Muhammad Irfan¹, Ali Raza^2,*, Faisal Althobiani³, Nasir Ayub^4,5, Muhammad Idrees⁶, Zain Ali⁷, Kashif Rizwan⁴, Abdullah Saeed Alwadie¹, Saleh Mohammed Ghonaim³, Hesham Abdushkour³, Saifur Rahman¹, Omar Alshorman¹, Samar Alqhtani⁸

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4249-4265, 2022, DOI:10.32604/cmc.2022.025863

Abstract In the Smart Grid (SG) residential environment, consumers change their power consumption routine according to the price and incentives announced by the utility, which causes the prices to deviate from the initial pattern. Thereby, electricity demand and price forecasting play a significant role and can help in terms of reliability and sustainability. Due to the massive amount of data, big data analytics for forecasting becomes a hot topic in the SG domain. In this paper, the changing and non-linearity of consumer consumption pattern complex data is taken as input. To minimize the computational cost and complexity of the data, the… More >

Soban Arshad¹, Khalid Iqbal^1,*, Sheneela Naz², Sadaf Yasmin¹, Zobia Rehman²

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4283-4301, 2022, DOI:10.32604/cmc.2022.025442

Abstract Telecom industry relies on churn prediction models to retain their customers. These prediction models help in precise and right time recognition of future switching by a group of customers to other service providers. Retention not only contributes to the profit of an organization, but it is also important for upholding a position in the competitive market. In the past, numerous churn prediction models have been proposed, but the current models have a number of flaws that prevent them from being used in real-world large-scale telecom datasets. These schemes, fail to incorporate frequently changing requirements. Data sparsity, noisy data, and the… More >

Saraswathi Shunmuganathan^1,*, Sridharan Kannan², T. V. Madhusudhana Rao³, K. Ambika⁴, T. Jayasankar⁵

Computer Systems Science and Engineering, Vol.43, No.2, pp. 785-801, 2022, DOI:10.32604/csse.2022.022424

Abstract The Cloud Computing Environment (CCE) developed for using the dynamic cloud is the ability of software and services likely to grow with any business. It has transformed the methodology for storing the enterprise data, accessing the data, and Data Sharing (DS). Big data frame a constant way of uploading and sharing the cloud data in a hierarchical architecture with different kinds of separate privileges to access the data. With the requirement of vast volumes of storage area in the CCEs, capturing a secured data access framework is an important issue. This paper proposes an Improved Secure Identification-based Multilevel Structure of… More >

Mohammed BinJubier¹, Mohd Arfian Ismail¹, Abdulghani Ali Ahmed^2,*, Ali Safaa Sadiq³

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3665-3686, 2022, DOI:10.32604/cmc.2022.024663

Abstract Publishing big data and making it accessible to researchers is important for knowledge building as it helps in applying highly efficient methods to plan, conduct, and assess scientific research. However, publishing and processing big data poses a privacy concern related to protecting individuals’ sensitive information while maintaining the usability of the published data. Several anonymization methods, such as slicing and merging, have been designed as solutions to the privacy concerns for publishing big data. However, the major drawback of merging and slicing is the random permutation procedure, which does not always guarantee complete protection against attribute or membership disclosure. Moreover,… More >

M. Anuradha^1,*, G. Mani², T. Shanthi³, N. R. Nagarajan⁴, P. Suresh⁵, C. Bharatiraja⁶

Computer Systems Science and Engineering, Vol.43, No.1, pp. 381-396, 2022, DOI:10.32604/csse.2022.023321

Abstract In the digital area, Internet of Things (IoT) and connected objects generate a huge quantity of data traffic which feeds big data analytic models to discover hidden patterns and detect abnormal traffic. Though IoT networks are popular and widely employed in real world applications, security in IoT networks remains a challenging problem. Conventional intrusion detection systems (IDS) cannot be employed in IoT networks owing to the limitations in resources and complexity. Therefore, this paper concentrates on the design of intelligent metaheuristic optimization based feature selection with deep learning (IMFSDL) based classification model, called IMFSDL-IDS for IoT networks. The proposed IMFSDL-IDS… More >

Fawaz Alassery^*

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 535-559, 2022, DOI:10.32604/cmc.2022.023558

Abstract Today, Internet of Things (IoT) is a technology paradigm which convinces many researchers for the purpose of achieving high performance of packets delivery in IoT applications such as smart cities. Interconnecting various physical devices such as sensors or actuators with the Internet may causes different constraints on the network resources such as packets delivery ratio, energy efficiency, end-to-end delays etc. However, traditional scheduling methodologies in large-scale environments such as big data smart cities cannot meet the requirements for high performance network metrics. In big data smart cities applications which need fast packets transmission ratio such as sending priority packets to… More >

Kun Yang¹, Xuanxu Jin², Xingyu Zeng^1,*

Journal of Cyber Security, Vol.3, No.4, pp. 187-199, 2021, DOI:10.32604/jcs.2021.026735

Abstract In the environment of big data, the traditional access control lacks effective and flexible access mechanism. Based on attribute access control, this paper proposes a HBMC-ABAC big data access control framework. It solves the problems of difficult authority change, complex management, over-authorization and lack of authorization in big data environment. At the same time, binary mapping codes are proposed to solve the problem of low efficiency of policy retrieval in traditional ABAC. Through experimental analysis, the results show that our proposed HBMC-ABAC model can meet the current large and complex environment of big data. More >

Surbhi Bhatia^*, Mohammed Alojail

Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 1261-1271, 2022, DOI:10.32604/iasc.2022.023501

Abstract The last decade has seen a rapid increase in big data, which has led to a need for more tools that can help organizations in their data management and decision making. Business intelligence tools have removed many of the obstacles to data visibility, and numerous data mining technologies are playing an essential role in this visibility. However, the increase in big data has also led to an increase in ‘dark data’, data that does not have any predefined structure and is not generated intentionally. In this paper, we show how dark data can be mined for practical purposes and utilized… More >

Hanbo Liu^*, Guang Sun

Journal on Big Data, Vol.3, No.4, pp. 175-182, 2021, DOI:10.32604/jbd.2021.024074

Abstract With the advent of the era of big data, traditional financial management has been unable to meet the needs of modern enterprise business. Enterprises hope that financial management has the function of improving the accuracy of corporate financial data, assisting corporate management to make decisions that are more in line with the actual development of the company, and optimizing corporate management systems, thereby comprehensively improving the overall level of the company and ensuring that the company can be in business with the assistance of financial integration, can better improve and develop themselves. Based on the investigation of enterprises and universities,… More >

Ahmed H. Almulihi¹, Fawaz Alassery², Asif Irshad Khan³, Sarita Shukla⁴, Bineet Kumar Gupta⁴, Rajeev Kumar^4,*

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1763-1779, 2022, DOI:10.32604/iasc.2022.023460

Abstract The contributions of the Internet of Medical Things (IoMT), cloud services, information systems, and smart devices are useful for the healthcare industry. With the help of digital healthcare, our lives have been made much more secure and effortless and provide more convenient and accessible treatment. In current, the modern healthcare sector has become more significant and convenient for the purpose of both external and internal threats. Big data breaches affect clients, stakeholders, organisations, and businesses, and they are a source of concern and complication for security professionals. This research examines the many types and categories of big data breaches that… More >