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Technology of Information Security
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 7
2136-2139

Predicting system vulnerability discovery with growth curve

Tang Chenghua1,2a
Pan Ran1
Li Haidong2b
Qiang Baohua1,2b
1. Guangxi Key Laboratory of Trusted Software, Guilin Guangxi 541004, China
2. a. Guangxi Key Laboratory of Cryptography & Information Security, b. Guangxi Cloud Computing & Big Data Collaborative Innovation Center, Guilin University of Electronic Technology, Guilin Guangxi 541004, China
DOI: 10.19734/j.issn.1001-3695.2019.01.0017

Abstract

Aiming at the effective discovery and prediction of system vulnerabilities, this paper proposed a system vulnerability detection and prediction model based on growth curve theory. Firstly, it analyzed the rule of vulnerability discovery, and introduced the concept of growth curve to determine the stage characteristics of vulnerability discovery growth. Secondly, based on the periodic expression of growth theory, it described the relationship between system vulnerability discovery process and time, and proposed the prediction process of system vulnerability discovery and the improved PMGTV model. Finally, it was compared with other models in the experiment and analyzed the validity. PMGTV fits the vulnerability growth process of win_xp, win_server_2003, mac_os_server and ubuntu_linux system software well. It performs best in the sum of squares for error(SSE) and the Chi-square value χ2, and the prediction accuracy is closest to the true value. Results show that the model is more accurate in the prediction of system vulnerability discovery, and provides a reliable basis for taking effective security policy and improving software quality.

Foundation Support

国家自然科学基金资助项目(61462020,61762025)
广西自然科学基金资助项目(2018JJA170058)
广西可信软件重点实验室基金资助项目(kx201506)
广西密码学与信息安全重点实验室基金资助项目(GCIS201619)
广西云计算与大数据协同创新中心项目(YF17101)
广西重点研发计划资助项目(桂科AB17195053)
广西高等学校高水平创新团队及卓越学者计划资助项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.01.0017
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 7
Section: Technology of Information Security
Pages: 2136-2139
Serial Number: 1001-3695(2020)07-044-2136-04

Publish History

[2020-07-05] Printed Article

Cite This Article

唐成华, 潘然, 李海东, 等. 一种基于生长曲线的系统漏洞发现预测模型 [J]. 计算机应用研究, 2020, 37 (7): 2136-2139. (Tang Chenghua, Pan Ran, Li Haidong, et al. Predicting system vulnerability discovery with growth curve [J]. Application Research of Computers, 2020, 37 (7): 2136-2139. )

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.

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