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Explain cloud data Security challenges?
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The techniques for Cloud Data Security are as follows:

  1. Data Integrity and Privacy Protection:

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  • User desire a software environment that provides many useful tools to build cloud applications over large data sets.
  • The application software for MapReduce,BigTable,EC2, 3S,Hadoop,AWS, GAE and WebSphere2 users need some security and privacy protection software for using cloud.
  • Such software should offer features:

    • Special APIs for authenticating and sending e-mail using commercial accounts.
    • Fine grained access control to protect data integrity and deter intruders or hackers
    • Shared data sets protected from malicious alteration, deletion or copyright violation.
    • Ability to secure the ISP or cloud service provider from invading user’s privacy.
    • Personal firewall at user end to keep shared data from Java, JavaScript and ActiveX applet.
    • VPN channels between resource sites to secure transmission of critical data objects.

2.Data Coloring and Cloud Watermarking

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  • The system generates special colors for each data object.
  • Data coloring means labeling each data object by a unique color.
  • Differently colored data objects are distinguishable
  • The user identification is also colored to be matched with the data colors. This color matching process can be applied to implement different trust management events.
  • Cloud storage provides a process for the generation, embedding and extraction of the watermarks in colored objects.
  • The data coloring takes a minimal number of calculations to color or decolor the data object.

3.Data Lock-in Problem and Proactive Solution

  • Cloud computing moves both the computation and the data to the server clusters maintained by cloud service providers.
  • Once the data is moved into the cloud, users cannot easily extract their data and programs from cloud servers to run on another platform. This leads to a data lock-in problem.
  • Data lockin is attributed to two causes: lack of interoperability where each cloud vendor has its proprietary API that limits users to extract data once submitted and lack of application compatibility in most computing clouds expect users to write new applications from scratch, when they switch cloud platforms.
  • The solution to data lockin is the use of standardized cloud APIs. This requires building standardized virtual platforms that adhere to OVF, a platform-independent, efficient, extensible and open format for VMs. This will enable efficient, secure software distribution, facilitating the mobility of VMs.
  • Using OVF one can move data fom one application to another.
  • This will enhance QoS and enable cross cloud applications, allowing workload migration among data centers to user-specific storage.
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