<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Apache Hadoop answers the quest of handling Bigdata for most organizations. It offers distributed storage and data analysis via Hadoop Distributed File System (HDFS) and Map-Reduce frameworks. Hadoop depends on third-party security providers like Kerberos for its security requirements. Kerberos by itself comes with many security loopholes like Single point of Failure (SoF), Dictionary Attacks, Time Synchronization and Insider Attacks. This paper suggests a solution that aims to eradicate the security issues in the Hadoop Cluster with a focus on Dictionary Attacks and Single Point of Failure. The scheme roots on Secure Remote Password Protocol, Blockchain Technology and Threshold Cryptography. Practical Byzantine Fault Tolerance mechanism (PBFT) is deployed at the blockchain as the consensus mechanism. The proposed scheme outperforms many of the existing schemes in terms of computational overhead and storage requirements without compromising the security level offered by the system. Riverbed Modeller (AE) Simulation results strengthen the aforesaid claims.</p>
</abstract>

Apache Hadoop answers the quest of handling Bigdata for most organizations. It offers distributed storage and data analysis via Hadoop Distributed File System (HDFS) and Map-Reduce frameworks. Hadoop depends on third-party security providers like Kerberos for its security requirements. Kerberos by itself comes with many security loopholes like Single point of Failure (SoF), Dictionary Attacks, Time Synchronization and Insider Attacks. This paper suggests a solution that aims to eradicate the security issues in the Hadoop Cluster with a focus on Dictionary Attacks and Single Point of Failure. The scheme roots on Secure Remote Password Protocol, Blockchain Technology and Threshold Cryptography. Practical Byzantine Fault Tolerance mechanism (PBFT) is deployed at the blockchain as the consensus mechanism. The proposed scheme outperforms many of the existing schemes in terms of computational overhead and storage requirements without compromising the security level offered by the system. Riverbed Modeller (AE) Simulation results strengthen the aforesaid claims.

A Three-Tier Authentication Scheme for Kerberized Hadoop Environment

Cybernetics and Information Technologies

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"A Three-Tier Authentication Scheme for Kerberized Hadoop Environment"}

Apache Hadoop answers the quest of handling Bigdata for most organizations. It offers distributed storage and data analysis via Hadoop Distributed File System...

A Three-Tier Authentication Scheme for Kerberized Hadoop Environment

Publié en ligne: 09 déc. 2021

Pages: 119 - 136

Reçu: 14 juin 2021

Accepté: 08 nov. 2021

DOI: https://doi.org/10.2478/cait-2021-0046

Mots clés
Apache hadoop, authentication, bigdata, blockchain, Kerberos

© 2021 M. Hena et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

A Three-Tier Authentication Scheme for Kerberized Hadoop Environment

Publié en ligne: 09 déc. 2021

Pages: 119 - 136

Reçu: 14 juin 2021

Accepté: 08 nov. 2021

DOI: https://doi.org/10.2478/cait-2021-0046

Mots clésApache hadoop, authentication, bigdata, blockchain, Kerberos

© 2021 M. Hena et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Mots clés
Apache hadoop, authentication, bigdata, blockchain, Kerberos