.png){kind=icon}
返回
An automatic classification algorithm for software vulnerability based on weighted word vector and fusion neural network
.png){kind=icon}
PRE
AI
DOI：10.1016/j.cose.2022.103070.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
To address the problem that the traditional vectored representation of software vulnerability data has high-dimensional sparsity and leads to unsatisfactory automatic classification, this paper proposes an au-tomatic classification algorithm for software vulnerabilities based on weighted word vectors and fusion neural network. Firstly, the Term Frequency-Inverse Document Frequency (TF-IDF) algorithm is improved to generate the weighted word vector with low dimension and density according to the category dis-tribution. Secondly, the vulnerability classification model TCNN-BiGRU consists of TextCNN (TCNN) and Bidirectional GRU (BiGRU) is constructed, which has made full use of the advantages of convolutional neural network (CNN) and gate recurrent unit neural network (GRU). TextCNN is used to extract local fea-tures of vulnerability description text, BiGRU is used to extract global features of vulnerability description text, and the output feature vectors are fused to achieve dimensionality reduction. Finally, the Dropout method and Early Stopping method are introduced to suppress overfitting, and a Softmax classifier is used to classify the vulnerability category. The classification performance of the proposed algorithm is verified by ablation experiments, sparsity problem expriments and comparative experiments on the vul-nerability data from NVD dataset on the indicators of accuracy, macro precision rate, macro recall rate and macro F1-score.(c) 2022 Elsevier Ltd. All rights reserved.
Keyword:
Software security
Vulnerability classification
Text classification
Word2Vec
Neural network
期刊
C
IF:
5.4
论文数:
4.6K
被引数:
1.4W
机构
引用论文
Improving Term Weighting Schemes for Short Text Classification in Vector Space Model.png)
IEEE ACCESS
OAAI
IEEE ACCESSIF3.6
OAAI分享收藏Incorporating context -relevant concepts into convolutional neural networks for short text classificationNEUROCOMPUTING
NEUROCOMPUTINGIF6.5
PREAI
分享收藏
Automatic Classification Method for Software Vulnerability Based on Deep Neural NetworkIEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAI分享收藏
查看更多内容