An Overview of Big Data Security With Hadoop Framework

Web Services ◽  
2019 ◽  
pp. 13-24
Author(s):  
Jaya Singh ◽  
Ashish Maruti Gimekar ◽  
S. Venkatesan
Keyword(s):  
Big Data ◽  
Data Security ◽  
High Volume ◽  
Digital Data ◽  
Sensitive Data ◽  
Privacy And Security ◽  
Traditional System ◽  
Security Issues ◽  
Security Challenges ◽  
Almost All

Big Data is a very huge volume of data which is beyond the storage capacity and processing capability of traditional system. The volume of data is increasing at exponential rate. Therefore, there is the need of such mechanism to store and process such high volume of data. The impressiveness of the Big data lies with its major applicability to almost all industries. Therefore, it represents both, the tremendous opportunities and complex challenges. Such omnipotent eminence leads to the privacy and security related challenges to the big data. Nowadays, security of big data is mainly focused by every organization because it contains a lot of sensitive data and useful information for taking decisions. The hostile nature of digital data itself has certain inherited security challenges. The aim of Big data security is to identify security issues and to find the better solution for handling security challenges. The observation and analysis of different security mechanism related to the issues of big data and their solutions are focused in this chapter.

An Overview of Big Data Security with Hadoop Framework

2016 ◽  
pp. 165-181
Author(s):  
Jaya Singh ◽  
Ashish Maruti Gimekar ◽  
S. Venkatesan
Keyword(s):  
Big Data ◽  
Data Security ◽  
High Volume ◽  
Digital Data ◽  
Sensitive Data ◽  
Privacy And Security ◽  
Traditional System ◽  
Security Issues ◽  
Security Challenges ◽  
Almost All

Big Data is a very huge volume of data which is beyond the storage capacity and processing capability of traditional system. The volume of data is increasing at exponential rate. Therefore, there is the need of such mechanism to store and process such high volume of data. The impressiveness of the Big data lies with its major applicability to almost all industries. Therefore, it represents both, the tremendous opportunities and complex challenges. Such omnipotent eminence leads to the privacy and security related challenges to the big data. Nowadays, security of big data is mainly focused by every organization because it contains a lot of sensitive data and useful information for taking decisions. The hostile nature of digital data itself has certain inherited security challenges. The aim of Big data security is to identify security issues and to find the better solution for handling security challenges. The observation and analysis of different security mechanism related to the issues of big data and their solutions are focused in this chapter.

scholarly journals Authorization of Data In Hadoop Using Apache Sentry

2018 ◽  
Vol 7 (3.6) ◽  
pp. 234 ◽  
Author(s):  
N Sirisha ◽  
K V.D. Kiran
Keyword(s):  
Big Data ◽  
Data Security ◽  
Data Encryption ◽  
Security Model ◽  
Huge Amount ◽  
Sensitive Data ◽  
Major Drawback ◽  
Security Issues ◽  
On Demand ◽  
Increasing Trend

Big Data has become more popular, as it can provide on-demand, reliable and flexible services to users such as storage and its processing. The data security has become a major issue in the Big data. The open source HDFS software is used to store huge amount of data with high throughput and fault tolerance and Map Reduce is used for its computations and processing. However, it is a significant target in the Hadoop system, security model was not designed and became the major drawback of Hadoop software. In terms of storage, meta data security, sensitive data  and also the data security will be an serious issue in HDFS. With the importance of Hadoop in today's enterprises, there is also an increasing trend in providing a high security features in enterprises. Over recent years, only some level of security in Hadoop such as Kerberos and Transparent Data Encryption(TDE),Encryption techniques, hash techniques are shown for Hadoop. This paper, shows the efforts that are made to present Hadoop Authorization security issues using Apache Sentry in HDFS. 

Solution to Big Data Security Issues

2021 ◽  
pp. 67-74
Author(s):  
Prashant Srivastava ◽  
Niraj Kumar Tiwari ◽  
Ali Abbas
Keyword(s):  
Big Data ◽  
Data Security ◽  
Data System ◽  
Distributed File System ◽  
Security Model ◽  
End User ◽  
Privacy And Security ◽  
Security Issues ◽  
Multiple Phase ◽  
New Challenges

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.

scholarly journals Privacy and Security Issues in Online Social Networks

2018 ◽  
Vol 10 (12) ◽  
pp. 114 ◽  
Author(s):  
Shaukat Ali ◽  
Naveed Islam ◽  
Azhar Rauf ◽  
Ikram Din ◽  
Mohsen Guizani ◽  
...  
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Virtual Communities ◽  
Service Providers ◽  
Security And Privacy ◽  
Security Issue ◽  
Sensitive Data ◽  
Privacy And Security ◽  
Security Issues ◽  
Social Sphere

The advent of online social networks (OSN) has transformed a common passive reader into a content contributor. It has allowed users to share information and exchange opinions, and also express themselves in online virtual communities to interact with other users of similar interests. However, OSN have turned the social sphere of users into the commercial sphere. This should create a privacy and security issue for OSN users. OSN service providers collect the private and sensitive data of their customers that can be misused by data collectors, third parties, or by unauthorized users. In this paper, common security and privacy issues are explained along with recommendations to OSN users to protect themselves from these issues whenever they use social media.

scholarly journals Is Big Data Security Essential for Students to Understand?

2020 ◽  
Vol 11 (2) ◽  
pp. 161-170
Author(s):  
Rochman Hadi Mustofa
Keyword(s):  
Big Data ◽  
Undergraduate Students ◽  
Data Security ◽  
Personal Data ◽  
Digital Data ◽  
Security And Privacy ◽  
Group Discussions ◽  
Technology Applications ◽  
Digital Payments ◽  
Financial Technology

AbstractBig Data has become a significant concern of the world, along with the era of digital transformation. However, there are still many young people, especially in developing countries, who are not yet aware of the security of their big data, especially personal data. Misuse of information from big data often results in violations of privacy, security, and cybercrime. This study aims to determine how aware of the younger generation of security and privacy of their big data. Data were collected qualitatively by interviews and focus group discussions (FGD) from. Respondents were undergraduate students who used social media and financial technology applications such as online shopping, digital payments, digital wallet and hotel/transportation booking applications. The results showed that students were not aware enough and understood the security or privacy of their digital data, and some respondents even gave personal data to potentially scam sites. Most students are not careful in providing big data information because they are not aware of the risks behind it, socialization is needed in the future as a step to prevent potential data theft.

Big Data

2020 ◽  
pp. 24-65
Author(s):  
P. Lalitha Surya Kumari
Keyword(s):  
Big Data ◽  
Life Cycle ◽  
Data Collection ◽  
Operating Systems ◽  
Data Security ◽  
Map Reduce ◽  
Security Issues ◽  
Big Data Applications

This chapter gives information about the most important aspects in how computing infrastructures should be configured and intelligently managed to fulfill the most notably security aspects required by big data applications. Big data is one area where we can store, extract, and process a large amount of data. All these data are very often unstructured. Using big data, security functions are required to work over the heterogeneous composition of diverse hardware, operating systems, and network domains. A clearly defined security boundary like firewalls and demilitarized zones (DMZs), conventional security solutions, are not effective for big data as it expands with the help of public clouds. This chapter discusses the different concepts like characteristics, risks, life cycle, and data collection of big data, map reduce components, issues and challenges in big data, cloud secure alliance, approaches to solve security issues, introduction of cybercrime, YARN, and Hadoop components.

Impact of Big Data on Security

2018 ◽  
pp. 326-350
Author(s):  
Kasarapu Ramani
Keyword(s):  
Big Data ◽  
Defense Mechanisms ◽  
Security And Privacy ◽  
End User ◽  
Sensitive Data ◽  
Insider Threats ◽  
Security Issues ◽  
Commercial Importance ◽  
Multi Level ◽  
Access Privileges

Big data has great commercial importance to major businesses, but security and privacy challenges are also daunting this storage, processing, and communication. Big data encapsulate organizations' most important and sensitive data with multi-level complex implementation. The challenge for any organization is securing access to the data while allowing end user to extract valuable insights. Unregulated access privileges to the big data leads to loss or theft of valuable and sensitive. Privilege escalation leads to insider threats. Also, the computing architecture of big data is not focusing on session recording; therefore, it is becoming a challenge to identify potential security issues and to take remedial and mitigation mechanisms. Therefore, various big data security issues and their defense mechanisms are discussed in this chapter.

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