Securing cloud by mitigating insider data theft attacks with decoy technology using Hadoop

  • Authors

    • K Vamsi Krishna
    • V Srikanth
    2018-05-29
    https://doi.org/10.14419/ijet.v7i2.31.13407
  • Data security, data access, malicious insider, decoy, intrusion detection, fog computing, user profiling, hadoop, cluster computing, multi-clouds, machine learning, naïve bayes, big data processing.

  • Cloud Computing has been intrinsically changing the way we utilize computers to keep and retrieve our personal & business data. With the advent of this emerging paradigm of computing, it arises the new security challenges. Existent cryptographic data security techniques i.e., encryption deteriorated in preventing data theft attacks once the key is compromised, especially those perpetrated by insiders. Cloud Security Alliance reckoned this threat as a significant danger of Cloud Computing. Although the majority of Cloud users are very much known of this risk, they are leftover with the only choice of trusting the cloud service provider, regards to their data protection. In this paper, we propose an alternate way to secure data on the cloud which is more efficient and secure by the concoction of user profile mapping using Hadoop framework and offensive decoy technology.

     

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  • How to Cite

    Vamsi Krishna, K., & Srikanth, V. (2018). Securing cloud by mitigating insider data theft attacks with decoy technology using Hadoop. International Journal of Engineering & Technology, 7(2.31), 101-105. https://doi.org/10.14419/ijet.v7i2.31.13407