Paweł Lula¹, Octavian Dospinescu^2,*, Daniel Homocianu², Napoleon-Alexandru Sireteanu²

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2425-2443, 2021, DOI:10.32604/cmc.2021.013771 - 28 December 2020

Abstract Our primary research hypothesis stands on a simple idea: The evolution of top-rated publications on a particular theme depends heavily on the progress and maturity of related topics. And this even when there are no clear relations or some concepts appear to cease to exist and leave place for newer ones starting many years ago. We implemented our model based on Computer Science Ontology (CSO) and analyzed 44 years of publications. Then we derived the most important concepts related to Cloud Computing (CC) from the scientific collection offered by Clarivate Analytics. Our methodology includes data More >

Zaiwar Ali¹, Sadia Khaf², Ziaul Haq Abbas², Ghulam Abbas³, Lei Jiao⁴, Amna Irshad², Kyung Sup Kwak⁵, Muhammad Bilal^6,*

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1461-1477, 2021, DOI:10.32604/cmc.2020.013743 - 26 November 2020

Abstract In mobile edge computing (MEC), one of the important challenges is how much resources of which mobile edge server (MES) should be allocated to which user equipment (UE). The existing resource allocation schemes only consider CPU as the requested resource and assume utility for MESs as either a random variable or dependent on the requested CPU only. This paper presents a novel comprehensive utility function for resource allocation in MEC. The utility function considers the heterogeneous nature of applications that a UE offloads to MES. The proposed utility function considers all important parameters, including CPU,… More >

Rosilah Hassan¹, Selver Pepic², Muzafer Saracevic³, Khaleel Ahmad^4,*, Milan Tasic⁵

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1139-1153, 2021, DOI:10.32604/cmc.2020.013104 - 26 November 2020

Abstract In this paper, we provide a new approach to data encryption using generalized inverses. Encryption is based on the implementation of weighted Moore–Penrose inverse A^†_MN(nxm) over the nx8 constant matrix. The square Hermitian positive definite matrix N_8x8 p is the key. The proposed solution represents a very strong key since the number of different variants of positive definite matrices of order 8 is huge. We have provided NIST (National Institute of Standards and Technology) quality assurance tests for a random generated Hermitian matrix (a total of 10 different tests and additional analysis with approximate entropy and random… More >

Tao Li¹, Qi Qian², Yongjun Ren^3,*, Yongzhen Ren⁴, Jinyue Xia⁵

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 779-791, 2021, DOI:10.32604/cmc.2020.010424 - 30 October 2020

Abstract The application field of the Internet of Things (IoT) involves all aspects, and its application in the fields of industry, agriculture, environment, transportation, logistics, security and other infrastructure has effectively promoted the intelligent development of these aspects. Although the IoT has gradually grown in recent years, there are still many problems that need to be overcome in terms of technology, management, cost, policy, and security. We need to constantly weigh the benefits of trusting IoT products and the risk of leaking private data. To avoid the leakage and loss of various user data, this paper… More >

Muhammad Adnan Khan^1,*, Mubashar Habib¹, Shazia Saqib¹, Tahir Alyas¹, Khalid Masood Khan¹, Mohammed A. Al Ghamdi², Sultan H. Almotiri²

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 691-706, 2021, DOI:10.32604/cmc.2020.012542 - 30 October 2020

Abstract The innovation and development in data science have an impact in all trades of life. The commercialization of sport has encouraged players, coaches, and other concerns to use technology to be in better position than r their opponents. In the past, the focus was on improved training techniques for better physical performance. These days, sports analytics identify the patterns in the performance and highlight strengths and weaknesses of potential players. Sports analytics not only predict the performance of players in the near future but it also performs predictive modeling for a particular behavior of a… More >

Rizwan Munir^1,*, Yifei Wei¹, Rahim Ullah², Iftikhar Hussain³, Kaleem Arshid⁴, Umair Tariq¹

Journal of Quantum Computing, Vol.2, No.4, pp. 193-202, 2020, DOI:10.32604/jqc.2020.016151 - 07 January 2021

Abstract A smart grid is the evolved form of the power grid with the integration of sensing, communication, computing, monitoring, and control technologies. These technologies make the power grid reliable, efficient, and economical. However, the smartness boosts the volume of data in the smart grid. To obligate full benefits, big data has attractive techniques to process and analyze smart grid data. This paper presents and simulates a framework to make sure the use of big data computing technique in the smart grid. The offered framework comprises of the following four layers: (i) Data source layer, (ii) More >

S. Jerald Nirmal Kumar^1,*, S. Ravimaran², M. M. Gowthul Alam³

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 671-697, 2020, DOI:10.32604/cmes.2020.09361 - 12 October 2020

Abstract Nowadays, succeeding safe communication and protection-sensitive data from unauthorized access above public networks are the main worries in cloud servers. Hence, to secure both data and keys ensuring secured data storage and access, our proposed work designs a Novel Quantum Key Distribution (QKD) relying upon a non-commutative encryption framework. It makes use of a Novel Quantum Key Distribution approach, which guarantees high level secured data transmission. Along with this, a shared secret is generated using Diffie Hellman (DH) to certify secured key generation at reduced time complexity. Moreover, a non-commutative approach is used, which effectively More >

Congdong Lv^{1, *}, Ji Zhang², Zhoubao Sun¹, Gang Qian¹

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2687-2705, 2020, DOI:10.32604/cmc.2020.011232 - 16 September 2020

Abstract Cloud computing provides services to users through Internet. This open mode not only facilitates the access by users, but also brings potential security risks. In cloud computing, the risk of data leakage exists between users and virtual machines. Whether direct or indirect data leakage, it can be regarded as illegal information flow. Methods, such as access control models can control the information flow, but not the covert information flow. Therefore, it needs to use the noninterference models to detect the existence of illegal information flow in cloud computing architecture. Typical noninterference models are not suitable… More >

Nithya Rekha Sivakumar^{1, *}, Sara Ghorashi¹, Mona Jamjoom¹, Mai Alduailij¹

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 1925-1943, 2020, DOI:10.32604/cmc.2020.011505 - 16 September 2020

Abstract In today’s world, smart phones offer various applications namely face detection, augmented-reality, image and video processing, video gaming and speech recognition. With the increasing demand for computing resources, these applications become more complicated. Cloud Computing (CC) environment provides access to unlimited resource pool with several features, including on demand self-service, elasticity, wide network access, resource pooling, low cost, and ease of use. Mobile Cloud Computing (MCC) aimed at overcoming drawbacks of smart phone devices. The task remains in combining CC technology to the mobile devices with improved battery life and therefore resulting in significant performance.… More >

Xiangshu Ou¹, Mingfang Jiang^2,*, Shuai Li¹, Yao Bai¹

Journal of Cyber Security, Vol.2, No.3, pp. 123-130, 2020, DOI:10.32604/jcs.2020.09703 - 14 September 2020

Abstract In smart environments, more and more teaching data sources are uploaded to remote cloud centers which promote the development of the smart campus. The outsourcing of massive teaching data can reduce storage burden and computational cost, but causes some privacy concerns because those teaching data (especially personal image data) may contain personal private information. In this paper, a privacy-preserving image feature extraction algorithm is proposed by using mean value features. Clients use block scrambling and chaotic map to encrypt original images before uploading to the remote servers. Cloud servers can directly extract image mean value More >