Security and Privacy Challenges in Big Data

2021 ◽  
pp. 15-41
Author(s):  
Dharmpal Singh ◽  
Ira Nath ◽  
Pawan Kumar Singh
Keyword(s):  
Big Data ◽  
Data Protection ◽  
High Performance ◽  
Digital Transformation ◽  
Security And Privacy ◽  
Privacy And Security ◽  
Data Safety ◽  
Amount Of Information ◽  
Enormous Amount ◽  
Software Skills

Big data refers to enormous amount of information which may be in planned and unplanned form. The huge capacity of data creates impracticable situation to handle with conventional database and traditional software skills. Thousands of servers are needed for its processing purpose. Big data gathers and examines huge capacity of data from various resources to determine exceptional novel awareness and recognizing the technical and commercial circumstances. However, big data discloses the endeavor to several data safety threats. Various challenges are there to maintain the privacy and security in big data. Protection of confidential and susceptible data from attackers is a vital issue. Therefore, the goal of this chapter is to discuss how to maintain security in big data to keep your organization robust, operational, flexible, and high performance, preserving its digital transformation and obtaining the complete benefit of big data, which is safe and secure.

Security and Privacy Challenges in Big Data

2020 ◽  
pp. 97-124
Author(s):  
Dharmpal Singh ◽  
Ira Nath ◽  
Pawan Kumar Singh
Keyword(s):  
Big Data ◽  
Data Protection ◽  
High Performance ◽  
Digital Transformation ◽  
Security And Privacy ◽  
Privacy And Security ◽  
Data Safety ◽  
Amount Of Information ◽  
Enormous Amount ◽  
Software Skills

Big data refers to enormous amount of information which may be in planned and unplanned form. The huge capacity of data creates impracticable situation to handle with conventional database and traditional software skills. Thousands of servers are needed for its processing purpose. Big data gathers and examines huge capacity of data from various resources to determine exceptional novel awareness and recognizing the technical and commercial circumstances. However, big data discloses the endeavor to several data safety threats. Various challenges are there to maintain the privacy and security in big data. Protection of confidential and susceptible data from attackers is a vital issue. Therefore, the goal of this chapter is to discuss how to maintain security in big data to keep your organization robust, operational, flexible, and high performance, preserving its digital transformation and obtaining the complete benefit of big data, which is safe and secure.

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.

Nth Order Binary Encoding with Split-Protocol

2018 ◽  
Vol 5 (2) ◽  
pp. 95-118 ◽  
Author(s):  
Bharat S Rawal ◽  
Songjie Liang ◽  
Shiva Gautam ◽  
Harsha Kumara Kalutarage ◽  
P Vijayakumar
Keyword(s):  
Big Data ◽  
Data Compression ◽  
Data Storage ◽  
Network Traffic ◽  
Transmission Rate ◽  
Security And Privacy ◽  
Unique Combination ◽  
Privacy And Security ◽  
Binary Encoding ◽  
Data Explosion

To cope up with the Big Data explosion, the Nth Order Binary Encoding (NOBE) algorithm with the Split-protocol has been proposed. In the earlier papers, the application Split-protocol for security, reliability, availability, HPC have been demonstrated and implemented encoding. This technology will significantly reduce the network traffic, improve the transmission rate and augment the capacity for data storage. In addition to data compression, improving the privacy and security is an inherent benefit of the proposed method. It is possible to encode the data recursively up to N times and use a unique combination of NOBE's parameters to generate encryption keys for additional security and privacy for data on the flight or at a station. This paper describes the design and a preliminary demonstration of (NOBE) algorithm, serving as a foundation for application implementers. It also reports the outcomes of computable studies concerning the performance of the underlying implementation.

Protecting a new Achilles heel: the role of auditors within the practice of data protection

2019 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Matteo La Torre ◽  
Vida Lucia Botes ◽  
John Dumay ◽  
Elza Odendaal
Keyword(s):  
Big Data ◽  
Data Protection ◽  
Data Security ◽  
Security And Privacy ◽  
Legal Responsibility ◽  
Future Research ◽  
Content Type ◽  
Privacy Concerns ◽  
Digital Ecosystem

Purpose Privacy concerns and data security are changing the risks for businesses and organisations. This indicates that the accountability of all governance participants changes. This paper aims to investigate the role of external auditors within data protection practices and how their role is evolving due to the current digital ecosystem. Design/methodology/approach By surveying the literature, the authors embrace a practice-oriented perspective to explain how data protection practices emerge, exist and occur and examine the auditors’ position within data protection. Findings Auditors need to align their tasks to the purpose of data protection practices. Accordingly, in accessing and using data, auditors are required to engage moral judgements and follow ethical principles that go beyond their legal responsibility. Simultaneously, their accountability extends to data protection ends for instilling confidence that security risks are properly managed. Due to the changing technological conditions under, which auditors operate, the traditional auditors’ task of hearing and verifying extend to new phenomena that create risks for businesses. Thus, within data protection practices, auditors have the accountability to keep interested parties informed about data security and privacy risks, continue to transmit signals to users and instill confidence in businesses. Research limitations/implications The normative level of the study is a research limitation, which calls for future empirical research on how Big Data and data protection is reshaping accounting and auditing practices. Practical implications This paper provides auditing standard setters and practitioners with insights into the redefinitions of auditing practices in the era of Big Data. Social implications Recent privacy concerns at Facebook have sent warning signals across the world about the risks posed by in Big Data systems in terms of privacy, to those charged with governance of organisations. Auditors need to understand these privacy issues to better serve their clients. Originality/value This paper contributes to triggering discussions and future research on data protection and privacy in accounting and auditing research, which is an emerging, yet unresearched topic.

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.

scholarly journals Secure big data ecosystem architecture: challenges and solutions

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Memoona J. Anwar ◽  
Asif Q. Gill ◽  
Farookh K. Hussain ◽  
Muhammad Imran
Keyword(s):  
Big Data ◽  
Organizational Context ◽  
Enterprise Architecture ◽  
Security And Privacy ◽  
Complex Data ◽  
Privacy And Security ◽  
Data Intensive ◽  
Security Models ◽  
Individual System ◽  
Data Ecosystem

AbstractBig data ecosystems are complex data-intensive, digital–physical systems. Data-intensive ecosystems offer a number of benefits; however, they present challenges as well. One major challenge is related to the privacy and security. A number of privacy and security models, techniques and algorithms have been proposed over a period of time. The limitation is that these solutions are primarily focused on an individual or on an isolated organizational context. There is a need to study and provide complete end-to-end solutions that ensure security and privacy throughout the data lifecycle across the ecosystem beyond the boundary of an individual system or organizational context. The results of current study provide a review of the existing privacy and security challenges and solutions using the systematic literature review (SLR) approach. Based on the SLR approach, 79 applicable articles were selected and analyzed. The information from these articles was extracted to compile a catalogue of security and privacy challenges in big data ecosystems and to highlight their interdependencies. The results were categorized from theoretical viewpoint using adaptive enterprise architecture and practical viewpoint using DAMA framework as guiding lens. The findings of this research will help to identify the research gaps and draw novel research directions in the context of privacy and security in big data-intensive ecosystems.

scholarly journals Examine and Visualising Packet Capture Files

2019 ◽  
Vol 8 (2S11) ◽  
pp. 3930-3933
Keyword(s):  
Big Data ◽  
Security Analysts ◽  
Amount Of Information ◽  
Visualisation Tool ◽  
Log Files ◽  
Packet Capture ◽  
Security Analyst ◽  
Enormous Amount ◽  
Graphical View ◽  
Readable Format

The field of security Visualisation is an interesting and tough field of research. Enormous amount of (big) data is involved in the networking of devices. In order to analyse and get data for solving the problem, visualisation can be very helpful. Combination of security world as well as the network world is discussed in this paper. Identifying various visualisation techniques for security log data and executing workflow based composition of multiple analytic components will be identified. Interactive modes of the techniques will be discussed. Making the security files to be readable and the format for analysing are identified. More network visualisation tool allows the security analysts to quickly examine the large amount of information by rendering a millions of events and log entries in a single graphical view. Extracting files from full packet captures can save security analyst a great deal of time. There are tools available for capturing PCAP(Packet Capture) files. This PCAP files will be analysed for further details. In the proposed solution, the PCAP files will be generated with the help of Wireshark and it will be processed with the help of Apache drill for converting it into a readable format and the Visualisation can be done with R Studio. Various Visualisation tools in R will be used to visualise the PCAP files. This in order will thoroughly give some insight on the log files for any detection and prediction of malicious data.

Big Data for Digital Transformation of Public Services

2021 ◽  
pp. 250-266
Author(s):  
Deepak Saxena
Keyword(s):  
Big Data ◽  
Public Services ◽  
Open Data ◽  
Regulatory Compliance ◽  
Digital Transformation ◽  
Future Research ◽  
Full Potential ◽  
Privacy And Security ◽  
Big Data Application ◽  
Digital Enterprise

Big data is presently considered integral to the management and strategies for digital enterprise transformation. Beyond being ‘a lot of data', big data can be characterized in terms of seven Vs: volume, velocity, variety, variability, veracity, visualization, and value. Already being applied in private businesses, big data has immense potential for the digital transformation of public services in advancing the e-governance agenda. This chapter explores the nature of big data in public service and discusses its application in areas such as tax administration, transportation, energy, public health, and disaster management. Challenges and concerns are noted in terms of data quality, infrastructure cost, availability of suitable human resources, privacy, and security. Possible solutions such as shared services, cloud computing, open source software, open data framework, and regulatory compliance are noted. The chapter ends by noting future research directions to realize the full potential of Big data application in digital transformation of public services.

scholarly journals Content an Insight to Security Paradigm for BigData on Cloud: Current Trend and Research

2017 ◽  
Vol 7 (5) ◽  
pp. 2873 ◽  
Author(s):  
Chhaya S Dule ◽  
Girijamma H. A.
Keyword(s):  
Big Data ◽  
Data Storage ◽  
Current Trend ◽  
Security And Privacy ◽  
Future Research ◽  
Survey Analysis ◽  
Cloud Infrastructure ◽  
Privacy And Security ◽  
Storage Mechanism ◽  
Efficient Data

The sucesssive growth of collabrative applications prodcuing Bigdata on timeline leads new opprutinity to setup commodities on cloud infrastructure. Mnay organizations will have demand of an efficient data storage mechanism and also the efficient data analysis. The Big Data (BD) also faces some of the security issues for the important data or information which is shared or transferred over the cloud. These issues include the tampering, losing control over the data, etc. This survey work offers some of the interesting, important aspects of big data including the high security and privacy issue. In this, the survey of existing research works for the preservation of privacy and security mechanism and also the existing tools for it are stated. The discussions for upcoming tools which are needed to be focused on performance improvement are discussed. With the survey analysis, a research gap is illustrated, and a future research idea is presented

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.

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