• DocumentCode
    255684
  • Title

    Evaluation of applicability of modified vector space representation for in-VM malicious activity detection in Cloud

  • Author

    Borisaniya, B. ; Patel, K. ; Patel, D.

  • Author_Institution
    Comput. Eng. Dept., NIT Surat, Surat, India
  • fYear
    2014
  • fDate
    11-13 Dec. 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Malware writers use increasingly complex evasion mechanisms to ensure the concealment of malware against standard anti-malware suites. To identify malware through its behaviour, rather than its approach is an interesting venue of exploration. System call traces are highly indicative of a process behaviour. However, it is difficult to acquire system calls of all processes running on a physical machine. Fortunately, the same cannot be said for the virtual machines, owing to the advancement of Virtual Machine Introspection (VMI) techniques. This opens up the possibility of utilizing system call information for malicious activity detection. In this paper, we study different representations of system call information and evaluate their applicability for in- VM malicious activity detection in Cloud environment.
  • Keywords
    cloud computing; invasive software; virtual machines; applicability evaluation; cloud computing; complex evasion mechanisms; in-VM malicious activity detection; malware concealment; malware identification; modified vector space representation; standard antimalware suites; system call information utilization; system call traces; virtual machine introspection techniques; Cloud computing; Information retrieval; Kernel; Malware; Testing; Vectors; Virtual machining; Cloud; System call traces; Vector Space Model; Virtual Machine Introspection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    India Conference (INDICON), 2014 Annual IEEE
  • Conference_Location
    Pune
  • Print_ISBN
    978-1-4799-5362-2
  • Type

    conf

  • DOI
    10.1109/INDICON.2014.7030588
  • Filename
    7030588