Comprehensive Survey on Hadoop Security

Martis, Maria; Pai, Namratha V.; Pragathi, R; Rakshatha, S.; Dixit, Sunanda

doi:10.1007/978-981-13-6001-5_17

Cited by 4 publications

(4 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…3 Department of Computer Science and Engineering, JNTUA , Anantapuramu, Andhra Pradesh, India. 4 JNTU Anantapur, Anantapuramu, Andhra Pradesh, India.…”

Section: Resultsmentioning

confidence: 99%

“…Many new services were contributed to Apache Hadoop framework after it became open source. The amount of security features were very less in Hadoop 1.0 and security features incorporated in Hadoop 2.0 were also inadequate [4]. In this section we will present the existing security features of Hadoop framework along with their limitations.…”

Section: Security Features In Hadoop and Its Limitationsmentioning

confidence: 99%

See 1 more Smart Citation

Sandbox security model for Hadoop file system

2020

View full text Add to dashboard Cite

Extensive usage of Internet based applications in day to day life has led to generation of huge amounts of data every minute. Apart from humans, data is generated by machines like sensors, satellite, CCTV etc. This huge collection of heterogeneous data is often referred as Big Data which can be processed to draw useful insights. Apache Hadoop has emerged has widely used open source software framework for Big Data Processing and it is a cluster of cooperative computers enabling distributed parallel processing. Hadoop Distributed File System is used to store data blocks replicated and spanned across different nodes. HDFS uses an AES based cryptographic techniques at block level which is transparent and end to end in nature. However cryptography provides security from unauthorized access to the data blocks, but a legitimate user can still harm the data. One such example was execution of malicious map reduce jar files by legitimate user which can harm the data in the HDFS. We developed a mechanism where every map reduce jar will be tested by our sandbox security to ensure the jar is not malicious and suspicious jar files are not allowed to process the data in the HDFS. This feature is not present in the existing Apache Hadoop framework and our work is made available in github for consideration and inclusion in the future versions of Apache Hadoop.

show abstract

“…3 Department of Computer Science and Engineering, JNTUA , Anantapuramu, Andhra Pradesh, India. 4 JNTU Anantapur, Anantapuramu, Andhra Pradesh, India.…”

Section: Resultsmentioning

confidence: 99%

Section: Security Features In Hadoop and Its Limitationsmentioning

confidence: 99%

Sandbox security model for Hadoop file system

2020

View full text Add to dashboard Cite

show abstract

“…The recent boom in the Bigdata technology demands secure computing platforms. As per a study conducted by (1), there exist many security loopholes in Apache Hadoop Systems. These include the absence of any strong encryption between the client and Hadoop Server and the data is stored in unencrypted format.…”

Section: Introductionmentioning

confidence: 97%

A Survey on Hadoop Security and Comparative Analysis on Authentication Frameworks in Hadoop Clusters

Hena¹,

Jeyanthi²

2022

ECS Trans.

View full text Add to dashboard Cite

This paper presents a survey on various security frameworks which aim to secure Hadoop clusters and the files stored there. Most of the Hadoop platforms rely on Kerberos Authentication Protocol for user authentication. It is known that Kerberos itself has some vulnerabilities like Password Guessing Attacks, Single Point of Failure, Insider Attacks, and Time Synchronization problems. A new authentication framework that can address most of the identified issues and is computationally feasible than other schemes is introduced in this paper. The proposed framework is based on Secure Remote Password Protocol (SRP), Threshold Cryptography, and Blockchain Technology. The system focus on eradicating Password Guessing Attacks and Single Point of Failure in Kerberos Enabled Hadoop Clusters. The analysis results strengthen the claim that the proposed scheme beats the others in terms of computational efficiency and feasibility while offering the same security features. The paper is concluded with directions for future work.

show abstract

“…Security overview [47], published by Cloudera, which provides services based on Hadoop, describes three security issues (i.e., authentication, encryption, and authorization). In addition, some studies [48][49][50] convey the meanings such as authentication, authorization, encryption, monitoring the system by expressing them such as access control, permission, data security at respite, data security internode communication, inspection, and classification. Therefore, the security requirements for a data processing platform of a C4I big data system could be organized into four categories: authentication, authorization, encryption, and security monitoring and audit.…”

mentioning

confidence: 99%

C4I System Security Architecture: A Perspective on Big Data Lifecycle in a Military Environment

Baek

Kim

2021

Sustainability

View full text Add to dashboard Cite

Although the defense field is also one of the key areas that use big data for security reasons, there is a lack of study that designs system frameworks and presents security requirements to implement big data in defense. However, we overcome the security matters by examining the battlefield environment and the system through the flow of data in the battlefield. As such, this research was conducted to apply big data in the defense domain, which is a unique field. In particular, a three-layered system framework was designed to apply big data in the C4I system, which collects, manages, and analyzes data generated from the battlefield, and the security measures required for each layer were developed. First, to enhance the general understanding of big data and the military environment, an overview of the C4I system, the characteristics of the 6V’s, and the five-phase big data lifecycle were described. While presenting a framework that divides the C4I system into three layers, the roles and components of each layer are described in detail, considering the big data lifecycle and system framework. A security architecture is finally proposed by specifying security requirements for each field in the three-layered C4I system. The proposed system framework and security architecture more accurately explain the unique nature of the military domain than those studied in healthcare, smart grids, and smart cities; development directions requiring further research are described.

show abstract

Comprehensive Survey on Hadoop Security

Cited by 4 publications

References 10 publications

Sandbox security model for Hadoop file system

Sandbox security model for Hadoop file system

A Survey on Hadoop Security and Comparative Analysis on Authentication Frameworks in Hadoop Clusters

C4I System Security Architecture: A Perspective on Big Data Lifecycle in a Military Environment

Contact Info

Product

Resources

About