Yousef Sanjalawe^1,2,*, Turke Althobaiti^3,4

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3571-3588, 2023, DOI:10.32604/cmc.2023.037386 - 31 March 2023

Abstract Intrusion Detection System (IDS) in the cloud Computing (CC) environment has received paramount interest over the last few years. Among the latest approaches, Deep Learning (DL)-based IDS methods allow the discovery of attacks with the highest performance. In the CC environment, Distributed Denial of Service (DDoS) attacks are widespread. The cloud services will be rendered unavailable to legitimate end-users as a consequence of the overwhelming network traffic, resulting in financial losses. Although various researchers have proposed many detection techniques, there are possible obstacles in terms of detection performance due to the use of insignificant traffic… More >

Muhammad Usman Sana^1,*, Zhanli Li¹, Tayybah Kiren², Hannan Bin Liaqat³, Shahid Naseem³, Atif Saeed⁴

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2741-2757, 2023, DOI:10.32604/cmc.2023.036093 - 31 March 2023

Abstract Cloud computing is a technology that provides secure storage space for the customer’s massive data and gives them the facility to retrieve and transmit their data efficiently through a secure network in which encryption and decryption algorithms are being deployed. In cloud computation, data processing, storage, and transmission can be done through laptops and mobile devices. Data Storing in cloud facilities is expanding each day and data is the most significant asset of clients. The important concern with the transmission of information to the cloud is security because there is no perceivability of the client’s… More >

Sultan Mesfer Aldossary^*

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3387-3404, 2023, DOI:10.32604/iasc.2023.035249 - 15 March 2023

Abstract With the emergence of cloud technologies, the services of healthcare systems have grown. Simultaneously, machine learning systems have become important tools for developing matured and decision-making computer applications. Both cloud computing and machine learning technologies have contributed significantly to the success of healthcare services. However, in some areas, these technologies are needed to provide and decide the next course of action for patients suffering from diabetic kidney disease (DKD) while ensuring privacy preservation of the medical data. To address the cloud data privacy problem, we proposed a DKD prediction module in a framework using cloud… More >

Caihui Lan¹, Haifeng Li^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2985-3010, 2023, DOI:10.32604/cmes.2023.026321 - 09 March 2023

Abstract Sharing of personal health records (PHR) in cloud computing is an essential functionality in the healthcare system. However, how to securely, efficiently and flexibly share PHRs data of the patient in a multi-receiver setting has not been well addressed. For instance, since the trust domain of the cloud server is not identical to the data owner or data user, the semi-trust cloud service provider may intentionally destroy or tamper shared PHRs data of user or only transform partial ciphertext of the shared PHRs or even return wrong computation results to save its storage and computation… More >

J. Prabakaran^1,*, P. Selvaraj²

Computer Systems Science and Engineering, Vol.46, No.2, pp. 2141-2157, 2023, DOI:10.32604/csse.2023.034210 - 09 February 2023

Abstract In healthcare systems, the Internet of Things (IoT) innovation and development approached new ways to evaluate patient data. A cloud-based platform tends to process data generated by IoT medical devices instead of high storage, and computational hardware. In this paper, an intelligent healthcare system has been proposed for the prediction and severity analysis of lung disease from chest computer tomography (CT) images of patients with pneumonia, Covid-19, tuberculosis (TB), and cancer. Firstly, the CT images are captured and transmitted to the fog node through IoT devices. In the fog node, the image gets modified into… More >

Mesfer Al Duhayyim^1,*, Jaber S. Alzahrani², Hanan Abdullah Mengash³, Mrim M. Alnfiai⁴, Radwa Marzouk³, Gouse Pasha Mohammed⁵, Mohammed Rizwanullah⁵, Amgad Atta Abdelmageed⁵

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1471-1485, 2023, DOI:10.32604/csse.2023.034137 - 09 February 2023

Abstract The Internet of Things (IoT) environment plays a crucial role in the design of smart environments. Security and privacy are the major challenging problems that exist in the design of IoT-enabled real-time environments. Security susceptibilities in IoT-based systems pose security threats which affect smart environment applications. Intrusion detection systems (IDS) can be used for IoT environments to mitigate IoT-related security attacks which use few security vulnerabilities. This paper introduces a modified garden balsan optimization-based machine learning model for intrusion detection (MGBO-MLID) in the IoT cloud environment. The presented MGBO-MLID technique focuses on the identification and… More >

Sumbal Zahoor¹, Ishtiaq Ahmad¹, Ateeq Ur Rehman², Elsayed Tag Eldin³, Nivin A. Ghamry⁴, Muhammad Shafiq^5,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 311-329, 2023, DOI:10.32604/cmc.2023.035960 - 06 February 2023

Abstract The development of the Next-Generation Wireless Network (NGWN) is becoming a reality. To conduct specialized processes more, rapid network deployment has become essential. Methodologies like Network Function Virtualization (NFV), Software-Defined Networks (SDN), and cloud computing will be crucial in addressing various challenges that 5G networks will face, particularly adaptability, scalability, and reliability. The motivation behind this work is to confirm the function of virtualization and the capabilities offered by various virtualization platforms, including hypervisors, clouds, and containers, which will serve as a guide to dealing with the stimulating environment of 5G. This is particularly crucial More >

Mohammad Aldossary^*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 633-649, 2023, DOI:10.32604/cmc.2023.035414 - 06 February 2023

Abstract In the smart city paradigm, the deployment of Internet of Things (IoT) services and solutions requires extensive communication and computing resources to place and process IoT applications in real time, which consumes a lot of energy and increases operational costs. Usually, IoT applications are placed in the cloud to provide high-quality services and scalable resources. However, the existing cloud-based approach should consider the above constraints to efficiently place and process IoT applications. In this paper, an efficient optimization approach for placing IoT applications in a multi-layer fog-cloud environment is proposed using a mathematical model (Mixed-Integer… More >

Jingqi Li^1,*, Yijie Bian¹, Jun Guan², Lu Yang²

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1119-1137, 2023, DOI:10.32604/cmc.2023.035369 - 06 February 2023

Abstract Promoting the co-constructing and sharing of organizational knowledge and improving organizational performance have always been the core research subject of knowledge management. Existing research focuses on the construction of knowledge management systems and knowledge sharing and transfer mechanisms. With the rapid development and application of cloud computing and big data technology, knowledge management is faced with many problems, such as how to combine with the new generation of information technology, how to achieve integration with organizational business processes, and so on. To solve such problems, this paper proposes a reciprocal collaborative knowledge management model (RCKM… More >

Abdulaziz Alorf^*

Computer Systems Science and Engineering, Vol.46, No.1, pp. 273-286, 2023, DOI:10.32604/csse.2023.035437 - 20 January 2023

Abstract Nowadays, smart electricity grids are managed through advanced tools and techniques. The advent of Artificial Intelligence (AI) and network technology helps to control the energy demand. These advanced technologies can resolve common issues such as blackouts, optimal energy generation costs, and peak-hours congestion. In this paper, the residential energy demand has been investigated and optimized to enhance the Quality of Service (QoS) to consumers. The energy consumption is distributed throughout the day to fulfill the demand in peak hours. Therefore, an Edge-Cloud computing-based model is proposed to schedule the energy demand with reward-based energy consumption. More >