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  • Open Access

    ARTICLE

    VMCTE: Visualization-Based Malware Classification Using Transfer and Ensemble Learning

    Zhiguo Chen1,2,*, Jiabing Cao1,2
    CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2023.038639
    Abstract The Corona Virus Disease 2019 (COVID-19) effect has made telecommuting and remote learning the norm. The growing number of Internet-connected devices provides cyber attackers with more attack vectors. The development of malware by criminals also incorporates a number of sophisticated obfuscation techniques, making it difficult to classify and detect malware using conventional approaches. Therefore, this paper proposes a novel visualization-based malware classification system using transfer and ensemble learning (VMCTE). VMCTE has a strong anti-interference ability. Even if malware uses obfuscation, fuzzing, encryption, and other techniques to evade detection, it can be accurately classified into its corresponding malware family. Unlike traditional… More >

  • Open Access

    ARTICLE

    Advanced DAG-Based Ranking (ADR) Protocol for Blockchain Scalability

    Tayyaba Noreen1,*, Qiufen Xia1, Muhammad Zeeshan Haider2
    CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2023.036139
    Abstract In the past decade, blockchain has evolved as a promising solution to develop secure distributed ledgers and has gained massive attention. However, current blockchain systems face the problems of limited throughput, poor scalability, and high latency. Due to the failure of consensus algorithms in managing nodes’identities, blockchain technology is considered inappropriate for many applications, e.g., in IoT environments, because of poor scalability. This paper proposes a blockchain consensus mechanism called the Advanced DAG-based Ranking (ADR) protocol to improve blockchain scalability and throughput. The ADR protocol uses the directed acyclic graph ledger, where nodes are placed according to their ranking positions… More >

  • Open Access

    ARTICLE

    Dark Forest Algorithm: A Novel Metaheuristic Algorithm for Global Optimization Problems

    Dongyang Li1, Shiyu Du2,*, Yiming Zhang2, Meiting Zhao3
    CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2023.035911
    Abstract Metaheuristic algorithms, as effective methods for solving optimization problems, have recently attracted considerable attention in science and engineering fields. They are popular and have broad applications owing to their high efficiency and low complexity. These algorithms are generally based on the behaviors observed in nature, physical sciences, or humans. This study proposes a novel metaheuristic algorithm called dark forest algorithm (DFA), which can yield improved optimization results for global optimization problems. In DFA, the population is divided into four groups: highest civilization, advanced civilization, normal civilization, and low civilization. Each civilization has a unique way of iteration. To verify DFA’s… More >

  • Open Access

    ARTICLE

    MEC-IoT-Healthcare: Analysis and Prospects

    Hongyuan Wang1, Mohammed Dauwed2, Imran Khan3, Nor Samsiah Sani4,*, Hasmila Amirah Omar4, Hirofumi Amano5, Samih M. Mostafa6
    CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2022.030958
    Abstract Physical sensors, intelligent sensors, and output recommendations are all examples of smart health technology that can be used to monitor patients’ health and change their behavior. Smart health is an Internet-of-Things (IoT)-aware network and sensing infrastructure that provides real-time, intelligent, and ubiquitous healthcare services. Because of the rapid development of cloud computing, as well as related technologies such as fog computing, smart health research is progressively moving in the right direction. Cloud, fog computing, IoT sensors, blockchain, privacy and security, and other related technologies have been the focus of smart health research in recent years. At the moment, the focus… More >

  • Open Access

    ARTICLE

    An Energy-Efficient Protocol for Internet of Things Based Wireless Sensor Networks

    Mohammed Mubarak Mustafa1, Ahmed Abelmonem Khalifa2,3, Korhan Cengiz4,5, Nikola Ivković6,*
    CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2023.036275
    Abstract The performance of Wireless Sensor Networks (WSNs) is an important fragment of the Internet of Things (IoT), where the current WSNbuilt IoT network’s sensor hubs are enticing due to their critical resources. By grouping hubs, a clustering convention offers a useful solution for ensuring energy-saving of hubs and Hybrid Media Access Control (HMAC) during the course of the organization. Nevertheless, current grouping standards suffer from issues with the grouping structure that impacts the exhibition of these conventions negatively. In this investigation, we recommend an Improved Energy-Proficient Algorithm (IEPA) for HMAC throughout the lifetime of the WSN-based IoT. Three consecutive segments… More >

  • Open Access

    ARTICLE

    Classifying Misinformation of User Credibility in Social Media Using Supervised Learning

    Muhammad Asfand-e-Yar1,*, Qadeer Hashir1,*, Syed Hassan Tanvir1, Wajeeha Khalil2
    CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2023.034741
    Abstract The growth of the internet and technology has had a significant effect on social interactions. False information has become an important research topic due to the massive amount of misinformed content on social networks. It is very easy for any user to spread misinformation through the media. Therefore, misinformation is a problem for professionals, organizers, and societies. Hence, it is essential to observe the credibility and validity of the News articles being shared on social media. The core challenge is to distinguish the difference between accurate and false information. Recent studies focus on News article content, such as News titles… More >