scholarly journals Big Data and Cloud Computing: Trends and Challenges

Author(s):  
Samir Abou El-Seoud ◽  
Hosam F. El-Sofany ◽  
Mohamed Ashraf Fouad Abdelfattah ◽  
Reham Mohamed

Big data is currently one of the most critical emerging technologies. Big Data are used as a concept that refers to the inability of traditional data architectures to efficiently handle the new data sets. The 4V’s of big data – volume, velocity, variety and veracity makes the data management and analytics challenging for the traditional data warehouses. It is important to think of big data and analytics together. Big data is the term used to describe the recent explosion of different types of data from disparate sources. Analytics is about examining data to derive interesting and relevant trends and patterns, which can be used to inform decisions, optimize processes, and even drive new business models. Cloud computing seems to be a perfect vehicle for hosting big data workloads. However, working on big data in the cloud brings its own challenge of reconciling two contradictory design principles. Cloud computing is based on the concepts of consolidation and resource pooling, but big data systems (such as Hadoop) are built on the shared nothing principle, where each node is independent and selfsufficient. The integrating big data with cloud computing technologies, businesses and education institutes can have a better direction to the future. The capability to store large amounts of data in different forms and process it all at very large speeds will result in data that can guide businesses and education institutes in developing fast. Nevertheless, there is a large concern regarding privacy and security issues when moving to the cloud which is the main causes as to why businesses and educational institutes will not move to the cloud. This paper introduces the characteristics, trends and challenges of big data. In addition to that, it investigates the benefits and the risks that may rise out of the integration between big data and cloud computing.

2019 ◽  
pp. 1440-1459
Author(s):  
Sara Usmani ◽  
Faiza Rehman ◽  
Sajid Umair ◽  
Safdar Abbas Khan

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.


The term cloud computing is referred as the shared pool of customizable computer resources and high quantity services which can easily be provisioned with less management endeavours via internet. It transfigured the mode associations reach IT, which enables them to be more perceptive, launch new business models, and minimise the IT costs. These technologies are to be administrated in an interdisciplinary collection of architectures, characterized into various deployment and service models, and can synchronize with other related technologies. The widespread issues with cloud computing are security, reliability, data privacy and anonymity. Cloud computing provides a way to share distributed sources and services that are owned by different organizations or sites. Since it shares distributed resources via network in open environment that results in security issues. In this paper, our aim is to upgrade the security of data in the cloud and also to annihilate the difficulties related to the data security with encipher algorithm. In our proposed plan, some key services of security like authentication and cryptographic techniques are assigned in cloud computing environment.


Author(s):  
Sara Usmani ◽  
Faiza Rehman ◽  
Sajid Umair ◽  
Safdar Abbas Khan

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.


2021 ◽  
Vol 29 (4) ◽  
Author(s):  
Matteo Repetto ◽  
Domenico Striccoli ◽  
Giuseppe Piro ◽  
Alessandro Carrega ◽  
Gennaro Boggia ◽  
...  

AbstractToday, the digital economy is pushing new business models, based on the creation of value chains for data processing, through the interconnection of processes, products, services, software, and things across different domains and organizations. Despite the growing availability of communication infrastructures, computing paradigms, and software architectures that already effectively support the implementation of distributed multi-domain value chains, a comprehensive architecture is still missing that effectively fulfills all related security issues: mutual trustworthiness of entities in partially unknown topologies, identification and mitigation of advanced multi-vector threats, identity management and access control, management and propagation of sensitive data. In order to fill this gap, this work proposes a new methodological approach to design and implement heterogeneous security services for distributed systems that combine together digital resources and components from multiple domains. The framework is designed to support both existing and new security services, and focuses on three novel aspects: (i) full automation of the processes that manage the whole system, i.e., threat detection, collection of information and reaction to attacks and system anomalies; (ii) dynamic adaptation of operations and security tasks to newest attack patterns, and (iii) real-time adjustment of the level of detail of inspection and monitoring processes. The overall architecture as well as the functions and relationships of its logical components are described in detail, presenting also a concrete use case as an example of application of the proposed framework.


2018 ◽  
Vol 189 ◽  
pp. 10015 ◽  
Author(s):  
Karim Zkik ◽  
Said EL Hajji ◽  
Ghizlane Orhanou

The information technology sector has experienced phenomenal growth during recent years. To follow this development many new technologies have emerged to satisfy the expectations of businesses and customers, such as Cloud Computing, mobility, virtualization, Internet of things and big data. Traditional network cannot longer support this growth and suffers more and more in terms of misconfiguration,management and configurations complexity. Software defined network (SDN) architectures can be considered as a big revolution in the field of computer networks, because they offer a centralized control on infrastructure, services and the applications deployed which facilitate configuration and management on the network. The implementation of this type of architecture is not obvious and requires great expertise and good handling and management of network equipment. To remedy this problem the SDN architectures have evolved towards distributed and hybrid architectures. Despites the advantages of using SDN, security issues remain a real obstacle in front of the deployment of this type of architecture. The centralized architecture of this type of networks makes it vulnerable to several types of attacks and intrusions, and the implementation of security equipment generally causes a decrease in performance and increase latency.


2018 ◽  
Vol 6 (4) ◽  
pp. 39-47 ◽  
Author(s):  
Reuben Ng

Cloud computing adoption enables big data applications in governance and policy. Singapore’s adoption of cloud computing is propelled by five key drivers: (1) public demand for and satisfaction with e-government services; (2) focus on whole-of-government policies and practices; (3) restructuring of technology agencies to integrate strategy and implementation; (4) building the Smart Nation Platform; (5) purpose-driven cloud applications especially in healthcare. This commentary also provides recommendations to propel big data applications in public policy and management: (a) technologically, embrace cloud analytics, and explore “fog computing”—an emerging technology that enables on-site data sense-making before transmission to the cloud; (b) promote regulatory sandboxes to experiment with policies that proactively manage novel technologies and business models that may radically change society; (c) on the collaboration front, establish unconventional partnerships to co-innovate on challenges like the skills-gap—an example is the unprecedented partnership led by the Lee Kuan Yew School of Public Policy with the government, private sector and unions.


Web Services ◽  
2019 ◽  
pp. 2161-2171
Author(s):  
Miltiadis D. Lytras ◽  
Vijay Raghavan ◽  
Ernesto Damiani

The Big Data and Data Analytics is a brand new paradigm, for the integration of Internet Technology in the human and machine context. For the first time in the history of the human mankind we are able to transforming raw data that are massively produced by humans and machines in to knowledge and wisdom capable of supporting smart decision making, innovative services, new business models, innovation, and entrepreneurship. For the Web Science research, this is a new methodological and technological spectrum of advanced methods, frameworks and functionalities never experienced in the past. At the same moment communities out of web science need to realize the potential of this new paradigm with the support of new sound business models and a critical shift in the perception of decision making. In this short visioning article, the authors are analyzing the main aspects of Big Data and Data Analytics Research and they provide their own metaphor for the next years. A number of research directions are outlined as well as a new roadmap towards the evolution of Big Data to Smart Decisions and Cognitive Computing. The authors do hope that the readers would like to react and to propose their own value propositions for the domain initiating a scientific dialogue beyond self-fulfilled expectations.


Author(s):  
Navin Jambhekar ◽  
Chitra Anil Dhawale

Information security is a prime goal for every individual and organization. The travelling from client to cloud server can be prone to security issues. The big data storages are available through cloud computing system to facilitate mobile client. The information security can be provided to mobile client and cloud technology with the help of integrated parallel and distributed encryption and decryption mechanism. The traditional technologies include the plaintext stored across cloud and can be prone to security issues. The solution provided by applying the encrypted data upload and encrypted search. The clouds can work in collaboration; therefore, the encryption can also be done in collaboration. Some part of encryption handle by client and other part handled by cloud system. This chapter presents the security scenario of different security algorithms and the concept of mobile and cloud computing. This chapter precisely defines the security features of existing cloud and big data system and provides the new framework that helps to improve the data security over cloud computing and big data security system.


Sign in / Sign up

Export Citation Format

Share Document