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HIDS: A host based intrusion detection system for cloud computing environment

Author

Listed:
  • Prachi Deshpande

    (Indian Institute of Technology Roorkee)

  • S. C. Sharma

    (Indian Institute of Technology Roorkee)

  • S. K. Peddoju

    (Indian Institute of Technology Roorkee)

  • S. Junaid

    (Indian Institute of Technology Roorkee)

Abstract

The paper reports a host based intrusion detection model for Cloud computing environment along with its implementation and analysis. This model alerts the Cloud user against the malicious activities within the system by analyzing the system call traces. The method analyses only selective system call traces, the failed system call trace, rather than all. An early detection of intrusions with reduced computational burden can be possible with this feature. The reported model provides security as a service (SecaaS) in the infrastructure layer of the Cloud environment. Implementation result shows 96 % average intrusion detection sensitivity.

Suggested Citation

  • Prachi Deshpande & S. C. Sharma & S. K. Peddoju & S. Junaid, 2018. "HIDS: A host based intrusion detection system for cloud computing environment," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(3), pages 567-576, June.
    • Handle: RePEc:spr:ijsaem:v:9:y:2018:i:3:d:10.1007_s13198-014-0277-7
    DOI: 10.1007/s13198-014-0277-7
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    Cited by:

    1. Sohail Saif & Nahal Yasmin & Suparna Biswas, 2023. "Feature engineering based performance analysis of ML and DL algorithms for Botnet attack detection in IoMT," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 512-522, March.
    2. Sharfah Ratibah Tuan Mat & Mohd Faizal Ab Razak & Mohd Nizam Mohmad Kahar & Juliza Mohamad Arif & Salwana Mohamad & Ahmad Firdaus, 2021. "Towards a systematic description of the field using bibliometric analysis: malware evolution," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 2013-2055, March.

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