Big Data-Driven Privacy and Security Issues and Challenges

2021 ◽  
pp. 17-32
Author(s):  
Selvakumar Samuel ◽  
Kesava Pillai Rajadorai ◽  
Vazeerudeen Abdul Hameed
Keyword(s):  
Big Data ◽  
Data Driven ◽  
Privacy And Security ◽  
Security Issues

scholarly journals PROTECTION OF PRIVACY AND PERSONAL DATA IN THE BIG DATA ENVIRONMENT OF SMART CITIES

2021 ◽  
Vol XLVI-4/W5-2021 ◽  
pp. 181-186
Author(s):  
A. Denker
Keyword(s):  
Big Data ◽  
Smart City ◽  
Personal Information ◽  
Smart Cities ◽  
Personal Data ◽  
Privacy And Security ◽  
Personal Data Protection ◽  
Security Issues ◽  
Data Environment ◽  
Bifocal Lenses

Abstract. The project of smart cities has emerged as a response to the challenges of twenty-first- century urbanization. Solutions to the fundamental conundrum of cities revolving around efficiency, convenience and security keep being sought by leveraging technology. Notwithstanding all the conveniences furnished by a smart city to all the citizens, privacy of a citizen is intertwined with the benefits of a smart city. The development processes which overlook privacy and security issues have left many of the smart city applications vulnerable to non-conventional security threats and susceptible to numerous privacy and personal data spillage risks. Among the challenges the smart city initiatives encounter, the emergence of the smartphone-big data-the cloud coalescence is perhaps the greatest, from the viewpoint of privacy and personal data protection. As our cities are getting digitalized, information comprising citizens' behavior, choices, and mobility, as well as their personal assets are shared over smartphone-big data-the cloud coalescences, thereby expanding cyber-threat surface and creating different security concerns. This coalescence refers to the practices of creating and analyzing vast sets of data, which comprise personal information. In this paper, the protection of privacy and personal data issues in the big data environment of smart cities are viewed through bifocal lenses, focusing on social and technical aspects. The protection of personal data and privacy in smart city enterprises is treated as a socio-technological operation where various actors and factors undertake different tasks. The article concludes by calling for novel developments, conceptual and practical changes both in technological and social realms.

scholarly journals Privacy and Security issues in Big Data : A Case Study of Characteristics, Challenges, and Solution

2020 ◽  
Vol 175 (12) ◽  
pp. 29-34
Author(s):  
Parth Sabhadiya ◽  
Nayankumar Sorathiya ◽  
Vaikunth Desai
Keyword(s):  
Big Data ◽  
Privacy And Security ◽  
Security Issues

A Review of Security Challenges in Cloud Storage of Big Data

2019 ◽  
pp. 1440-1459
Author(s):  
Sara Usmani ◽  
Faiza Rehman ◽  
Sajid Umair ◽  
Safdar Abbas Khan
Keyword(s):  
Information Technology ◽  
Cloud Computing ◽  
Big Data ◽  
Data Storage ◽  
Cloud Storage ◽  
Personal Data ◽  
Security And Privacy ◽  
Privacy And Security ◽  
Security Issues ◽  
The People

The novel advances in the field of Information Technology presented the people pleasure, luxuries and ease. One of the latest expansions in the Information Technology (IT) industry is Cloud Computing, a technology that uses the internet for storage and access of data. It is also known as on-demand computing. The end user can access personal data and applications anywhere any time with a device having internet. Cloud Computing has gained an enormous attention but it results in the issues of data security and privacy as the data is scattered on different machines in different places across the globe which is a serious threat to the technology. It has many advantages like flexibility, efficiency and scalability but many of the companies are hesitant to invest in it due to privacy concerns. In this chapter, the objective is to review the privacy and security issues in cloud storage of Big Data and to enhance the security in cloud environment so that end users can enjoy a trustworthy and reliable data storage and access.

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 Big Data Warehouse for Healthcare-Sensitive Data Applications

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2353
Author(s):  
Arsalan Shahid ◽  
Thien-An Ngoc Nguyen ◽  
M-Tahar Kechadi
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Childhood Obesity ◽  
Access Control ◽  
Data Warehouse ◽  
System Architecture ◽  
Data Access ◽  
Data Representation ◽  
Data Driven ◽  
Privacy And Security

Obesity is a major public health problem worldwide, and the prevalence of childhood obesity is of particular concern. Effective interventions for preventing and treating childhood obesity aim to change behaviour and exposure at the individual, community, and societal levels. However, monitoring and evaluating such changes is very challenging. The EU Horizon 2020 project “Big Data against Childhood Obesity (BigO)” aims at gathering large-scale data from a large number of children using different sensor technologies to create comprehensive obesity prevalence models for data-driven predictions about specific policies on a community. It further provides real-time monitoring of the population responses, supported by meaningful real-time data analysis and visualisations. Since BigO involves monitoring and storing of personal data related to the behaviours of a potentially vulnerable population, the data representation, security, and access control are crucial. In this paper, we briefly present the BigO system architecture and focus on the necessary components of the system that deals with data access control, storage, anonymisation, and the corresponding interfaces with the rest of the system. We propose a three-layered data warehouse architecture: The back-end layer consists of a database management system for data collection, de-identification, and anonymisation of the original datasets. The role-based permissions and secured views are implemented in the access control layer. Lastly, the controller layer regulates the data access protocols for any data access and data analysis. We further present the data representation methods and the storage models considering the privacy and security mechanisms. The data privacy and security plans are devised based on the types of collected personal, the types of users, data storage, data transmission, and data analysis. We discuss in detail the challenges of privacy protection in this large distributed data-driven application and implement novel privacy-aware data analysis protocols to ensure that the proposed models guarantee the privacy and security of datasets. Finally, we present the BigO system architecture and its implementation that integrates privacy-aware protocols.

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.

A Review of Security Challenges in Cloud Storage of Big Data

2018 ◽  
pp. 175-195
Author(s):  
Sara Usmani ◽  
Faiza Rehman ◽  
Sajid Umair ◽  
Safdar Abbas Khan
Keyword(s):  
Information Technology ◽  
Cloud Computing ◽  
Big Data ◽  
Data Storage ◽  
Cloud Storage ◽  
Personal Data ◽  
Security And Privacy ◽  
Privacy And Security ◽  
Security Issues ◽  
The People

The novel advances in the field of Information Technology presented the people pleasure, luxuries and ease. One of the latest expansions in the Information Technology (IT) industry is Cloud Computing, a technology that uses the internet for storage and access of data. It is also known as on-demand computing. The end user can access personal data and applications anywhere any time with a device having internet. Cloud Computing has gained an enormous attention but it results in the issues of data security and privacy as the data is scattered on different machines in different places across the globe which is a serious threat to the technology. It has many advantages like flexibility, efficiency and scalability but many of the companies are hesitant to invest in it due to privacy concerns. In this chapter, the objective is to review the privacy and security issues in cloud storage of Big Data and to enhance the security in cloud environment so that end users can enjoy a trustworthy and reliable data storage and access.

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.

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