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  • Open Access


    A Network Security Risk Assessment Method Based on a B_NAG Model

    Hui Wang1, Chuanhan Zhu1, Zihao Shen1,*, Dengwei Lin2, Kun Liu1, MengYao Zhao3

    Computer Systems Science and Engineering, Vol.38, No.1, pp. 103-117, 2021, DOI:10.32604/csse.2021.014680

    Abstract Computer networks face a variety of cyberattacks. Most network attacks are contagious and destructive, and these types of attacks can be harmful to society and computer network security. Security evaluation is an effective method to solve network security problems. For accurate assessment of the vulnerabilities of computer networks, this paper proposes a network security risk assessment method based on a Bayesian network attack graph (B_NAG) model. First, a new resource attack graph (RAG) and the algorithm E-Loop, which is applied to eliminate loops in the B_NAG, are proposed. Second, to distinguish the confusing relationships between nodes of the attack graph… More >

  • Open Access


    A Recommendation Approach Based on Bayesian Networks for Clone Refactor

    Ye Zhai1, *, Dongsheng Liu1, Celimuge Wu2, Rongrong She1

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1999-2012, 2020, DOI:10.32604/cmc.2020.09950

    Abstract Reusing code fragments by copying and pasting them with or without minor adaptation is a common activity in software development. As a result, software systems often contain sections of code that are very similar, called code clones. Code clones are beneficial in reducing software development costs and development risks. However, recent studies have indicated some negative impacts as a result. In order to effectively manage and utilize the clones, we design an approach for recommending refactoring clones based on a Bayesian network. Firstly, clone codes are detected from the source code. Secondly, the clones that need to be refactored are… More >

  • Open Access


    A Novel Probabilistic Hybrid Model to Detect Anomaly in Smart Homes

    Sasan Saqaeeyan1, Hamid Haj Seyyed Javadi1,2,*, Hossein Amirkhani1,3

    CMES-Computer Modeling in Engineering & Sciences, Vol.121, No.3, pp. 815-834, 2019, DOI:10.32604/cmes.2019.07848

    Abstract Anomaly detection in smart homes provides support to enhance the health and safety of people who live alone. Compared to the previous studies done on this topic, less attention has been given to hybrid methods. This paper presents a two-steps hybrid probabilistic anomaly detection model in the smart home. First, it employs various algorithms with different characteristics to detect anomalies from sensory data. Then, it aggregates their results using a Bayesian network. In this Bayesian network, abnormal events are detected through calculating the probability of abnormality given anomaly detection results of base methods. Experimental evaluation of a real dataset indicates… More >

  • Open Access


    Tibetan Multi-Dialect Speech Recognition Using Latent Regression Bayesian Network and End-To-End Mode

    Yue Zhao1, Jianjian Yue1, Wei Song1,*, Xiaona Xu1, Xiali Li1, Licheng Wu1, Qiang Ji2

    Journal on Internet of Things, Vol.1, No.1, pp. 17-23, 2019, DOI:10.32604/jiot.2019.05866

    Abstract We proposed a method using latent regression Bayesian network (LRBN) to extract the shared speech feature for the input of end-to-end speech recognition model. The structure of LRBN is compact and its parameter learning is fast. Compared with Convolutional Neural Network, it has a simpler and understood structure and less parameters to learn. Experimental results show that the advantage of hybrid LRBN/Bidirectional Long Short-Term Memory-Connectionist Temporal Classification architecture for Tibetan multi-dialect speech recognition, and demonstrate the LRBN is helpful to differentiate among multiple language speech sets. More >

  • Open Access


    Uncertain Knowledge Reasoning Based on the Fuzzy Multi Entity Bayesian Networks

    Dun Li1, Hong Wu1, Jinzhu Gao2, Zhuoyun Liu1, Lun Li1, Zhiyun Zheng1,*

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 301-321, 2019, DOI:10.32604/cmc.2019.05953

    Abstract With the rapid development of the semantic web and the ever-growing size of uncertain data, representing and reasoning uncertain information has become a great challenge for the semantic web application developers. In this paper, we present a novel reasoning framework based on the representation of fuzzy PR-OWL. Firstly, the paper gives an overview of the previous research work on uncertainty knowledge representation and reasoning, incorporates Ontology into the fuzzy Multi Entity Bayesian Networks theory, and introduces fuzzy PR-OWL, an Ontology language based on OWL2. Fuzzy PR-OWL describes fuzzy semantics and uncertain relations and gives grammatical definition and semantic interpretation. Secondly,… More >

  • Open Access


    Multi-Label Learning Based on Transfer Learning and Label Correlation

    Kehua Yang1,*, Chaowei She1, Wei Zhang1, Jiqing Yao2, Shaosong Long1

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 155-169, 2019, DOI:10.32604/cmc.2019.05901

    Abstract In recent years, multi-label learning has received a lot of attention. However, most of the existing methods only consider global label correlation or local label correlation. In fact, on the one hand, both global and local label correlations can appear in real-world situation at same time. On the other hand, we should not be limited to pairwise labels while ignoring the high-order label correlation. In this paper, we propose a novel and effective method called GLLCBN for multi-label learning. Firstly, we obtain the global label correlation by exploiting label semantic similarity. Then, we analyze the pairwise labels in the label… More >

  • Open Access


    Improve Computer Visualization of Architecture Based on the Bayesian Network

    Tao Shen1,*, Yukari Nagai1, Chan Gao2

    CMC-Computers, Materials & Continua, Vol.58, No.2, pp. 307-318, 2019, DOI:10.32604/cmc.2019.04876

    Abstract Computer visualization has marvelous effects when it is applied in various fields, especially in architectural design. As an emerging force in the innovation industry, architects and design agencies have already demonstrated the value of architectural visual products in actual application projects. Based on the digital image technology, virtual presentation of future scenes simulates architecture design, architectural renderings and multimedia videos. Therefore, it can help design agencies transform the theoretical design concept into a lively and realistic visual which can provide the audience with a clearer understanding of the engineering and construction projects. However, it is challenging for designers to produce… More >

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