Abstract
Big data (BD) handling is a vital task in today’s world where huge amount of data is circulated within a distributed network. To handle BD, Hadoop is being widely used by various organizations, as Hadoop supports both parallel processing and distributed computing over wide area networks. Hadoop clusters (HC) are widely accepted in the distributed and parallel computing frameworks for storing the BD because of its good scalability, tightly coupling among commodity hardware. Though data storage and processing can be handled well by HC, it does not provide data security which is inevitable where data may contain sensitive information. In HC Yet Another Resource Negotiator (YARN) and NameNode act as masters that provide resources for users and processes without authentication. All kinds of users in HC have the same level of accessing privileges which can be a threat to data security. HC completely depends on third-party security providers for satisfying various security requirements which in turn is a computational burden. This paper proposes a proprietary new security mechanism, implemented as Secure Authentication Interface (SAI) layer over HC. SAI provides user authentication, metadata security and access control all at a time. Compared to the existing mechanisms, SAI can provide security with less computational overhead.
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Balaraju, J., Prasada Rao, P.V.R.D. (2020). Innovative Secure Authentication Interface for Hadoop Cluster Using DNA Cryptography: A Practical Study. In: Reddy, V., Prasad, V., Wang, J., Reddy, K. (eds) Soft Computing and Signal Processing. ICSCSP 2019. Advances in Intelligent Systems and Computing, vol 1118. Springer, Singapore. https://doi.org/10.1007/978-981-15-2475-2_3
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DOI: https://doi.org/10.1007/978-981-15-2475-2_3
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