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  • Open Access


    Fault Management Cyber-Physical Systems in Virtual Storage Model

    Kailash Kumar*, Ahmad Abdullah Aljabr

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3781-3801, 2022, DOI:10.32604/cmc.2022.020510

    Abstract On average, every two years, the amount of data existing globally doubles. Software development will be affected and improved by Cyber-Physical Systems (CPS). The number of problems remained even though developments helped Information Technology experts extract better value from their storage investments. Because of poor interoperability between different vendors and devices, countless numbers of Storage Area Networks were created. Network setup used for data storage includes a complex and rigid arrangement of routers, switch, hosts/servers, storage arrays. We have evaluated the performance of routing protocol Transmission Control Protocol (TCP) and Fibre Channel Protocol (FCP) under different network scenario by Network… More >

  • Open Access


    Secure Cloud Data Storage System Using Hybrid Paillier–Blowfish Algorithm

    Bijeta Seth1, Surjeet Dalal1, Dac-Nhuong Le2,3,*, Vivek Jaglan4, Neeraj Dahiya1, Akshat Agrawal5, Mayank Mohan Sharma6, Deo Prakash7, K. D. Verma8

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 779-798, 2021, DOI:10.32604/cmc.2021.014466

    Abstract Cloud computing utilizes enormous clusters of serviceable and manageable resources that can be virtually and dynamically reconfigured in order to deliver optimum resource utilization by exploiting the pay-per-use model. However, concerns around security have been an impediment in the extensive adoption of the cloud computing model. In this regard, advancements in cryptography, accelerated by the wide usage of the internet worldwide, has emerged as a key area in addressing some of these security concerns. In this document, a hybrid cryptographic protocol deploying Blowfish and Paillier encryption algorithms has been presented and its strength compared with the existing hybrid Advanced Encryption… More >

  • Open Access


    Blockchain-Based Data Storage Mechanism for Industrial Internet of Things

    Jin Wang1,2, Wencheng Chen1, Lei Wang3, Yongjun Ren4,*, R. Simon Sherratt5

    Intelligent Automation & Soft Computing, Vol.26, No.5, pp. 1157-1172, 2020, DOI:10.32604/iasc.2020.012174

    Abstract With the development of the Industrial Internet of Things and the continuous expansion of application scenarios, many development bottlenecks have followed. Its data security issue has become an obstacle to its widespread application. It has attracted substantial attention from both academia and industry. Blockchain technology has the characteristics of decentralization, openness and transparency and non-tampering. It has natural advantages in solving the security of the Industrial Internet of Things. Accordingly, this paper first analyzes the security risks associated with data storage in the Industrial Internet of Things and proposes the use of blockchain technology to ensure the secure storage of… More >

  • Open Access


    Secure and Efficient Data Storage and Sharing Scheme Based on Double Blockchain

    Lejun Zhang1,2,*, Minghui Peng1, Weizheng Wang3 , Yansen Su4, Shuna Cui5,6, Seokhoon Kim7

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 499-515, 2021, DOI:10.32604/cmc.2020.012205

    Abstract In the digital era, electronic medical record (EMR) has been a major way for hospitals to store patients’ medical data. The traditional centralized medical system and semi-trusted cloud storage are difficult to achieve dynamic balance between privacy protection and data sharing. The storage capacity of blockchain is limited and single blockchain schemes have poor scalability and low throughput. To address these issues, we propose a secure and efficient medical data storage and sharing scheme based on double blockchain. In our scheme, we encrypt the original EMR and store it in the cloud. The storage blockchain stores the index of the… More >

  • Open Access


    Forensic Investigation Through Data Remnants on Hadoop Big Data Storage System

    Myat Nandar Oo1, Sazia Parvin2, Thandar Thein3

    Computer Systems Science and Engineering, Vol.33, No.3, pp. 203-217, 2018, DOI:10.32604/csse.2018.33.203

    Abstract Forensic examiners are in an uninterrupted battle with criminals in the use of Big Data technology. The underlying storage system is the main scene to trace the criminal activities. Big Data Storage System is identified as an emerging challenge to digital forensics. Thus, it requires the development of a sound methodology to investigate Big Data Storage System. Since the use of Hadoop as Big Data Storage System continues to grow rapidly, investigation process model for forensic analysis on Hadoop Storage and attached client devices is compulsory. Moreover, forensic analysis on Hadoop Big Data Storage System may take additional time without… More >

  • Open Access


    Fast Compass Alignment for Strapdown Inertial Navigation System

    Jin Sun1, Dengyin Zhang1, *, Xiaoye Shi1, Fei Ding1, 2

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1349-1360, 2020, DOI:10.32604/cmc.2020.011459

    Abstract Initial alignment is the precondition for strapdown inertial navigation system (SINS) to navigate. Its two important indexes are accuracy and rapidity, the accuracy of the initial alignment is directly related to the working accuracy of SINS, but in selfalignment, the two indexes are often contradictory. In view of the limitations of conventional data processing algorithms, a novel method of compass alignment based on stored data and repeated navigation calculation for SINS is proposed. By means of data storage, the same data is used in different stages of the initial alignment, which is beneficial to shorten the initial alignment time and… More >

  • Open Access


    Failure Prediction, Lead Time Estimation and Health Degree Assessment for Hard Disk Drives Using Voting Based Decision Trees

    Kamaljit Kaur1, *, Kuljit Kaur2

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 913-946, 2019, DOI:10.32604/cmc.2019.07675

    Abstract Hard Disk drives (HDDs) are an essential component of cloud computing and big data, responsible for storing humongous volumes of collected data. However, HDD failures pose a huge challenge to big data servers and cloud service providers. Every year, about 10% disk drives used in servers crash at least twice, lead to data loss, recovery cost and lower reliability. Recently, the researchers have used SMART parameters to develop various prediction techniques, however, these methods need to be improved for reliability and real-world usage due to the following factors: they lack the ability to consider the gradual change/deterioration of HDDs; they… More >

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