Approach Using API Call Sequences

Owens, Joshua
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1659532355023855

Abstract Details

2022, MS, University of Cincinnati, Engineering and Applied Science: Computer Science.
Google’s BERT (Bidirectional Encoder Representations from Transformers) algorithm is a neural network based method for processing natural language. In this exploratory study we have used API call sequences to generate a language for use with BERT to perform malware classification with Support Vector Machines. Detecting malware using sequences of API calls has been shown to be a promising area for malware detection, especially when used in conjunction with other features such as opcodes and system calls. The increase in detection accuracy and efficiency achieved through the use of BERT is a desired outcome as malware authors develop more sophisticated techniques for obfuscating their behavior. We have used an open-source dataset that contains sequences of API calls from both known malware and from non-malware and have performed analysis using Support Vector Machines (SVM) for classification, a common method used in previous work on detecting malicious API-based attacks, while using BERT as a preprocessor.
Carla Purdy, Ph.D. (Committee Member)
Anca Ralescu, Ph.D. (Committee Member)
John Gallagher, Ph.D. (Committee Member)
37 p.
Computer Science
Malware; BERT

Recommended Citations

Citations

  • Owens, J. (2022). Towards a Malware Language for Use with BERT Transformer—An Approach Using API Call Sequences [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1659532355023855

    APA Style (7th edition)

  • Owens, Joshua. Towards a Malware Language for Use with BERT Transformer—An Approach Using API Call Sequences. 2022. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1659532355023855.

    MLA Style (8th edition)

  • Owens, Joshua. "Towards a Malware Language for Use with BERT Transformer—An Approach Using API Call Sequences." Master's thesis, University of Cincinnati, 2022. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1659532355023855

    Chicago Manual of Style (17th edition)

ucin1659532355023855
269
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This open access ETD is published by University of Cincinnati and OhioLINK.