Research on Information Security and Privacy of Libraries in Big Data Era

2014 ◽  
Vol 1049-1050 ◽  
pp. 1934-1937 ◽  
Author(s):  
Ning Ning Sun ◽  
Li Hua Ma
Keyword(s):  
Big Data ◽  
Information Security ◽  
Data Privacy ◽  
Security And Privacy ◽  
Research Focus ◽  
Security And Protection ◽  
Vital Importance

In the big data era, the security and protection of users’ privacy have become a research focus of libraries, especially the protection for users’ data privacy is of vital importance. This paper analyzes and discusses the features of libraries in big data era, discusses the influence of big data era on information security of libraries, and proposes big data-related scientific problems which shall be solved in terms of information security.

Security and Privacy in Big Data Computing

2020 ◽  
pp. 236-256
Author(s):  
Kiritkumar J. Modi ◽  
Prachi Devangbhai Shah ◽  
Zalak Prajapati
Keyword(s):  
Big Data ◽  
Data Privacy ◽  
Security And Privacy ◽  
Comprehensive Overview ◽  
Privacy And Security ◽  
Cloud Data ◽  
Big Data Privacy ◽  
Cloud Data Storage ◽  
Type Data ◽  
Big Data Computing

The rapid growth of digitization in the present era leads to an exponential increase of information which demands the need of a Big Data paradigm. Big Data denotes complex, unstructured, massive, heterogeneous type data. The Big Data is essential to the success in many applications; however, it has a major setback regarding security and privacy issues. These issues arise because the Big Data is scattered over a distributed system by various users. The security of Big Data relates to all the solutions and measures to prevent the data from threats and malicious activities. Privacy prevails when it comes to processing personal data, while security means protecting information assets from unauthorized access. The existence of cloud computing and cloud data storage have been predecessor and conciliator of emergence of Big Data computing. This article highlights open issues related to traditional techniques of Big Data privacy and security. Moreover, it also illustrates a comprehensive overview of possible security techniques and future directions addressing Big Data privacy and security issues.

scholarly journals Information Security in Big Data: Privacy and Data Mining

IEEE Access ◽  
2014 ◽  
Vol 2 ◽  
pp. 1149-1176 ◽  
Author(s):  
Lei Xu ◽  
Chunxiao Jiang ◽  
Jian Wang ◽  
Jian Yuan ◽  
Yong Ren
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Information Security ◽  
Data Privacy ◽  
Big Data Privacy

Differential Privacy Approach for Big Data Privacy in Healthcare

2017 ◽  
pp. 191-213 ◽  
Author(s):  
Marmar Moussa ◽  
Steven A. Demurjian
Keyword(s):  
Big Data ◽  
Data Sharing ◽  
Data Privacy ◽  
Large Scale ◽  
Differential Privacy ◽  
Security And Privacy ◽  
Instrumental Case Study ◽  
Large Scale Data ◽  
Private Data

This chapter presents a survey of the most important security and privacy issues related to large-scale data sharing and mining in big data with focus on differential privacy as a promising approach for achieving privacy especially in statistical databases often used in healthcare. A case study is presented utilizing differential privacy in healthcare domain, the chapter analyzes and compares the major differentially private data release strategies and noise mechanisms such as the Laplace and the exponential mechanisms. The background section discusses several security and privacy approaches in big data including authentication and encryption protocols, and privacy preserving techniques such as k-anonymity. Next, the chapter introduces the differential privacy concepts used in the interactive and non-interactive data sharing models and the various noise mechanisms used. An instrumental case study is then presented to examine the effect of applying differential privacy in analytics. The chapter then explores the future trends and finally, provides a conclusion.

Blockchain-Based Data Market (BCBDM) Framework for Security and Privacy

2021 ◽  
pp. 186-205
Author(s):  
Shailesh Pancham Khapre ◽  
Chandramohan Dhasarathan ◽  
Puviyarasi T. ◽  
Sam Goundar
Keyword(s):  
Big Data ◽  
Data Sharing ◽  
Data Storage ◽  
Data Privacy ◽  
Security And Privacy ◽  
Research Progress ◽  
Distributed Data ◽  
Distributed Data Storage ◽  
Data Market ◽  
Privacy Issues

In the internet era, incalculable data is generated every day. In the process of data sharing, complex issues such as data privacy and ownership are emerging. Blockchain is a decentralized distributed data storage technology. The introduction of blockchain can eliminate the disadvantages of the centralized data market, but at the same time, distributed data markets have created security and privacy issues. It summarizes the industry status and research progress of the domestic and foreign big data trading markets and refines the nature of the blockchain-based big data sharing and circulation platform. Based on these properties, a blockchain-based data market (BCBDM) framework is proposed, and the security and privacy issues as well as corresponding solutions in this framework are analyzed and discussed. Based on this framework, a data market testing system was implemented, and the feasibility and security of the framework were confirmed.

Big Data, Privacy, and Healthcare

2019 ◽  
pp. 162-175
Author(s):  
Nirav Bhatt ◽  
Amit Thakkar
Keyword(s):  
Big Data ◽  
Data Storage ◽  
Data Privacy ◽  
Rapid Development ◽  
Big Data Analytics ◽  
Disease Diagnosis ◽  
Security And Privacy ◽  
Healthcare Industry ◽  
Storage And Retrieval ◽  
Healthcare Data

In the era of big data, large amounts of data are generated from different areas like education, business, stock market, healthcare, etc. Most of the available data from these areas are unstructured, which is large and complex. As healthcare industries become value-based from volume-based, there is a need to have specialized tools and methods to handle it. The traditional methods for data storage and retrieval can be used when data is structured in nature. Big data analytics provide technologies to store large amounts of complex healthcare data. It is believed that there is an enormous opportunity to improve lives by applying big data in the healthcare industry. No industry counts more than healthcare as it is a matter of life and death. Due to rapid development of big data tools and technologies, it is possible to improve disease diagnosis more efficiently than ever before, but security and privacy are two major issues when dealing with big data in the healthcare industry.

Differential Privacy Approach for Big Data Privacy in Healthcare

Web Services ◽  
2019 ◽  
pp. 1623-1645
Author(s):  
Marmar Moussa ◽  
Steven A. Demurjian
Keyword(s):  
Big Data ◽  
Data Sharing ◽  
Data Privacy ◽  
Large Scale ◽  
Differential Privacy ◽  
Security And Privacy ◽  
Instrumental Case Study ◽  
Large Scale Data ◽  
Private Data

This chapter presents a survey of the most important security and privacy issues related to large-scale data sharing and mining in big data with focus on differential privacy as a promising approach for achieving privacy especially in statistical databases often used in healthcare. A case study is presented utilizing differential privacy in healthcare domain, the chapter analyzes and compares the major differentially private data release strategies and noise mechanisms such as the Laplace and the exponential mechanisms. The background section discusses several security and privacy approaches in big data including authentication and encryption protocols, and privacy preserving techniques such as k-anonymity. Next, the chapter introduces the differential privacy concepts used in the interactive and non-interactive data sharing models and the various noise mechanisms used. An instrumental case study is then presented to examine the effect of applying differential privacy in analytics. The chapter then explores the future trends and finally, provides a conclusion.

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