• DocumentCode
    2559592
  • Title

    R/Bootkit detection based on trusted computing and neural network

  • Author

    Sha, Le-Tian ; Wang, Hong-Xia

  • Author_Institution
    Inf. Security & Nat. Comput. Grid Lab., Southwest Jiaotong Univ., Chengdu, China
  • fYear
    2010
  • fDate
    16-18 April 2010
  • Firstpage
    117
  • Lastpage
    121
  • Abstract
    There is no standardized definition to characterize R/Bootkit that threatens kernel security of boot process in operating system. Most existing detection techniques attempt to detect the performance of it in the running stage of operating system, rather than protect kernel modules in the boot process. This paper proposes a new trust chain, where the trust root is TPM, which checks all kernel modules from CPU to the application environment, then security of kernel modules can be ensured out of R/Bootkit. In addition, a neural network is designed to identify known and unknown R/Bootkit. The test results show that we can correctly detect illegal modifications for kernel modules.
  • Keywords
    neural nets; operating system kernels; R/Bootkit detection; TPM; boot process; kernel module protection; neural network; operating system; trusted computing; Computer networks; Grid computing; Information security; Kernel; Laboratories; National security; Neural networks; Operating systems; Protection; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Management and Engineering (ICIME), 2010 The 2nd IEEE International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-5263-7
  • Electronic_ISBN
    978-1-4244-5265-1
  • Type

    conf

  • DOI
    10.1109/ICIME.2010.5478345
  • Filename
    5478345