Visible to the public Biblio

Filters: Keyword is Network analyzers  [Clear All Filters]
2023-03-17
Lv, Xiaonan, Huang, Zongwei, Sun, Liangyu, Wu, Miaomiao, Huang, Li, Li, Yehong.  2022.  Research and design of web-based capital transaction data dynamic multi-mode visual analysis tool. 2022 IEEE 7th International Conference on Smart Cloud (SmartCloud). :165–170.
For multi-source heterogeneous complex data types of data cleaning and visual display, we proposed to build dynamic multimode visualization analysis tool, according to the different types of data designed by the user in accordance with the data model, and use visualization technology tools to build and use CQRS technology to design, external interface using a RESTFul architecture, The domain model and data query are completely separated, and the underlying data store adopts Hbase, ES and relational database. Drools is adopted in the data flow engine. According to the internal algorithm, three kinds of graphs can be output, namely, transaction relationship network analysis graph, capital flow analysis graph and transaction timing analysis graph, which can reduce the difficulty of analysis and help users to analyze data in a more friendly way
2022-08-26
Lv, Huiying, Zhang, Yuan, Li, Huan, Chang, Wenjun.  2021.  Security Assessment of Enterprise Networks Based on Analytic Network Process and Evidence Theory. 2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture (AIAM). :305—313.

Network security has always been the most important of enterprise informatization construction and development, and the security assessment of network system is the basis for enterprises to make effective security defense strategies. Aiming at the relevance of security factors and subjectivity of evaluation results in the process of enterprise network system security assessment, a security assessment method combining Analytic Network Process and evidence theory is proposed. Firstly, we built a complete security assessment index system and network analysis structure model for enterprise network, and determined the converged security index weights by calculating hypermatrix, limit hypermatrix and stable limit hypermatrix; then, we used the evidence theory on data fusion of the evaluation opinions of multiple experts to eliminate the conflict between evidences. Finally, according to the principle of maximum membership degree, we realized the assessment of enterprise network security level using weighted average. The example analysis showed that the model not only weighed the correlation influence among the security indicators, but also effectively reduced the subjectivity of expert evaluation and the fuzziness and uncertainty in qualitative analysis, which verified the effectiveness of the model and method, and provided an important basis for network security management.

2022-08-12
Aguinaldo, Roberto Daniel, Solano, Geoffrey, Pontiveros, Marc Jermaine, Balolong, Marilen Parungao.  2021.  NAMData: A Web-application for the Network Analysis of Microbiome Data. TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON). :341–346.
Recent projects regarding the exploration of the functions of microbiomes within communities brought about a plethora of new data. That specific field of study is called Metagenomics and one of its more advancing approach is the application of network analysis. The paper introduces NAMData which is a web-application tool for the network analysis of microbiome data. The system handles the compositionality and sparsity nature of microbiome data by applying taxa filtration, normalization, and zero treatment. Furthermore, compositionally aware correlation estimators were used to compute for the correlation between taxa and the system divides the network into the positive and negative correlation network. NAMData aims to capitalize on the unique network features namely network visualization, centrality scores, and community detection. The system enables researchers to include network analysis in their analysis pipelines even without any knowledge of programming. Biological concepts can be integrated with the network findings gathered from the system to either support existing facts or form new insights.