The search functionality is under construction.
The search functionality is under construction.

Character-Level Convolutional Neural Network for Predicting Severity of Software Vulnerability from Vulnerability Description

Shunta NAKAGAWA, Tatsuya NAGAI, Hideaki KANEHARA, Keisuke FURUMOTO, Makoto TAKITA, Yoshiaki SHIRAISHI, Takeshi TAKAHASHI, Masami MOHRI, Yasuhiro TAKANO, Masakatu MORII

  • Full Text Views

    0

  • Cite this

Summary :

System administrators and security officials of an organization need to deal with vulnerable IT assets, especially those with severe vulnerabilities, to minimize the risk of these vulnerabilities being exploited. The Common Vulnerability Scoring System (CVSS) can be used as a means to calculate the severity score of vulnerabilities, but it currently requires human operators to choose input values. A word-level Convolutional Neural Network (CNN) has been proposed to estimate the input parameters of CVSS and derive the severity score of vulnerability notes, but its accuracy needs to be improved further. In this paper, we propose a character-level CNN for estimating the severity scores. Experiments show that the proposed scheme outperforms conventional one in terms of accuracy and how errors occur.

Publication
IEICE TRANSACTIONS on Information Vol.E102-D No.9 pp.1679-1682
Publication Date
2019/09/01
Publicized
2019/06/21
Online ISSN
1745-1361
DOI
10.1587/transinf.2018OFL0006
Type of Manuscript
Special Section LETTER (Special Section on Log Data Usage Technology and Office Information Systems)
Category
Cybersecurity

Authors

Shunta NAKAGAWA
  Kobe University
Tatsuya NAGAI
  Kobe University
Hideaki KANEHARA
  National Institute of Information and Communications Technology
Keisuke FURUMOTO
  National Institute of Information and Communications Technology
Makoto TAKITA
  Kobe University
Yoshiaki SHIRAISHI
  Kobe University
Takeshi TAKAHASHI
  National Institute of Information and Communications Technology
Masami MOHRI
  Gifu University
Yasuhiro TAKANO
  Kobe University
Masakatu MORII
  Kobe University

Keyword