• DocumentCode
    2160136
  • Title

    MapReduce based log file analysis for system threats and problem identification

  • Author

    Vernekar, S.S. ; Buchade, A.

  • Author_Institution
    Dept. of Comput. Eng., Pune Inst. of Comput. Technol., Pune, India
  • fYear
    2013
  • fDate
    22-23 Feb. 2013
  • Firstpage
    831
  • Lastpage
    835
  • Abstract
    Log files are primary source of information for identifying the System threats and problems that occur in the System at any point of time. These threats and problem in the system can be identified by analyzing the log file and finding the patterns for possible suspicious behavior. The concern administrator can then be provided with appropriate alter or warning regarding these security threats and problems in the system, which are generated after the log files are analyzed. Based upon this alters or warnings the administrator can take appropriate actions. Many tools or approaches are available for this purpose, some are proprietary and some are open source. This paper presents a new approach which uses a MapReduce algorithm for the purpose of log file analysis, providing appropriate security alerts or warning. The results of this system can then be compared with the tools available.
  • Keywords
    data analysis; parallel processing; security of data; MapReduce based log file analysis; problem identification; security alert; security threat; security warning; system threat; Algorithm design and analysis; Clustering algorithms; Computers; Conferences; Context; Correlation; Security; Event Correlation; Log File analysis; MapReduce;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advance Computing Conference (IACC), 2013 IEEE 3rd International
  • Conference_Location
    Ghaziabad
  • Print_ISBN
    978-1-4673-4527-9
  • Type

    conf

  • DOI
    10.1109/IAdCC.2013.6514334
  • Filename
    6514334