dataset · IEEE DataPort · 2021

Open source projects for software vulnerabilities

Nguyen, Van

Cited by 0Open access

Abstract

Here are some real-world data sets for software vulnerabilities.The original real-world data sets, collected by Lin et al. (https://github.com/DanielLin1986/TransferRepresentationLearning), which contain the source codes of vulnerable and non-vulnerable functions obtained from six real-world software projects, namely FFmpeg, LibTIFF, LibPNG, VLC and Pidgin. These datasets cover both multimedia and image application categories.To obtain our used data sets, we preprocess these data sets before inputting into the deep neural networks. Firstly, we standardize the source codes by removing comments, blank lines and non-ASCII characters. Secondly, we map user-defined variables to symbolic names (e.g., “var1”, “var2”) and user-defined functions to symbolic names (e.g., “func1”, “func2”). We also replace integers, real and hexadecimal numbers with a generic "num" token and strings with a generic "str" token. We usehttps://joern.readthedocs.io/en/latest/to analyze the source codes to get user-defined variables and functions.

Cite this paper

APA 7

Nguyen, V. (2021). Open source projects for software vulnerabilities. IEEE DataPort. https://doi.org/10.21227/7h0n-d422

MLA 9

Nguyen, Van. “Open source projects for software vulnerabilities.” IEEE DataPort, 2021, https://doi.org/10.21227/7h0n-d422.

Chicago

Nguyen, Van. 2021. “Open source projects for software vulnerabilities.” IEEE DataPort. https://doi.org/10.21227/7h0n-d422.

Harvard

Nguyen, V. (2021) ‘Open source projects for software vulnerabilities’, IEEE DataPort. Available at: https://doi.org/10.21227/7h0n-d422.

BibTeX

@misc{nguyen2021open,
  title = {{Open source projects for software vulnerabilities}},
  author = {Nguyen, Van},
  journal = {IEEE DataPort},
  year = {2021},
  doi = {10.21227/7h0n-d422}
}

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