Academic Journal

Data correlation analysis assists vulnerability detection.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Data correlation analysis assists vulnerability detection. (English)
Συγγραφείς: YIN Qing, LI Yong-wei, SHU Hui
Πηγή: Application Research of Computers / Jisuanji Yingyong Yanjiu; Feb2014, Vol. 31 Issue 2, p583-589, 4p
Θεματικοί όροι: Data analysis, Statistical correlation, Decompilers (Computer programs), Syntax in programming languages, Algorithms, Information science, Automation
Περίληψη: In order to improve the efficiency of such vulnerabilities discovery, this paper presented a method which used data correlation analysis auxiliary vulnerabilities discovery. Firstly, the method decompiled target files and constructed the abstract syntax tree (AST), designed algorithm to extract the inversely correlation information of key variables. Then, it applied the extracted information to detect of buffer overflow. This method has obvious advantages in non-source code vulnerability discovery, can discover buffer overflow in the software effectively, and improve the efficiency and automation of vulnerability discovery. [ABSTRACT FROM AUTHOR]
Copyright of Application Research of Computers / Jisuanji Yingyong Yanjiu is the property of Application Research of Computers Edition and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Βάση Δεδομένων: Complementary Index
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An: 95444170
RelevancyScore: 835
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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IllustrationInfo
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  Label: Title
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  Data: Data correlation analysis assists vulnerability detection. (English)
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22YIN+Qing%22">YIN Qing</searchLink><br /><searchLink fieldCode="AR" term="%22LI+Yong-wei%22">LI Yong-wei</searchLink><br /><searchLink fieldCode="AR" term="%22SHU+Hui%22">SHU Hui</searchLink>
– Name: TitleSource
  Label: Source
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  Data: Application Research of Computers / Jisuanji Yingyong Yanjiu; Feb2014, Vol. 31 Issue 2, p583-589, 4p
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Data+analysis%22">Data analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+correlation%22">Statistical correlation</searchLink><br /><searchLink fieldCode="DE" term="%22Decompilers+%28Computer+programs%29%22">Decompilers (Computer programs)</searchLink><br /><searchLink fieldCode="DE" term="%22Syntax+in+programming+languages%22">Syntax in programming languages</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Information+science%22">Information science</searchLink><br /><searchLink fieldCode="DE" term="%22Automation%22">Automation</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: In order to improve the efficiency of such vulnerabilities discovery, this paper presented a method which used data correlation analysis auxiliary vulnerabilities discovery. Firstly, the method decompiled target files and constructed the abstract syntax tree (AST), designed algorithm to extract the inversely correlation information of key variables. Then, it applied the extracted information to detect of buffer overflow. This method has obvious advantages in non-source code vulnerability discovery, can discover buffer overflow in the software effectively, and improve the efficiency and automation of vulnerability discovery. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Application Research of Computers / Jisuanji Yingyong Yanjiu is the property of Application Research of Computers Edition and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.3969/j.issn.1001-3695.2014.02.063
    Languages:
      – Code: chi
        Text: Chinese
    PhysicalDescription:
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        PageCount: 4
        StartPage: 583
    Subjects:
      – SubjectFull: Data analysis
        Type: general
      – SubjectFull: Statistical correlation
        Type: general
      – SubjectFull: Decompilers (Computer programs)
        Type: general
      – SubjectFull: Syntax in programming languages
        Type: general
      – SubjectFull: Algorithms
        Type: general
      – SubjectFull: Information science
        Type: general
      – SubjectFull: Automation
        Type: general
    Titles:
      – TitleFull: Data correlation analysis assists vulnerability detection.
        Type: main
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      – PersonEntity:
          Name:
            NameFull: YIN Qing
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          Name:
            NameFull: LI Yong-wei
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            NameFull: SHU Hui
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          Dates:
            – D: 01
              M: 02
              Text: Feb2014
              Type: published
              Y: 2014
          Identifiers:
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              Value: 10013695
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            – Type: volume
              Value: 31
            – Type: issue
              Value: 2
          Titles:
            – TitleFull: Application Research of Computers / Jisuanji Yingyong Yanjiu
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