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  • Open Access

    ARTICLE

    Unknown DDoS Attack Detection with Fuzzy C-Means Clustering and Spatial Location Constraint Prototype Loss

    Thanh-Lam Nguyen1, Hao Kao1, Thanh-Tuan Nguyen2, Mong-Fong Horng1,*, Chin-Shiuh Shieh1,*

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2181-2205, 2024, DOI:10.32604/cmc.2024.047387

    Abstract Since its inception, the Internet has been rapidly evolving. With the advancement of science and technology and the explosive growth of the population, the demand for the Internet has been on the rise. Many applications in education, healthcare, entertainment, science, and more are being increasingly deployed based on the internet. Concurrently, malicious threats on the internet are on the rise as well. Distributed Denial of Service (DDoS) attacks are among the most common and dangerous threats on the internet today. The scale and complexity of DDoS attacks are constantly growing. Intrusion Detection Systems (IDS) have been deployed and have demonstrated… More >

  • Open Access

    ARTICLE

    IoT Smart Devices Risk Assessment Model Using Fuzzy Logic and PSO

    Ashraf S. Mashaleh1,2,*, Noor Farizah Binti Ibrahim1, Mohammad Alauthman3, Mohammad Almseidin4, Amjad Gawanmeh5

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2245-2267, 2024, DOI:10.32604/cmc.2023.047323

    Abstract Increasing Internet of Things (IoT) device connectivity makes botnet attacks more dangerous, carrying catastrophic hazards. As IoT botnets evolve, their dynamic and multifaceted nature hampers conventional detection methods. This paper proposes a risk assessment framework based on fuzzy logic and Particle Swarm Optimization (PSO) to address the risks associated with IoT botnets. Fuzzy logic addresses IoT threat uncertainties and ambiguities methodically. Fuzzy component settings are optimized using PSO to improve accuracy. The methodology allows for more complex thinking by transitioning from binary to continuous assessment. Instead of expert inputs, PSO data-driven tunes rules and membership functions. This study presents a… More >

  • Open Access

    ARTICLE

    Cybersecurity Threats Detection Using Optimized Machine Learning Frameworks

    Nadir Omer1,*, Ahmed H. Samak2, Ahmed I. Taloba3,4, Rasha M. Abd El-Aziz3,5

    Computer Systems Science and Engineering, Vol.48, No.1, pp. 77-95, 2024, DOI:10.32604/csse.2023.039265

    Abstract Today’s world depends on the Internet to meet all its daily needs. The usage of the Internet is growing rapidly. The world is using the Internet more frequently than ever. The hazards of harmful attacks have also increased due to the growing reliance on the Internet. Hazards to cyber security are actions taken by someone with malicious intent to steal data, destroy computer systems, or disrupt them. Due to rising cyber security concerns, cyber security has emerged as the key component in the fight against all online threats, forgeries, and assaults. A device capable of identifying network irregularities and cyber-attacks… More >

  • Open Access

    ARTICLE

    Enhancing Healthcare Data Security and Disease Detection Using Crossover-Based Multilayer Perceptron in Smart Healthcare Systems

    Mustufa Haider Abidi*, Hisham Alkhalefah, Mohamed K. Aboudaif

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 977-997, 2024, DOI:10.32604/cmes.2023.044169

    Abstract The healthcare data requires accurate disease detection analysis, real-time monitoring, and advancements to ensure proper treatment for patients. Consequently, Machine Learning methods are widely utilized in Smart Healthcare Systems (SHS) to extract valuable features from heterogeneous and high-dimensional healthcare data for predicting various diseases and monitoring patient activities. These methods are employed across different domains that are susceptible to adversarial attacks, necessitating careful consideration. Hence, this paper proposes a crossover-based Multilayer Perceptron (CMLP) model. The collected samples are pre-processed and fed into the crossover-based multilayer perceptron neural network to detect adversarial attacks on the medical records of patients. Once an… More >

  • Open Access

    ARTICLE

    Multiclass Classification for Cyber Threats Detection on Twitter

    Adnan Hussein1, Abdulwahab Ali Almazroi2,*

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3853-3866, 2023, DOI:10.32604/cmc.2023.040856

    Abstract The advances in technology increase the number of internet systems usage. As a result, cybersecurity issues have become more common. Cyber threats are one of the main problems in the area of cybersecurity. However, detecting cybersecurity threats is not a trivial task and thus is the center of focus for many researchers due to its importance. This study aims to analyze Twitter data to detect cyber threats using a multiclass classification approach. The data is passed through different tasks to prepare it for the analysis. Term Frequency and Inverse Document Frequency (TFIDF) features are extracted to vectorize the cleaned data… More >

  • Open Access

    ARTICLE

    Phishing Website URL’s Detection Using NLP and Machine Learning Techniques

    Dinesh Kalla1,*, Sivaraju Kuraku2

    Journal on Artificial Intelligence, Vol.5, pp. 145-162, 2023, DOI:10.32604/jai.2023.043366

    Abstract Phishing websites present a severe cybersecurity risk since they can lead to financial losses, data breaches, and user privacy violations. This study uses machine learning approaches to solve the problem of phishing website detection. Using artificial intelligence, the project aims to provide efficient techniques for locating and thwarting these dangerous websites. The study goals were attained by performing a thorough literature analysis to investigate several models and methods often used in phishing website identification. Logistic Regression, K-Nearest Neighbors, Decision Trees, Random Forests, Support Vector Classifiers, Linear Support Vector Classifiers, and Naive Bayes were all used in the inquiry. This research… More >

  • Open Access

    ARTICLE

    Chinese Cyber Threat Intelligence Named Entity Recognition via RoBERTa-wwm-RDCNN-CRF

    Zhen Zhen1, Jian Gao1,2,*

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 299-323, 2023, DOI:10.32604/cmc.2023.042090

    Abstract In recent years, cyber attacks have been intensifying and causing great harm to individuals, companies, and countries. The mining of cyber threat intelligence (CTI) can facilitate intelligence integration and serve well in combating cyber attacks. Named Entity Recognition (NER), as a crucial component of text mining, can structure complex CTI text and aid cybersecurity professionals in effectively countering threats. However, current CTI NER research has mainly focused on studying English CTI. In the limited studies conducted on Chinese text, existing models have shown poor performance. To fully utilize the power of Chinese pre-trained language models (PLMs) and conquer the problem… More >

  • Open Access

    ARTICLE

    Solar Power Plant Network Packet-Based Anomaly Detection System for Cybersecurity

    Ju Hyeon Lee1, Jiho Shin2, Jung Taek Seo3,*

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 757-779, 2023, DOI:10.32604/cmc.2023.039461

    Abstract As energy-related problems continue to emerge, the need for stable energy supplies and issues regarding both environmental and safety require urgent consideration. Renewable energy is becoming increasingly important, with solar power accounting for the most significant proportion of renewables. As the scale and importance of solar energy have increased, cyber threats against solar power plants have also increased. So, we need an anomaly detection system that effectively detects cyber threats to solar power plants. However, as mentioned earlier, the existing solar power plant anomaly detection system monitors only operating information such as power generation, making it difficult to detect cyberattacks.… More >

  • 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 >

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