Vul-Mirror: A Few-Shot Learning Method for Discovering Vulnerable Code Clone

He, Yuan and Wang, Wenjie and Sun, Hongyu and Zhang, Yuqing (2020) Vul-Mirror: A Few-Shot Learning Method for Discovering Vulnerable Code Clone. EAI Endorsed Transactions on Security and Safety, 7 (23). e4. ISSN 2032-9393

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Abstract

It is quite common for reusing code in soft development, which may lead to the wide spread of the vulnerability, so automatic detection of vulnerable code clone is becoming more and more important. However, the existing solutions either cannot automatically extract the characteristics of the vulnerable codes or cannot select different algorithms according to different codes, which results in low detection accuracy. In this paper, we consider the identification of vulnerable code clone as a code recognition task and propose a method named Vul-Mirror based on a few-shot learning model for discovering clone vulnerable codes. It can not only automatically extract features of vulnerabilities, but also use the network to measure similarity. The results of experiments on open-source projects of five operating systems show that the accuracy of Vul-Mirror is 95.7%, and its performance is better than the state-of-the-art methods.

Item Type: Article
Uncontrolled Keywords: Vulnerability, few-shot learning, code clone, distance-metric
Subjects: H Social Sciences > H Social Sciences (General)
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor IV
Date Deposited: 26 Mar 2021 14:02
Last Modified: 26 Mar 2021 14:02
URI: https://eprints.eudl.eu/id/eprint/2133

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