Big Data Security on Cloud Servers Using Data Fragmentation Technique and NoSQL Database

Abstract Cloud computing is a new way of computing and storage. Users do not need to master professional skills, but can enjoy convenient network services as long as they pay according to their own needs. When we use cloud services, we need to upload data to cloud servers. As the cloud is an open environment, it is easy for attackers to use cloud computing to conduct excessive computational analysis on big data, which is bound to infringe on others’ privacy. In this process, we inevitably face the challenge of data security. How to ensure data privacy security in the cloud environment has become an urgent problem to be solved. This paper studies the big data security privacy protection based on cloud computing platform. This paper starts from two aspects: implicit security mechanism and display security mechanism (encryption mechanism), so as to protect the security privacy of cloud big data platform in data storage and data computing processing.

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A Big Data Security using Data Masking Methods

Indonesian Journal of Electrical Engineering and Computer Science ◽

10.11591/ijeecs.v7.i2.pp449-456 ◽

2017 ◽

Vol 7 (2) ◽

pp. 449 ◽

Cited By ~ 2

Author(s):

Archana R A ◽

Ravindra S Hegadi ◽

Manjunath T N

Keyword(s):

Big Data ◽

Data Management ◽

Data Security ◽

Service Providers ◽

Data Sets ◽

Management Service ◽

Data Set ◽

Original Dataset ◽

Data Masking ◽

Using Data

<p>Due to Internet of things and social media platforms, raw data is getting generated from systems around us in three sixty degree with respect to time, volume and type. Social networking is increasing rapidly to exploit business advertisements as business demands. In this regard there are many challenges for data management service providers, security is one among them. Data management service providers need to ensure security for their privileged customers in providing accurate and valid data. Since underlying transactional data have varying data characteristics such huge volume, variety and complexity, there is an essence of deploying such data sets on to the big data platforms which can handle structured, semi-structured and un-structured data sets. In this regard we propose a data masking technique for big data security. Data masking ensures proxy of original dataset with a different dataset which is not real but looks realistic. The given data set is masked using modulus operator and the concept of keys. Our experiment advocates enhanced modulus based data masking is better with respect to execution time and space utilization for larger data sets when compared to modulus based data masking. This work will help big data developers, quality analysts in the business domains and provides confidence for end-users in providing data security.</p>

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Big Data Security Challenges and Solution of Distributed Computing in Hadoop Environment: A Security Framework

Recent Advances in Computer Science and Communications ◽

10.2174/2213275912666190822095422 ◽

2020 ◽

Vol 13 (4) ◽

pp. 790-797

Author(s):

Gurjit Singh Bhathal ◽

Amardeep Singh Dhiman

Keyword(s):

Big Data ◽

Data Security ◽

Data Sets ◽

Security Framework ◽

Hadoop Distributed File System ◽

Current Scenario ◽

Hadoop Cluster ◽

Ciphertext Policy ◽

In Transit ◽

Hadoop Framework

Background: In current scenario of internet, large amounts of data are generated and processed. Hadoop framework is widely used to store and process big data in a highly distributed manner. It is argued that Hadoop Framework is not mature enough to deal with the current cyberattacks on the data. Objective: The main objective of the proposed work is to provide a complete security approach comprising of authorisation and authentication for the user and the Hadoop cluster nodes and to secure the data at rest as well as in transit. Methods: The proposed algorithm uses Kerberos network authentication protocol for authorisation and authentication and to validate the users and the cluster nodes. The Ciphertext-Policy Attribute- Based Encryption (CP-ABE) is used for data at rest and data in transit. User encrypts the file with their own set of attributes and stores on Hadoop Distributed File System. Only intended users can decrypt that file with matching parameters. Results: The proposed algorithm was implemented with data sets of different sizes. The data was processed with and without encryption. The results show little difference in processing time. The performance was affected in range of 0.8% to 3.1%, which includes impact of other factors also, like system configuration, the number of parallel jobs running and virtual environment. Conclusion: The solutions available for handling the big data security problems faced in Hadoop framework are inefficient or incomplete. A complete security framework is proposed for Hadoop Environment. The solution is experimentally proven to have little effect on the performance of the system for datasets of different sizes.

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Comparative Study of Cryptography for Cloud Computing for Data Security

Recent Advances in Computer Science and Communications ◽

10.2174/2666255813666190911114909 ◽

2019 ◽

Vol 13 ◽

Author(s):

Priya Mathur ◽

Amit Kumar Gupta ◽

Prateek Vashishtha

Keyword(s):

Cloud Computing ◽

Data Security ◽

Elliptic Curve Cryptography ◽

Plain Text ◽

Hybrid Encryption ◽

Cipher Text ◽

Business Applications ◽

Computing Grid ◽

Cloud Servers ◽

Client Side

Cloud computing is an emerging technique by which anyone can access the applications as utilities over the internet. Cloud computing is the technology which comprises of all the characteristics of the technologies like distributed computing, grid computing, and ubiquitous computing. Cloud computing allows everyone to create, to configure as well as to customize the business applications online. Cryptography is the technique which is use to convert the plain text into cipher text using various encryption techniques. The art and science used to introduce the secrecy in the information security in order to secure the messages is defined as cryptography. In this paper we are going to review few latest Cryptographic algorithms which are used to enhance the security of the data on the cloud servers. We are comparing Short Range Natural Number Modified RSA (SRNN), Elliptic Curve Cryptography Algorithm, Client Side Encryption Technique and Hybrid Encryption Technique to secure the data in cloud.

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