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

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.

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.

Role of Big Data in Internet of Things Networks

2022 ◽  
pp. 336-363
Author(s):  
Vijayalakshmi Saravanan ◽  
Fatima Hussain ◽  
Naik Kshirasagar
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Data Storage ◽  
Data Analytics ◽  
Future Research ◽  
Smart Transportation ◽  
Architectural Model ◽  
Efficient Data ◽  
Smart Health

With recent advancement in cyber-physical systems and technological revolutions, internet of things is the focus of research in industry as well as in academia. IoT is not only a research and technological revolution but in fact a revolution in our daily life. It is considered a new era of smart lifestyle and has a deep impact on everyday errands. Its applications include but are not limited to smart home, smart transportation, smart health, smart security, and smart surveillance. A large number of devices connected in all these application networks generates an enormous amount of data. This leads to problems in data storage, efficient data processing, and intelligent data analytics. In this chapter, the authors discuss the role of big data and related challenges in IoT networks and various data analytics platforms, used for the IoT domain. In addition to this, they present and discuss the architectural model of big data in IoT along with various future research challenges. Afterward, they discuss smart health and smart transportation as a case study to supplement the presented architectural 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.

Role of Big Data in Internet of Things Networks

2019 ◽  
pp. 273-299 ◽  
Author(s):  
Vijayalakshmi Saravanan ◽  
Fatima Hussain ◽  
Naik Kshirasagar
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Data Storage ◽  
Data Analytics ◽  
Future Research ◽  
Smart Transportation ◽  
Architectural Model ◽  
Efficient Data ◽  
Smart Health

With recent advancement in cyber-physical systems and technological revolutions, internet of things is the focus of research in industry as well as in academia. IoT is not only a research and technological revolution but in fact a revolution in our daily life. It is considered a new era of smart lifestyle and has a deep impact on everyday errands. Its applications include but are not limited to smart home, smart transportation, smart health, smart security, and smart surveillance. A large number of devices connected in all these application networks generates an enormous amount of data. This leads to problems in data storage, efficient data processing, and intelligent data analytics. In this chapter, the authors discuss the role of big data and related challenges in IoT networks and various data analytics platforms, used for the IoT domain. In addition to this, they present and discuss the architectural model of big data in IoT along with various future research challenges. Afterward, they discuss smart health and smart transportation as a case study to supplement the presented architectural model.

scholarly journals Intelligent Secure Storage Mechanism for Big Data

Webology ◽  
2021 ◽  
Vol 18 (Special Issue 01) ◽  
pp. 246-261
Author(s):  
K.R. Remesh Babu ◽  
K.P. Madhu
Keyword(s):  
Big Data ◽  
Data Storage ◽  
Big Data Analytics ◽  
Business Organizations ◽  
Storage Mechanism ◽  
Data Intensive ◽  
Secure Storage ◽  
Huge Data ◽  
Efficient Data ◽  
Data Intensive Applications

The management of big data became more important due to the wide spread adoption of internet of things in various fields. The developments in technology, science, human habits, etc., generates massive amount of data, so it is increasingly important to store and protect these data from attacks. Big data analytics is now a hot topic. The data storage facility provided by the cloud computing enabled business organizations to overcome the burden of huge data storage and maintenance. Also, several distributed cloud applications supports them to analyze this data for taking appropriate decisions. The dynamic growth of data and data intensive applications demands an efficient intelligent storage mechanism for big data. The proposed system analyzes IP packets for vulnerabilities and classifies data nodes as reliable and unreliable nodes for the efficient data storage. The proposed Apriori algorithm based method automatically classifies the nodes for intelligent secure storage mechanism for the distributed big data storage.

Data Security and Data Privacy in Cloud Computing

2014 ◽  
Vol 905 ◽  
pp. 687-692
Author(s):  
Waleed Al-Museelem ◽  
Chun Lin Li
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Data Security ◽  
Data Privacy ◽  
Research Work ◽  
Research Paper ◽  
Security And Privacy ◽  
Future Research ◽  
Successful Implementation ◽  
Privacy And Security

Cloud computing has led to the development of IT to more sophisticated levels by improving the capacity and flexibility of data storage and by providing a scalable computation and processing power which matches the dynamic data requirements. Cloud computing has many benefits which has led to the transfer of many enterprise applications and data to public and hybrid clouds. However, many organizations refer to the protection of privacy and the security of data as the major issues which prevent them from adopting cloud computing. The only way successful implementation of clouds can be achieved is through effective enhancement and management of data security and privacy in clouds. This research paper analyzes the privacy and protection of data in cloud computing through all data lifecycle stages providing an overall perspective of cloud computing while highlighting key security issues and concerns which should be addressed. It also discusses several current solutions and further proposes more solutions which can enhance the privacy and security of data in clouds. Finally, the research paper describes future research work on the protection of data privacy and security in clouds.

Website Information Security and Privacy Concerns in 4IR: The Moderating Role of Trust in B2C e-Commerce

10.29007/jlq6 ◽  
2019 ◽  
Author(s):  
Thabang Mofokeng
Keyword(s):  
South Africa ◽  
Customer Satisfaction ◽  
Customer Loyalty ◽  
Success Factors ◽  
Industrial Revolution ◽  
Emerging Market ◽  
Security And Privacy ◽  
Future Research ◽  
Privacy And Security ◽  
Customer Trust

The technology devices introduced in recent years are not only vulnerable to Internet risks but are also unable to elevate the growth of B2C e-commerce. These concerns are particularly relevant today, as the world transitions into the Fourth Industrial Revolution. To date, existing research has largely focused on obstacles to customer loyalty. Studies have tested e-commerce models guided by the establishment of trusting, satisfied and loyal consumers in various international contexts. In South Africa, however, as an emerging market, there has been limited research on the success factors of online shopping.This study examines the influence of security and privacy on trust, seen as a moderator of customer satisfaction, which in turn, has an effect on loyalty towards websites. Based on an exhaustive review of literature, a conceptual model is proposed on the relationships between security and privacy on the one hand, and customer trust, satisfaction and loyalty on the other. A total of 250 structured, self-administered questionnaires was distributed to a purposively selected sample of respondents using face-to-face surveys in Johannesburg, South Africa. A multivariate data analysis technique was used to draw inferences from the data. With an 80.1% response rate, the findings showed that privacy and security do influence customer trust; security strongly influences customer trust and weakly influences satisfaction. In South Africa, customer loyalty towards websites is strongly determined by satisfaction and weakly determined by trust. Trust significantly moderates the effect of customer satisfaction on loyalty. The study implications and limitations are presented and future research directions are suggested.

scholarly journals Design on Big data Platform-based in Higher Education Institute

2020 ◽  
Vol 10 (4) ◽  
pp. 36
Author(s):  
Sajeewan Pratsri ◽  
Prachyanun Nilsook
Keyword(s):  
Higher Education ◽  
Big Data ◽  
Data Analysis ◽  
Digital Media ◽  
Data Storage ◽  
Security And Privacy ◽  
Digital Learning ◽  
Learning Platform ◽  
Data Platform ◽  
Tools And Techniques

According to a continuously increasing amount of information in all aspects whether the sources are retrieved from an internal or external organization, a platform should be provided for the automation of whole processes in the collection, storage, and processing of Big Data. The tool for creating Big Data is a Big Data challenge. Furthermore, the security and privacy of Big Data and Big Data analysis in organizations, government agencies, and educational institutions also have an impact on the aspect of designing a Big Data platform for higher education institute (HEi). It is a digital learning platform that is an online instruction and the use of digital media for educational reform including a module provides information on functions of various modules between computers and humans. 1) Big Data architecture is a framework for an architecture of numerous data which consisting of Big Data Infrastructure (BDI), Data Storage (Cloud-based), processing of a computer system that uses all parts of computer resources for optimal efficiency (High-Performance Computing: HPC), a network system to detect the target device network. Thereafter, according to Hadoop’s tools and techniques, when Big Data was introduced with Hadoop's tools and techniques, the benefits of the Big Data platform would provide desired data analysis by retrieving existing information, to illustrate, student information and teaching information that is large amounts of information to adopt for accurate forecasting.

scholarly journals Security and Privacy Risk Assessment of Energy Big Data in Cloud Environment

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Zhiru Li ◽  
Wei Xu ◽  
Huibin Shi ◽  
Yuanyuan Zhang ◽  
Yan Yan
Keyword(s):  
Neural Network ◽  
Risk Factors ◽  
Risk Assessment ◽  
Big Data ◽  
Data Storage ◽  
Bp Neural Network ◽  
Security And Privacy ◽  
Cloud Environment ◽  
Privacy Risk ◽  
Whole Life Cycle

Considering the importance of energy in our lives and its impact on other critical infrastructures, this paper starts from the whole life cycle of big data and divides the security and privacy risk factors of energy big data into five stages: data collection, data transmission, data storage, data use, and data destruction. Integrating into the consideration of cloud environment, this paper fully analyzes the risk factors of each stage and establishes a risk assessment index system for the security and privacy of energy big data. According to the different degrees of risk impact, AHP method is used to give indexes weights, genetic algorithm is used to optimize the initial weights and thresholds of BP neural network, and then the optimized weights and thresholds are given to BP neural network, and the evaluation samples in the database are used to train it. Then, the trained model is used to evaluate a case to verify the applicability of the model.

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