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  • Open Access

    ARTICLE

    An Energy Trading Method Based on Alliance Blockchain and Multi-Signature

    Hongliang Tian, Jiaming Wang*

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1611-1629, 2024, DOI:10.32604/cmc.2023.046698

    Abstract Blockchain, known for its secure encrypted ledger, has garnered attention in financial and data transfer realms, including the field of energy trading. However, the decentralized nature and identity anonymity of user nodes raise uncertainties in energy transactions. The broadcast consensus authentication slows transaction speeds, and frequent single-point transactions in multi-node settings pose key exposure risks without protective measures during user signing. To address these, an alliance blockchain scheme is proposed, reducing the resource-intensive identity verification among nodes. It integrates multi-signature functionality to fortify user resources and transaction security. A novel multi-signature process within this framework involves neutral nodes established through… More >

  • Open Access

    ARTICLE

    Strengthening Network Security: Deep Learning Models for Intrusion Detection with Optimized Feature Subset and Effective Imbalance Handling

    Bayi Xu1, Lei Sun2,*, Xiuqing Mao2, Chengwei Liu3, Zhiyi Ding2

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1995-2022, 2024, DOI:10.32604/cmc.2023.046478

    Abstract In recent years, frequent network attacks have highlighted the importance of efficient detection methods for ensuring cyberspace security. This paper presents a novel intrusion detection system consisting of a data preprocessing stage and a deep learning model for accurately identifying network attacks. We have proposed four deep neural network models, which are constructed using architectures such as Convolutional Neural Networks (CNN), Bi-directional Long Short-Term Memory (BiLSTM), Bidirectional Gate Recurrent Unit (BiGRU), and Attention mechanism. These models have been evaluated for their detection performance on the NSL-KDD dataset.To enhance the compatibility between the data and the models, we apply various preprocessing… More >

  • Open Access

    ARTICLE

    Advanced Optimized Anomaly Detection System for IoT Cyberattacks Using Artificial Intelligence

    Ali Hamid Farea1,*, Omar H. Alhazmi1, Kerem Kucuk2

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1525-1545, 2024, DOI:10.32604/cmc.2023.045794

    Abstract While emerging technologies such as the Internet of Things (IoT) have many benefits, they also pose considerable security challenges that require innovative solutions, including those based on artificial intelligence (AI), given that these techniques are increasingly being used by malicious actors to compromise IoT systems. Although an ample body of research focusing on conventional AI methods exists, there is a paucity of studies related to advanced statistical and optimization approaches aimed at enhancing security measures. To contribute to this nascent research stream, a novel AI-driven security system denoted as “AI2AI” is presented in this work. AI2AI employs AI techniques to… More >

  • Open Access

    ARTICLE

    Machine Learning Security Defense Algorithms Based on Metadata Correlation Features

    Ruchun Jia, Jianwei Zhang*, Yi Lin

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2391-2418, 2024, DOI:10.32604/cmc.2024.044149

    Abstract With the popularization of the Internet and the development of technology, cyber threats are increasing day by day. Threats such as malware, hacking, and data breaches have had a serious impact on cybersecurity. The network security environment in the era of big data presents the characteristics of large amounts of data, high diversity, and high real-time requirements. Traditional security defense methods and tools have been unable to cope with the complex and changing network security threats. This paper proposes a machine-learning security defense algorithm based on metadata association features. Emphasize control over unauthorized users through privacy, integrity, and availability. The… More >

  • Open Access

    ARTICLE

    Do Public Health Events Promote the Prevalence of Adjustment Disorder in College Students? An Example from the COVID-19 Pandemic

    Rong Fu*, Luze Xie

    International Journal of Mental Health Promotion, Vol.26, No.1, pp. 21-30, 2024, DOI:10.32604/ijmhp.2023.041730

    Abstract COVID-19, as one of the most serious sudden public health problems in this century, is a serious threat to people’s mental health. College students, as a vulnerable group, are more likely to develop mental health problems. When the body is unable to adapt to new changes in the environment, the main mental health problem that arises is adjustment disorder. The aim of this study was to assess the prevalence and influencing factors of adjustment disorder among college students during the COVID-19 outbreak in China. Cross-sectional data collected by web-based questionnaires were obtained through convenience sampling and snowball sampling between March… More >

  • Open Access

    REVIEW

    A Review of Lightweight Security and Privacy for Resource-Constrained IoT Devices

    Sunil Kumar1, Dilip Kumar1, Ramraj Dangi2, Gaurav Choudhary3, Nicola Dragoni4, Ilsun You5,*

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 31-63, 2024, DOI:10.32604/cmc.2023.047084

    Abstract The widespread and growing interest in the Internet of Things (IoT) may be attributed to its usefulness in many different fields. Physical settings are probed for data, which is then transferred via linked networks. There are several hurdles to overcome when putting IoT into practice, from managing server infrastructure to coordinating the use of tiny sensors. When it comes to deploying IoT, everyone agrees that security is the biggest issue. This is due to the fact that a large number of IoT devices exist in the physical world and that many of them have constrained resources such as electricity, memory,… More >

  • Open Access

    ARTICLE

    Identification of Important FPGA Modules Based on Complex Network

    Senjie Zhang1,2, Jinbo Wang2,*, Shan Zhou2, Jingpei Wang2,3, Zhenyong Zhang4,*, Ruixue Wang2

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1027-1047, 2024, DOI:10.32604/cmc.2023.046355

    Abstract The globalization of hardware designs and supply chains, as well as the integration of third-party intellectual property (IP) cores, has led to an increased focus from malicious attackers on computing hardware. However, existing defense or detection approaches often require additional circuitry to perform security verification, and are thus constrained by time and resource limitations. Considering the scale of actual engineering tasks and tight project schedules, it is usually difficult to implement designs for all modules in field programmable gate array (FPGA) circuits. Some studies have pointed out that the failure of key modules tends to cause greater damage to the… More >

  • Open Access

    ARTICLE

    Enhancing IoT Security: Quantum-Level Resilience against Threats

    Hosam Alhakami*

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 329-356, 2024, DOI:10.32604/cmc.2023.043439

    Abstract The rapid growth of the Internet of Things (IoT) operations has necessitated the incorporation of quantum computing technologies to meet its expanding needs. This integration is motivated by the need to solve the specific issues provided by the expansion of IoT and the potential benefits that quantum computing can offer in this scenario. The combination of IoT and quantum computing creates new privacy and security problems. This study examines the critical need to prevent potential security concerns from quantum computing in IoT applications. We investigate the incorporation of quantum computing approaches within IoT security frameworks, with a focus on developing… More >

  • Open Access

    ARTICLE

    An Innovative Approach Using TKN-Cryptology for Identifying the Replay Assault

    Syeda Wajiha Zahra1, Muhammad Nadeem2, Ali Arshad3,*, Saman Riaz3, Muhammad Abu Bakr4, Ashit Kumar Dutta5, Zaid Alzaid6, Badr Almutairi7, Sultan Almotairi8

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 589-616, 2024, DOI:10.32604/cmc.2023.042386

    Abstract Various organizations store data online rather than on physical servers. As the number of user’s data stored in cloud servers increases, the attack rate to access data from cloud servers also increases. Different researchers worked on different algorithms to protect cloud data from replay attacks. None of the papers used a technique that simultaneously detects a full-message and partial-message replay attack. This study presents the development of a TKN (Text, Key and Name) cryptographic algorithm aimed at protecting data from replay attacks. The program employs distinct ways to encrypt plain text [P], a user-defined Key [K], and a Secret Code… More >

  • Open Access

    REVIEW

    Fuzzing: Progress, Challenges, and Perspectives

    Zhenhua Yu1, Zhengqi Liu1, Xuya Cong1,*, Xiaobo Li2, Li Yin3

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1-29, 2024, DOI:10.32604/cmc.2023.042361

    Abstract As one of the most effective techniques for finding software vulnerabilities, fuzzing has become a hot topic in software security. It feeds potentially syntactically or semantically malformed test data to a target program to mine vulnerabilities and crash the system. In recent years, considerable efforts have been dedicated by researchers and practitioners towards improving fuzzing, so there are more and more methods and forms, which make it difficult to have a comprehensive understanding of the technique. This paper conducts a thorough survey of fuzzing, focusing on its general process, classification, common application scenarios, and some state-of-the-art techniques that have been… More >

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