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  • Open Access


    Application Research on Two-Layer Threat Prediction Model Based on Event Graph

    Shuqin Zhang, Xinyu Su*, Yunfei Han, Tianhui Du, Peiyu Shi

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3993-4023, 2023, DOI:10.32604/cmc.2023.044526

    Abstract Advanced Persistent Threat (APT) is now the most common network assault. However, the existing threat analysis models cannot simultaneously predict the macro-development trend and micro-propagation path of APT attacks. They cannot provide rapid and accurate early warning and decision responses to the present system state because they are inadequate at deducing the risk evolution rules of network threats. To address the above problems, firstly, this paper constructs the multi-source threat element analysis ontology (MTEAO) by integrating multi-source network security knowledge bases. Subsequently, based on MTEAO, we propose a two-layer threat prediction model (TL-TPM) that combines the knowledge graph and the… More >

  • Open Access


    Threat Modeling and Application Research Based on Multi-Source Attack and Defense Knowledge

    Shuqin Zhang, Xinyu Su*, Peiyu Shi, Tianhui Du, Yunfei Han

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 349-377, 2023, DOI:10.32604/cmc.2023.040964

    Abstract Cyber Threat Intelligence (CTI) is a valuable resource for cybersecurity defense, but it also poses challenges due to its multi-source and heterogeneous nature. Security personnel may be unable to use CTI effectively to understand the condition and trend of a cyberattack and respond promptly. To address these challenges, we propose a novel approach that consists of three steps. First, we construct the attack and defense analysis of the cybersecurity ontology (ADACO) model by integrating multiple cybersecurity databases. Second, we develop the threat evolution prediction algorithm (TEPA), which can automatically detect threats at device nodes, correlate and map multi-source threat information,… More >

  • Open Access


    Risk Analysis Using Multi-Source Data for Distribution Networks Facing Extreme Natural Disasters

    Jun Yang*, Nannan Wang, Jiang Wang, Yashuai Luo

    Energy Engineering, Vol.120, No.9, pp. 2079-2096, 2023, DOI:10.32604/ee.2023.028653

    Abstract Distribution networks denote important public infrastructure necessary for people’s livelihoods. However, extreme natural disasters, such as earthquakes, typhoons, and mudslides, severely threaten the safe and stable operation of distribution networks and power supplies needed for daily life. Therefore, considering the requirements for distribution network disaster prevention and mitigation, there is an urgent need for in-depth research on risk assessment methods of distribution networks under extreme natural disaster conditions. This paper accesses multi-source data, presents the data quality improvement methods of distribution networks, and conducts data-driven active fault diagnosis and disaster damage analysis and evaluation using data-driven theory. Furthermore, the paper… More >

  • Open Access


    Multi-Source Data Privacy Protection Method Based on Homomorphic Encryption and Blockchain

    Ze Xu, Sanxing Cao*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 861-881, 2023, DOI:10.32604/cmes.2023.025159

    Abstract Multi-Source data plays an important role in the evolution of media convergence. Its fusion processing enables the further mining of data and utilization of data value and broadens the path for the sharing and dissemination of media data. However, it also faces serious problems in terms of protecting user and data privacy. Many privacy protection methods have been proposed to solve the problem of privacy leakage during the process of data sharing, but they suffer from two flaws: 1) the lack of algorithmic frameworks for specific scenarios such as dynamic datasets in the media domain; 2) the inability to solve… More > Graphic Abstract

    Multi-Source Data Privacy Protection Method Based on Homomorphic Encryption and Blockchain

  • Open Access


    Public Health Emergency Management and Multi-Source Data Technology in China

    Xinzhi Wanga, Yi Liub, Hui Zhanga, Qiuju Maa, Zhidong Caoc

    Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 89-96, 2018, DOI:10.1080/10798587.2016.1267246

    Abstract Public health emergency is governed by the physical rules, which are related to the propagation of diseases in the physical space, and the social rules, which are related to government structures, social behaviors, and social media in cyber space. Effective preparedness and response of public health emergency is strongly related to interoperation, collaboration and cooperation among different levels of government agencies and among different regions, as well as information flow and data mining between agencies and general public. In this paper, we review the technologies using multi-source data for public health emergency in China. At the micro-level, risk analysis and… More >

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