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  • Open Access

    REVIEW

    Blockchain-Enabled Cybersecurity Provision for Scalable Heterogeneous Network: A Comprehensive Survey

    Md. Shohidul Islam1,*, Md. Arafatur Rahman2, Mohamed Ariff Bin Ameedeen1, Husnul Ajra1, Zahian Binti Ismail1, Jasni Mohamad Zain3

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 43-123, 2024, DOI:10.32604/cmes.2023.028687

    Abstract Blockchain-enabled cybersecurity system to ensure and strengthen decentralized digital transaction is gradually gaining popularity in the digital era for various areas like finance, transportation, healthcare, education, and supply chain management. Blockchain interactions in the heterogeneous network have fascinated more attention due to the authentication of their digital application exchanges. However, the exponential development of storage space capabilities across the blockchain-based heterogeneous network has become an important issue in preventing blockchain distribution and the extension of blockchain nodes. There is the biggest challenge of data integrity and scalability, including significant computing complexity and inapplicable latency on regional network diversity, operating system… More > Graphic Abstract

    Blockchain-Enabled Cybersecurity Provision for Scalable Heterogeneous Network: A Comprehensive Survey

  • Open Access

    ARTICLE

    Design the IoT Botnet Defense Process for Cybersecurity in Smart City

    Donghyun Kim1, Seungho Jeon2, Jiho Shin3, Jung Taek Seo4,*

    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2979-2997, 2023, DOI:10.32604/iasc.2023.040019

    Abstract The smart city comprises various infrastructures, including healthcare, transportation, manufacturing, and energy. A smart city’s Internet of Things (IoT) environment constitutes a massive IoT environment encompassing numerous devices. As many devices are installed, managing security for the entire IoT device ecosystem becomes challenging, and attack vectors accessible to attackers increase. However, these devices often have low power and specifications, lacking the same security features as general Information Technology (IT) systems, making them susceptible to cyberattacks. This vulnerability is particularly concerning in smart cities, where IoT devices are connected to essential support systems such as healthcare and transportation. Disruptions can lead… More >

  • Open Access

    ARTICLE

    Explainable Artificial Intelligence-Based Model Drift Detection Applicable to Unsupervised Environments

    Yongsoo Lee, Yeeun Lee, Eungyu Lee, Taejin Lee*

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1701-1719, 2023, DOI:10.32604/cmc.2023.040235

    Abstract Cybersecurity increasingly relies on machine learning (ML) models to respond to and detect attacks. However, the rapidly changing data environment makes model life-cycle management after deployment essential. Real-time detection of drift signals from various threats is fundamental for effectively managing deployed models. However, detecting drift in unsupervised environments can be challenging. This study introduces a novel approach leveraging Shapley additive explanations (SHAP), a widely recognized explainability technique in ML, to address drift detection in unsupervised settings. The proposed method incorporates a range of plots and statistical techniques to enhance drift detection reliability and introduces a drift suspicion metric that considers… More >

  • Open Access

    REVIEW

    Phishing Attacks in Social Engineering: A Review

    Kofi Sarpong Adu-Manu*, Richard Kwasi Ahiable, Justice Kwame Appati, Ebenezer Essel Mensah

    Journal of Cyber Security, Vol.4, No.4, pp. 239-267, 2022, DOI:10.32604/jcs.2023.041095

    Abstract Organisations closed their offices and began working from home online to prevent the spread of the COVID-19 virus. This shift in work culture coincided with increased online use during the same period. As a result, the rate of cybercrime has skyrocketed. This study examines the approaches, techniques, and countermeasures of Social Engineering and phishing in this context. The study discusses recent trends in the existing approaches for identifying phishing assaults. We explore social engineering attacks, categorise them into types, and offer both technical and social solutions for countering phishing attacks which makes this paper different from similar works that mainly… More >

  • Open Access

    ARTICLE

    Seeded Transfer Learning for Enhanced Attack Trace and Effective Deception

    Jalaj Pateria1,*, Laxmi Ahuja1, Subhranil Som2

    Journal of Cyber Security, Vol.4, No.4, pp. 223-238, 2022, DOI:10.32604/jcs.2023.040186

    Abstract Cyberattacks have reached their peak during COVID-19, and intruders urge to gain the upper hand in the cybersecurity battlefield, even gaining dominance. Now intruders are trying harder to elude behavior analysis techniques, which in turn gets organization security to come for a toss. This phenomenon is even more prevalent in agentless environments (IOT devices, mobile devices), where we do not have any access to edge devices and rely on packet data to predict any attack and its actors. In this paper, we shall be discussing enhancing the accuracy of anomalous behavior detection techniques for efficient threat intelligence and revamping deception… More >

  • Open Access

    ARTICLE

    Archimedes Optimization with Deep Learning Based Aerial Image Classification for Cybersecurity Enabled UAV Networks

    Faris Kateb, Mahmoud Ragab*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2171-2185, 2023, DOI:10.32604/csse.2023.039931

    Abstract The recent adoption of satellite technologies, unmanned aerial vehicles (UAVs) and 5G has encouraged telecom networking to evolve into more stable service to remote areas and render higher quality. But, security concerns with drones were increasing as drone nodes have been striking targets for cyberattacks because of immensely weak inbuilt and growing poor security volumes. This study presents an Archimedes Optimization with Deep Learning based Aerial Image Classification and Intrusion Detection (AODL-AICID) technique in secure UAV networks. The presented AODL-AICID technique concentrates on two major processes: image classification and intrusion detection. For aerial image classification, the AODL-AICID technique encompasses MobileNetv2… More >

  • Open Access

    ARTICLE

    A Novel Ensemble Learning System for Cyberattack Classification

    Óscar Mogollón-Gutiérrez*, José Carlos Sancho Núñez, Mar Ávila Vegas, Andrés Caro Lindo

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1691-1709, 2023, DOI:10.32604/iasc.2023.039255

    Abstract Nowadays, IT systems rely mainly on artificial intelligence (AI) algorithms to process data. AI is generally used to extract knowledge from stored information and, depending on the nature of data, it may be necessary to apply different AI algorithms. In this article, a novel perspective on the use of AI to ensure the cybersecurity through the study of network traffic is presented. This is done through the construction of a two-stage cyberattack classification ensemble model addressing class imbalance following a one-vs-rest (OvR) approach. With the growing trend of cyberattacks, it is essential to implement techniques that ensure legitimate access to… More >

  • Open Access

    ARTICLE

    Machine Learning Based Cybersecurity Threat Detection for Secure IoT Assisted Cloud Environment

    Z. Faizal Khan1, Saeed M. Alshahrani2,*, Abdulrahman Alghamdi2, Someah Alangari3, Nouf Ibrahim Altamami4, Khalid A. Alissa5, Sana Alazwari6, Mesfer Al Duhayyim7, Fahd N. Al-Wesabi8

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 855-871, 2023, DOI:10.32604/csse.2023.036735

    Abstract The Internet of Things (IoT) is determine enormous economic openings for industries and allow stimulating innovation which obtain between domains in childcare for eldercare, in health service to energy, and in developed to transport. Cybersecurity develops a difficult problem in IoT platform whereas the presence of cyber-attack requires that solved. The progress of automatic devices for cyber-attack classifier and detection employing Artificial Intelligence (AI) and Machine Learning (ML) devices are crucial fact to realize security in IoT platform. It can be required for minimizing the issues of security based on IoT devices efficiently. Thus, this research proposal establishes novel mayfly… More >

  • Open Access

    ARTICLE

    BIoMT: A Blockchain-Enabled Healthcare Architecture for Information Security in the Internet of Medical Things

    Sahar Badri1, Sana Ullah Jan2,*, Daniyal Alghazzawi1, Sahar Aldhaheri1, Nikolaos Pitropakis2

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3667-3684, 2023, DOI:10.32604/csse.2023.037531

    Abstract Rapid technological advancement has enabled modern healthcare systems to provide more sophisticated and real-time services on the Internet of Medical Things (IoMT). The existing cloud-based, centralized IoMT architectures are vulnerable to multiple security and privacy problems. The blockchain-enabled IoMT is an emerging paradigm that can ensure the security and trustworthiness of medical data sharing in the IoMT networks. This article presents a private and easily expandable blockchain-based framework for the IoMT. The proposed framework contains several participants, including private blockchain, hospital management systems, cloud service providers, doctors, and patients. Data security is ensured by incorporating an attribute-based encryption scheme. Furthermore,… More >

  • Open Access

    ARTICLE

    An Effective Threat Detection Framework for Advanced Persistent Cyberattacks

    So-Eun Jeon1, Sun-Jin Lee1, Eun-Young Lee1, Yeon-Ji Lee2, Jung-Hwa Ryu2, Jung-Hyun Moon2, Sun-Min Yi2, Il-Gu Lee1,2,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4231-4253, 2023, DOI:10.32604/cmc.2023.034287

    Abstract Recently, with the normalization of non-face-to-face online environments in response to the COVID-19 pandemic, the possibility of cyberattacks through endpoints has increased. Numerous endpoint devices are managed meticulously to prevent cyberattacks and ensure timely responses to potential security threats. In particular, because telecommuting, telemedicine, and tele-education are implemented in uncontrolled environments, attackers typically target vulnerable endpoints to acquire administrator rights or steal authentication information, and reports of endpoint attacks have been increasing considerably. Advanced persistent threats (APTs) using various novel variant malicious codes are a form of a sophisticated attack. However, conventional commercial antivirus and anti-malware systems that use signature-based… More >

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