• DocumentCode
    263594
  • Title

    Automated Forensic Data Acquisition in the Cloud

  • Author

    Reichert, Zachary ; Richards, Katarina ; Yoshigoe, Kenji

  • Author_Institution
    Div. of Inf. Technol. & Sci., Champlain Coll., Burlington, VT, USA
  • fYear
    2014
  • fDate
    28-30 Oct. 2014
  • Firstpage
    725
  • Lastpage
    730
  • Abstract
    Movement of businesses and individuals to the cloud has posed many new complications for digital forensic investigators. This is due to a multi-tenant environment on cloud servers, chain of custody problems, globalization of data, and the inability of the Cloud Service Provider (CSP) to keep logs of everything within their network. This paper proposes a practical solution that can be implemented to mitigate the challenges with minimal to no CSP upkeep. Our model builds upon and adds to existing models and solutions including network monitoring for Infrastructure as a Service and snapshot capabilities to provide forensic evidence. We propose to utilize the automation of snapshots and an open-source tool, Google Rapid Response (GRR), set off by a hypervisor-based intrusion detection system in order to collect forensic evidence. Finally, we discuss the ideal implementation of our model and the future research direction.
  • Keywords
    cloud computing; data acquisition; digital forensics; CSP; GRR; Google Rapid Response; automated forensic data acquisition; cloud service provider; digital forensic investigators; hypervisor-based intrusion detection system; infrastructure as a service; network monitoring; open-source tool; Computational modeling; Databases; Forensics; Intrusion detection; Servers; Virtual machine monitors; Virtual machining; cloud forensics; automated snapshots; hypervisorbased intrusion detection systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mobile Ad Hoc and Sensor Systems (MASS), 2014 IEEE 11th International Conference on
  • Conference_Location
    Philadelphia, PA
  • Print_ISBN
    978-1-4799-6035-4
  • Type

    conf

  • DOI
    10.1109/MASS.2014.135
  • Filename
    7035772