Data security in Hadoop distributed file system

Shetty, Madhvaraj M.; Manjaiah, D. H.

doi:10.1109/icett.2016.7873697

Cited by 21 publications

(9 citation statements)

References 1 publication

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“…They realized that HDFS works well for files more extensive than the default blocks and poorly for files smaller than the standard blocks. Clubric et al [61]. The security of essential data, not accomplished by Kerberos, at an HDFS storage level.…”

Section: Literature Reviewmentioning

confidence: 99%

A Comprehensive Survey for Hadoop Distributed File System

Merceedi

Sabry²

2021

AJRCoS

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In the last few days, data and the internet have become increasingly growing, occurring in big data. For these problems, there are many software frameworks used to increase the performance of the distributed system. This software is used for available ample data storage. One of the most beneficial software frameworks used to utilize data in distributed systems is Hadoop. This software creates machine clustering and formatting the work between them. Hadoop consists of two major components: Hadoop Distributed File System (HDFS) and Map Reduce (MR). By Hadoop, we can process, count, and distribute each word in a large file and know the number of affecting for each of them. The HDFS is designed to effectively store and transmit colossal data sets to high-bandwidth user applications. The differences between this and other file systems provided are relevant. HDFS is intended for low-cost hardware and is exceptionally tolerant to defects. Thousands of computers in a vast cluster both have directly associated storage functions and user programmers. The resource scales with demand while being cost-effective in all sizes by distributing storage and calculation through numerous servers. Depending on the above characteristics of the HDFS, many researchers worked in this field trying to enhance the performance and efficiency of the addressed file system to be one of the most active cloud systems. This paper offers an adequate study to review the essential investigations as a trend beneficial for researchers wishing to operate in such a system. The basic ideas and features of the investigated experiments were taken into account to have a robust comparison, which simplifies the selection for future researchers in this subject. According to many authors, this paper will explain what Hadoop is and its architectures, how it works, and its performance analysis in a distributed systems. In addition, assessing each Writing and compare with each other.

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Section: Literature Reviewmentioning

confidence: 99%

A Comprehensive Survey for Hadoop Distributed File System

Merceedi

Sabry²

2021

AJRCoS

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“…The main machine is running it. It records where the data is located in the cluster and remembers where each file is located in the file system [7]. To make specific operations on the data, the Name Node interacts with the client apps.…”

Section: A Name Nodementioning

confidence: 99%

An Efficient Approach for Bigdata Security Based on Hadoop System Using Cryptographic Techniques

Gattoju¹,

Nagalakshmi²

2021

INDJCSE

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When relational database systems could no longer keep up with the huge amounts of unstructured data created by organizations, social media, and all other data-generating sources, big data came into being. The amount of data being added every day, together with Hadoop, makes for an urgent and growing need for more data processing solutions. The MapReduce programming model is one common approach for processing and handling huge amounts of data, especially when used to big data research. As HDFS, a distributed, scalable, and portable file system constructed in Java for the Hadoop architecture, is already useful, it is noteworthy that it is built using Java technology. This computing environment suffers from two issues. First, when intruders access the system, they can steal or corrupt the data stored in the system. The AES encryption mechanism has been implemented in HDFS to safeguard the security of data stored in HDFS. Some data saved in HDFS can be secured with the application of AES encryption technique. I conducted an extensive research on security challenges around large data in the context of Hadoop, along with numerous solutions and technologies utilized to secure it.

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“…Thus, for encryption and decryption, AES encryption/decryption classes are added. Complete two HDFS-RSA and HDFS matching integrations (Shetty and Manjaiah, 2016) applied as some differing kinds of extensions of HDFS. Analyses confirmed a suitable overhead for reading operations and significant overhead for writing operations (Yang et al, September 9-11, 2013, pp.…”

Section: Introductionmentioning

confidence: 99%

Enhancing Approach for Information Security in Hadoop

2020

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Developing a confident Hadoop essentially a cloud computing is an essential challenge as the cloud. The protection policy can be utilized during various cloud services such as Platform as a Service (PaaS), Infrastructure as a Service (IaaS), and Software as a Service (SaaS) and also can support most requirements in cloud computing. This event motivates the need of a policy which will control these challenges. Hadoop may be a used policy recommended to beat this big data problem which usually utilizes MapReduce design to arrange huge amounts of information of the cloud system. Hadoop has no policy to ensure the privacy and protection of the files saved within the Hadoop Distributed File System (HDFS). Within the cloud, the safety of sensitive data may be a significant problem within which encryption schemes play an avital rule. This paper proposes a hybrid method between pair well-known asymmetric key cryptosystems (RSA and Rabin) to cipher the files saved in HDFS. Therefore, before storing data in HDFS, the proposed cryptosystem is employed to cipher the information. In the proposed system, the user of the cloud might upload files in two ways, secure or non-secure. The hybrid method presents more powerful computational complexity and smaller latency as compared to the RSA cryptosystem alone.

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Data security in Hadoop distributed file system

Cited by 21 publications

References 1 publication

A Comprehensive Survey for Hadoop Distributed File System

A Comprehensive Survey for Hadoop Distributed File System

An Efficient Approach for Bigdata Security Based on Hadoop System Using Cryptographic Techniques

Enhancing Approach for Information Security in Hadoop

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