Efficient deep features learning for vulnerability detection using character N-gram embedding
Other Title(s)
نظام تعلم عميق فعال للسمات لكشف الهشاشة باستخدام تضميم الزمور (ن-غرام)
Joint Authors
al-Anzi, Mamduh Ayid
Zaghan, Muhammad
Jawid, Yasir
Source
Jordanian Journal of Computetrs and Information Technology
Issue
Vol. 7, Issue 1 (31 Mar. 2021), pp.25-38, 14 p.
Publisher
Princess Sumaya University for Technology
Publication Date
2021-03-31
Country of Publication
Jordan
No. of Pages
14
Main Subjects
Information Technology and Computer Science
Abstract EN
Deep Learning (DL) techniques were successfully applied to solve challenging problems in the field of Natural Language Processing (NLP).
Since source code and natural text share several similarities, it was possible to adopt text classification techniques, such as word embedding, to propose DL-based Automatic Vulnerabilities Prediction (AVP) approaches.
Although the obtained results were interesting, they were not good enough compared to those obtained in NLP.
In this paper, we propose an improved DL-based AVP approach based on the technique of character n-gram embedding.
We evaluate the proposed approach for 4 types of vulnerabilities using a large c/c++ open-source codebase.
The results show that our approach can yield a very excellent performance which outperforms the performances obtained by previous approaches.
American Psychological Association (APA)
al-Anzi, Mamduh Ayid& Zaghan, Muhammad& Jawid, Yasir. 2021. Efficient deep features learning for vulnerability detection using character N-gram embedding. Jordanian Journal of Computetrs and Information Technology،Vol. 7, no. 1, pp.25-38.
https://search.emarefa.net/detail/BIM-1416144
Modern Language Association (MLA)
al-Anzi, Mamduh Ayid…[et al.]. Efficient deep features learning for vulnerability detection using character N-gram embedding. Jordanian Journal of Computetrs and Information Technology Vol. 7, no. 1 (Mar. 2021), pp.25-38.
https://search.emarefa.net/detail/BIM-1416144
American Medical Association (AMA)
al-Anzi, Mamduh Ayid& Zaghan, Muhammad& Jawid, Yasir. Efficient deep features learning for vulnerability detection using character N-gram embedding. Jordanian Journal of Computetrs and Information Technology. 2021. Vol. 7, no. 1, pp.25-38.
https://search.emarefa.net/detail/BIM-1416144
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 36-38
Record ID
BIM-1416144