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  • Open Access

    ARTICLE

    A Joint Estimation Method of SOC and SOH for Lithium-ion Battery Considering Cyber-Attacks Based on GA-BP

    Tianqing Yuan1,2, Na Li1,2, Hao Sun3, Sen Tan4,*

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4497-4512, 2024, DOI:10.32604/cmc.2024.056061 - 12 September 2024

    Abstract To improve the estimation accuracy of state of charge (SOC) and state of health (SOH) for lithium-ion batteries, in this paper, a joint estimation method of SOC and SOH at charging cut-off voltage based on genetic algorithm (GA) combined with back propagation (BP) neural network is proposed, the research addresses the issue of data manipulation resulting from cyber-attacks. Firstly, anomalous data stemming from cyber-attacks are identified and eliminated using the isolated forest algorithm, followed by data restoration. Secondly, the incremental capacity (IC) curve is derived from the restored data using the Kalman filtering algorithm, with… More >

  • Open Access

    ARTICLE

    Detection of Real-Time Distributed Denial-of-Service (DDoS) Attacks on Internet of Things (IoT) Networks Using Machine Learning Algorithms

    Zaed Mahdi1,*, Nada Abdalhussien2, Naba Mahmood1, Rana Zaki3,*

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2139-2159, 2024, DOI:10.32604/cmc.2024.053542 - 15 August 2024

    Abstract The primary concern of modern technology is cyber attacks targeting the Internet of Things. As it is one of the most widely used networks today and vulnerable to attacks. Real-time threats pose with modern cyber attacks that pose a great danger to the Internet of Things (IoT) networks, as devices can be monitored or service isolated from them and affect users in one way or another. Securing Internet of Things networks is an important matter, as it requires the use of modern technologies and methods, and real and up-to-date data to design and train systems… More >

  • Open Access

    REVIEW

    Deep Transfer Learning Techniques in Intrusion Detection System-Internet of Vehicles: A State-of-the-Art Review

    Wufei Wu1, Javad Hassannataj Joloudari2,3,4, Senthil Kumar Jagatheesaperumal5, Kandala N. V. P. S. Rajesh6, Silvia Gaftandzhieva7,*, Sadiq Hussain8, Rahimullah Rabih9, Najibullah Haqjoo10, Mobeen Nazar11, Hamed Vahdat-Nejad9, Rositsa Doneva12

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2785-2813, 2024, DOI:10.32604/cmc.2024.053037 - 15 August 2024

    Abstract The high performance of IoT technology in transportation networks has led to the increasing adoption of Internet of Vehicles (IoV) technology. The functional advantages of IoV include online communication services, accident prevention, cost reduction, and enhanced traffic regularity. Despite these benefits, IoV technology is susceptible to cyber-attacks, which can exploit vulnerabilities in the vehicle network, leading to perturbations, disturbances, non-recognition of traffic signs, accidents, and vehicle immobilization. This paper reviews the state-of-the-art achievements and developments in applying Deep Transfer Learning (DTL) models for Intrusion Detection Systems in the Internet of Vehicles (IDS-IoV) based on anomaly… More >

  • Open Access

    ARTICLE

    Intrusion Detection System for Smart Industrial Environments with Ensemble Feature Selection and Deep Convolutional Neural Networks

    Asad Raza1,*, Shahzad Memon1, Muhammad Ali Nizamani1, Mahmood Hussain Shah2

    Intelligent Automation & Soft Computing, Vol.39, No.3, pp. 545-566, 2024, DOI:10.32604/iasc.2024.051779 - 11 July 2024

    Abstract Smart Industrial environments use the Industrial Internet of Things (IIoT) for their routine operations and transform their industrial operations with intelligent and driven approaches. However, IIoT devices are vulnerable to cyber threats and exploits due to their connectivity with the internet. Traditional signature-based IDS are effective in detecting known attacks, but they are unable to detect unknown emerging attacks. Therefore, there is the need for an IDS which can learn from data and detect new threats. Ensemble Machine Learning (ML) and individual Deep Learning (DL) based IDS have been developed, and these individual models achieved… More >

  • Open Access

    ARTICLE

    CL2ES-KDBC: A Novel Covariance Embedded Selection Based on Kernel Distributed Bayes Classifier for Detection of Cyber-Attacks in IoT Systems

    Talal Albalawi, P. Ganeshkumar*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3511-3528, 2024, DOI:10.32604/cmc.2024.046396 - 26 March 2024

    Abstract The Internet of Things (IoT) is a growing technology that allows the sharing of data with other devices across wireless networks. Specifically, IoT systems are vulnerable to cyberattacks due to its opennes The proposed work intends to implement a new security framework for detecting the most specific and harmful intrusions in IoT networks. In this framework, a Covariance Linear Learning Embedding Selection (CL2ES) methodology is used at first to extract the features highly associated with the IoT intrusions. Then, the Kernel Distributed Bayes Classifier (KDBC) is created to forecast attacks based on the probability distribution More >

  • Open Access

    REVIEW

    A Survey on Sensor- and Communication-Based Issues of Autonomous UAVs

    Pavlo Mykytyn1,2,*, Marcin Brzozowski1, Zoya Dyka1,2, Peter Langendoerfer1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1019-1050, 2024, DOI:10.32604/cmes.2023.029075 - 17 November 2023

    Abstract The application field for Unmanned Aerial Vehicle (UAV) technology and its adoption rate have been increasing steadily in the past years. Decreasing cost of commercial drones has enabled their use at a scale broader than ever before. However, increasing the complexity of UAVs and decreasing the cost, both contribute to a lack of implemented security measures and raise new security and safety concerns. For instance, the issue of implausible or tampered UAV sensor measurements is barely addressed in the current research literature and thus, requires more attention from the research community. The goal of this… More >

  • Open Access

    ARTICLE

    Analysis of Security Testing Techniques

    Omer Bin Tauqeer1, Sadeeq Jan1,*, Alaa Omar Khadidos2, Adil Omar Khadidos3, Fazal Qudus Khan3, Sana Khattak1

    Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 291-306, 2021, DOI:10.32604/iasc.2021.017260 - 12 May 2021

    Abstract In the past decades, a significant increase has been observed in cyber-attacks on the web-based systems used for financial purposes. Such individual systems often contain security weaknesses, called vulnerabilities that can be exploited for malicious purposes. The exploitation of such vulnerabilities can result in disclosure and manipulation of sensitive data as well as have destructive effects. To protect such systems, security testing is required on a periodic basis. Various detection and assessment techniques have been suggested by developers and researchers to address these security issues. In this paper, we survey the contributions of academia in… More >

  • Open Access

    ARTICLE

    Cyber Security and Privacy Issues in Industrial Internet of Things

    NZ Jhanjhi1, Mamoona Humayun2,*, Saleh N. Almuayqil2

    Computer Systems Science and Engineering, Vol.37, No.3, pp. 361-380, 2021, DOI:10.32604/csse.2021.015206 - 08 March 2021

    Abstract The emergence of industry 4.0 stems from research that has received a great deal of attention in the last few decades. Consequently, there has been a huge paradigm shift in the manufacturing and production sectors. However, this poses a challenge for cybersecurity and highlights the need to address the possible threats targeting (various pillars of) industry 4.0. However, before providing a concrete solution certain aspect need to be researched, for instance, cybersecurity threats and privacy issues in the industry. To fill this gap, this paper discusses potential solutions to cybersecurity targeting this industry and highlights… More >

  • Open Access

    ARTICLE

    An Efficient Sound and Data Steganography Based Secure Authentication System

    Debajit Datta1, Lalit Garg2,*, Kathiravan Srinivasan3, Atsushi Inoue4, G. Thippa Reddy3, M. Praveen Kumar Reddy3, K. Ramesh5, Nidal Nasser6

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 723-751, 2021, DOI:10.32604/cmc.2021.014802 - 12 January 2021

    Abstract The prodigious advancements in contemporary technologies have also brought in the situation of unprecedented cyber-attacks. Further, the pin-based security system is an inadequate mechanism for handling such a scenario. The reason is that hackers use multiple strategies for evading security systems and thereby gaining access to private data. This research proposes to deploy diverse approaches for authenticating and securing a connection amongst two devices/gadgets via sound, thereby disregarding the pins’ manual verification. Further, the results demonstrate that the proposed approaches outperform conventional pin-based authentication or QR authentication approaches. Firstly, a random signal is encrypted, and… More >

  • Open Access

    ARTICLE

    Multilayer Self-Defense System to Protect Enterprise Cloud

    Shailendra Mishra, Sunil Kumar Sharma*, Majed A. Alowaidi

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 71-85, 2021, DOI:10.32604/cmc.2020.012475 - 30 October 2020

    Abstract A data breach can seriously impact organizational intellectual property, resources, time, and product value. The risk of system intrusion is augmented by the intrinsic openness of commonly utilized technologies like TCP/IP protocols. As TCP relies on IP addresses, an attacker may easily trace the IP address of the organization. Given that many organizations run the risk of data breach and cyber-attacks at a certain point, a repeatable and well-developed incident response framework is critical to shield them. Enterprise cloud possesses the challenges of security, lack of transparency, trust and loss of controls. Technology eases quickens… More >

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