Solution to Big Data Security Issues

Solution to Big Data Security Issues

Prashant Srivastava, Niraj Kumar Tiwari, Ali Abbas
Copyright: © 2021 |Pages: 8
DOI: 10.4018/978-1-7998-3327-7.ch005
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Abstract

Organizations now have knowledge of big data significance, but new challenges stand up with new inventions. These challenges are not only limited to the three Vs of big data, but also to privacy and security. Attacks on big data system ranges from DDoS to information theft, ransomware to end user level security. So implementing security to big data system is a multiple phase-based ongoing process in which security is imposed from perimeter level to distributed file system security, cloud security to data security, storage to data mining security, and so on. In this chapter, the authors have identified some key vulnerable point related to big data and also proposed a security model.
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Security Issue To Big Data

As discuss by Ardagna et al. (2014) and Moreno et al. (2018), now a day’s big data is a first choice of attackers. Organizations are accepting big data technologies, by using its great analytics tools helps in decision-making, identifying prospects, and enhance the performance. But with the enormous consumption and increased usage of data, rises security concern of the big data. At last, the adoption of the big data create a question marks for many enterprises: how can you control big data’s potential while effectively mitigating big data security risks?

The authors identified some security issue of big data they are as follows.

Distributed Frameworks

For early result of the data, analysis should be done in a very faster way so all big data implementations actually distribute the huge processing jobs among different processing nodes which leads the security concern like all the nodes should have proper security policy. Hadoop is an example of open source software for distributed system for big data analysis so Hadoop security procedures must be installed and updated. The attackers can use the mapper for Map Reduce to show improper values or key pairs, for destruction. Distributed system may decrease the outstanding burden on a framework, yet in the long run more systems mean more security issues.

Non-Relational Databases

Till now the databases available for data management and storage follows relational database management system concepts and uses tablular structures which is nearly not applicable in case of big data. Big data is highly diversified and scalable in nature. Non-Relational databases or NoSQL databases are designed in such a way that they do not follow the tabular structure, and follows storage models which is basically data type based which results Non-relational databases as more scalable and flexible. NoSQL has its own common security protocols so the organization who are implementing the Big Data system must set up their database in their own secure environment with additional security measures.

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