In accordance with regulations and requirements, the editorial department's website domain has been changed to arocmag.cn. The original domain (arocmag.com) will be discontinued after Dec. 31st, 2024.
Software Technology Research
|
1107-1110,1114

Open source software vulnerability detection method based on deep clustering

Li Yuancheng1
Huang Rong1
Lai Fenggang2
Mao Yifan2
Cai Lijun3
1. School of Control & Computer Engineering, North China Electric Power University, Beijing 102206, China
2. State Grid Information & Tele-communication Branch, Beijing 100761, China
3. State Grid Fujian Information & Telecommunication Branch, Fuzhou 350003, China

Abstract

Aiming at the open source software vulnerability, this paper proposed a software source code vulnerability detection method based on deep clustering algorithm. This method used code graph model to construct the code attribute map and tra-versed the key code nodes to extract the application programming interfaces(API) sequence, then took the key sequence as the center to cluster and calculated the outliers of the function in each clustering to generate a test report, matched the vulnerability library to detect vulnerabilities in the source code. The experimental results show that the proposed method can locate the key code segments of the vulnerability in open source software and detect the vulnerability.

Foundation Support

国家电网公司总部科技项目(SGFJXT00YJJS1800074)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.09.0721
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 4
Section: Software Technology Research
Pages: 1107-1110,1114
Serial Number: 1001-3695(2020)04-031-1107-04

Publish History

[2020-04-05] Printed Article

Cite This Article

李元诚, 黄戎, 来风刚, 等. 基于深度聚类的开源软件漏洞检测方法 [J]. 计算机应用研究, 2020, 37 (4): 1107-1110,1114. (Li Yuancheng, Huang Rong, Lai Fenggang, et al. Open source software vulnerability detection method based on deep clustering [J]. Application Research of Computers, 2020, 37 (4): 1107-1110,1114. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.


Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)