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  • Open Access

    ARTICLE

    Video Transmission Secrecy Improvement Based on Fractional Order Hyper Chaotic System

    S. Kayalvizhi*, S. Malarvizhi

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 1201-1214, 2023, DOI:10.32604/csse.2023.032381

    Abstract In the Digital World scenario, the confidentiality of information in video transmission plays an important role. Chaotic systems have been shown to be effective for video signal encryption. To improve video transmission secrecy, compressive encryption method is proposed to accomplish compression and encryption based on fractional order hyper chaotic system that incorporates Compressive Sensing (CS), pixel level, bit level scrambling and nucleotide Sequences operations. The measurement matrix generates by the fractional order hyper chaotic system strengthens the efficiency of the encryption process. To avoid plain text attack, the CS measurement is scrambled to its pixel level, bit level scrambling decreases… More >

  • Open Access

    ARTICLE

    Short-Term Power Load Forecasting with Hybrid TPA-BiLSTM Prediction Model Based on CSSA

    Jiahao Wen, Zhijian Wang*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 749-765, 2023, DOI:10.32604/cmes.2023.023865

    Abstract Since the existing prediction methods have encountered difficulties in processing the multiple influencing factors in short-term power load forecasting, we propose a bidirectional long short-term memory (BiLSTM) neural network model based on the temporal pattern attention (TPA) mechanism. Firstly, based on the grey relational analysis, datasets similar to forecast day are obtained. Secondly, the bidirectional LSTM layer models the data of the historical load, temperature, humidity, and date-type and extracts complex relationships between data from the hidden row vectors obtained by the BiLSTM network, so that the influencing factors (with different characteristics) can select relevant information from different time steps… More >

  • Open Access

    ARTICLE

    A Novel 2D Hyperchaotic with a Complex Dynamic Behavior for Color Image Encryption

    Yongsheng Hu*, Liyong Nan

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6555-6571, 2023, DOI:10.32604/cmc.2023.036090

    Abstract The generation method of the key stream and the structure of the algorithm determine the security of the cryptosystem. The classical chaotic map has simple dynamic behavior and few control parameters, so it is not suitable for modern cryptography. In this paper, we design a new 2D hyperchaotic system called 2D simple structure and complex dynamic behavior map (2D-SSCDB). The 2D-SSCDB has a simple structure but has complex dynamic behavior. The Lyapunov exponent verifies that the 2D-SSCDB has hyperchaotic behavior, and the parameter space in the hyperchaotic state is extensive and continuous. Trajectory analysis and some randomness tests verify that… More >

  • Open Access

    ARTICLE

    Chaotic Metaheuristics with Multi-Spiking Neural Network Based Cloud Intrusion Detection

    Mohammad Yamin1,*, Saleh Bajaba2, Zenah Mahmoud AlKubaisy1

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6101-6118, 2023, DOI:10.32604/cmc.2023.033677

    Abstract Cloud Computing (CC) provides data storage options as well as computing services to its users through the Internet. On the other hand, cloud users are concerned about security and privacy issues due to the increased number of cyberattacks. Data protection has become an important issue since the users’ information gets exposed to third parties. Computer networks are exposed to different types of attacks which have extensively grown in addition to the novel intrusion methods and hacking tools. Intrusion Detection Systems (IDSs) can be used in a network to manage suspicious activities. These IDSs monitor the activities of the CC environment… More >

  • Open Access

    ARTICLE

    Chaotic Flower Pollination with Deep Learning Based COVID-19 Classification Model

    T. Gopalakrishnan1, Mohamed Yacin Sikkandar2, Raed Abdullah Alharbi3, P. Selvaraj4, Zahraa H. Kareem5, Ahmed Alkhayyat6,*, Ali Hashim Abbas7

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6195-6212, 2023, DOI:10.32604/cmc.2023.033252

    Abstract The Coronavirus Disease (COVID-19) pandemic has exposed the vulnerabilities of medical services across the globe, especially in underdeveloped nations. In the aftermath of the COVID-19 outbreak, a strong demand exists for developing novel computer-assisted diagnostic tools to execute rapid and cost-effective screenings in locations where many screenings cannot be executed using conventional methods. Medical imaging has become a crucial component in the disease diagnosis process, whereas X-rays and Computed Tomography (CT) scan imaging are employed in a deep network to diagnose the diseases. In general, four steps are followed in image-based diagnostics and disease classification processes by making use of… More >

  • Open Access

    ARTICLE

    Securing 3D Point and Mesh Fog Data Using Novel Chaotic Cat Map

    K. Priyadarsini1, Arun Kumar Sivaraman2, Abdul Quadir Md2, Areej Malibari3,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6703-6717, 2023, DOI:10.32604/cmc.2023.030648

    Abstract With the rapid evolution of Internet technology, fog computing has taken a major role in managing large amounts of data. The major concerns in this domain are security and privacy. Therefore, attaining a reliable level of confidentiality in the fog computing environment is a pivotal task. Among different types of data stored in the fog, the 3D point and mesh fog data are increasingly popular in recent days, due to the growth of 3D modelling and 3D printing technologies. Hence, in this research, we propose a novel scheme for preserving the privacy of 3D point and mesh fog data. Chaotic… More >

  • Open Access

    ARTICLE

    An Intelligence Computational Approach for the Fractional 4D Chaotic Financial Model

    Wajaree Weera1, Thongchai Botmart1,*, Charuwat Chantawat1, Zulqurnain Sabir2,3, Waleed Adel4,5, Muhammad Asif Zahoor Raja6, Muhammad Kristiawan7

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2711-2724, 2023, DOI:10.32604/cmc.2023.033233

    Abstract The main purpose of the study is to present a numerical approach to investigate the numerical performances of the fractional 4-D chaotic financial system using a stochastic procedure. The stochastic procedures mainly depend on the combination of the artificial neural network (ANNs) along with the Levenberg-Marquardt Backpropagation (LMB) i.e., ANNs-LMB technique. The fractional-order term is defined in the Caputo sense and three cases are solved using the proposed technique for different values of the fractional order α. The values of the fractional order derivatives to solve the fractional 4-D chaotic financial system are used between 0 and 1. The data… More >

  • Open Access

    ARTICLE

    Numerical Simulation of the Fractional-Order Lorenz Chaotic Systems with Caputo Fractional Derivative

    Dandan Dai1, Xiaoyu Li2, Zhiyuan Li2, Wei Zhang3, Yulan Wang2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1371-1392, 2023, DOI:10.32604/cmes.2022.022323

    Abstract Although some numerical methods of the fractional-order chaotic systems have been announced, high-precision numerical methods have always been the direction that researchers strive to pursue. Based on this problem, this paper introduces a high-precision numerical approach. Some complex dynamic behavior of fractional-order Lorenz chaotic systems are shown by using the present method. We observe some novel dynamic behavior in numerical experiments which are unlike any that have been previously discovered in numerical experiments or theoretical studies. We investigate the influence of , , on the numerical solution of fractional-order Lorenz chaotic systems. The simulation results of integer order are in… More >

  • Open Access

    ARTICLE

    Efficient Hardware Design of a Secure Cancellable Biometric Cryptosystem

    Lamiaa A. Abou Elazm1,2, Walid El-Shafai3,4, Sameh Ibrahim2, Mohamed G. Egila1, H. Shawkey1, Mohamed K. H. Elsaid2, Naglaa F. Soliman5, Hussah Nasser AlEisa6,*, Fathi E. Abd El-Samie3

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 929-955, 2023, DOI:10.32604/iasc.2023.031386

    Abstract Biometric security is a growing trend, as it supports the authentication of persons using confidential biometric data. Most of the transmitted data in multimedia systems are susceptible to attacks, which affect the security of these systems. Biometric systems provide sufficient protection and privacy for users. The recently-introduced cancellable biometric recognition systems have not been investigated in the presence of different types of attacks. In addition, they have not been studied on different and large biometric datasets. Another point that deserves consideration is the hardware implementation of cancellable biometric recognition systems. This paper presents a suggested hybrid cancellable biometric recognition system… More >

  • Open Access

    ARTICLE

    A New Sine-Ikeda Modulated Chaotic Key for Cybersecurity

    S. Hanis*

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 865-878, 2023, DOI:10.32604/iasc.2023.030597

    Abstract In the recent past, the storage of images and data in the cloud has shown rapid growth due to the tremendous usage of multimedia applications. In this paper, a modulated version of the Ikeda map and key generation algorithm are proposed, which can be used as a chaotic key for securely storing images in the cloud. The distinctive feature of the proposed map is that it is hyperchaotic, highly sensitive to initial conditions, and depicts chaos over a wide range of control parameter variations. These properties prevent the attacker from detecting and extracting the keys easily. The key generation algorithm… More >

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