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Linux-Kernel associated CVE (Common Vulnerabilities and Exposures) intelligent prediction method based on machine learning

A technology of machine learning and intelligent prediction, applied in the fields of computer software and information technology

Inactive Publication Date: 2017-09-22
INST OF SOFTWARE - CHINESE ACAD OF SCI
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  • Abstract
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Problems solved by technology

But so far, there is no machine learning-based method for analyzing Linux discussion email data to automatically predict Linux-related vulnerabilities

Method used

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Embodiment Construction

[0025] Below in conjunction with accompanying drawing, the present invention will be further described through embodiment.

[0026] The Linux-Kernel correlation cve intelligent prediction method based on machine learning of this embodiment, its overall process is as follows figure 1 As shown, each processing module is as figure 2 As shown, the method mainly includes the following steps:

[0027] 1) Crawl the Linux discussion email data, and manually mark it as CVE-related and CVE-irrelevant

[0028] Specifically, manually mark the crawled Linux discussion email data to form a training data set. The steps are as follows: image 3 As shown, the specific description is as follows:

[0029] 1a) Extract the title, sender, sending time of all emails under the discussion topic, keyword extraction of email content, interval time between replies, and the webpage link where the email is located, and turn to 1b).

[0030] 1b) Determine whether the web page link where the email is lo...

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Abstract

The invention discloses a Linux-Kernel associated CVE (Common Vulnerabilities and Exposures) intelligent prediction method based on machine learning. The method comprises the following steps that: 1) from a Linux discussion mail data publishing website, crawling the data of a set time period, carrying out classified storage according to themes by mail titles; 2) labeling the crawled data, i.e., labeling a discussion theme as CVE association and CVE non association according to the contents of the discussion theme and CVE description contents; 3) randomly extracting multiple pieces of sample data labeled as CVE association and multiple pieces of sample data labeled as CVE non association, and utilizing a machine learning algorithm to train to obtain a CVE vulnerability prediction model; and 4) utilizing the CVE vulnerability prediction model to automatically predict new mail data to obtain the prediction result and the result explanation of the mail data. By use of the method, possible vulnerability information in a kernel can be found as early as possible, a detailed explanation for a judgment result that the vulnerability may be caused is given for reference.

Description

technical field [0001] The invention belongs to the technical fields of information technology and computer software, and in particular relates to a machine learning-based Linux-Kernel correlation CVE function prediction method. Background technique [0002] Linux is an open source computer operating system kernel. It is a Unix-like operating system written in C language and conforms to the POSIX standard. Linux was first developed by Finnish hacker Linus Torvalds as an attempt to provide a free Unix-like operating system on the Intel x86 architecture. The project started in 1991 with the assistance of some Minix hackers in the early days of the project, and today countless programmers around the world are helping the project pro bono. [0003] Due to the open source nature of Linux, there are endless methods of vulnerability analysis and prediction for Linux, mainly including static source code analysis and dynamic runtime analysis. But so far, there is no machine learni...

Claims

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Application Information

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IPC IPC(8): G06F21/57G06F17/30
CPCG06F16/951G06F21/577
Inventor 龙清吴敬征李牧
Owner INST OF SOFTWARE - CHINESE ACAD OF SCI
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