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A security event and analysis method technology, applied in the field of fusion analysis of electronic credential security events, can solve the problems of various forms and massive abnormal data analysis, and achieve accurate results
Inactive Publication Date: 2019-09-24
SHANGHAI JIAO TONG UNIV
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Most of the existing research focuses on the research on text and semantic similarity in natural language. The application of text semantic similarity to entity data in a specific environment needs to consider the production environment for data cleaning, integration and screening, and the electronic credentials of electronic invoices The application of abnormal behaviors is diverse and changeable, and the analysis of massive abnormal data using traditional statistical methods seems to be stretched. In addition, industry and production life involve the use of deep learning methods for similarity analysis of multiple entities with intricate relationships. relatively rare
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Embodiment 1
[0033] A fusion analysis method for electronic credential security events, such as figure 1 , 2 Shown include the following steps:
[0034] S101: data collection;
[0035] S102: data preprocessing;
[0036] S103: feature extraction;
[0037] S104: Fusion computing;
[0038] S105: result output;
[0039] The S104 step includes security event research and judgment and association relationship learning. The security event research and judgment uses the Kmeans clustering algorithm to obtain the alert threshold for security incidents of enterprises or users, and the association relationship learning uses the Skip-gram model to train abnormal behavior corresponding codes. After obtaining the word vectors of abnormal behavior, the cosine similarity is used to calculate the similarity between word vectors, and then the correlation similarity between enterprises and users can be obtained.
[0040] Further, in the step S101, the data acquisition uses sensors to collect analog info...
Embodiment 2
[0048]A fusion analysis method for electronic credential security events. On the basis of Embodiment 1, more specifically, abnormal behaviors of electronic credential are diverse and changeable. For example, there are abnormal behaviors such as multiple password attempts in electronic credential password services. There are abnormal behaviors such as repeated reimbursement of services, abnormal behaviors such as over-limit invoices, super-type invoices, issuance of wrong content or parameter invoices, invalid or red-red invoice reimbursement, over-limit reimbursement and other abnormal behaviors in approved services, wrong reimbursement, false invoice reimbursement, and modification Abnormal behaviors such as invoice reimbursement, other platform invoice reimbursement, system counterfeiting, abnormal circulation, etc., enterprise / personal application systems have abnormal behaviors such as issuing a large number of invoices in a short period of time, issuing a large number of la...
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Abstract
The invention relates to the field of data analysis, discloses an electronic credential security event fusion analysis method, and solves the technical problem of better completing a fusion analysis system task in an electronic credential third-party supervision system. The method comprises the following steps: s101: data acquisition, s102: data preprocessing, s103, feature extraction, S104, fusion calculation and S105, result output; S104 inclues safety event study and judgment and association relationship learning; the safety event study and judgment uses a Kmeans clustering algorithm to obtain a warning threshold value of a safety event of an enterprise or a use; the association relationship learning adopts a Skip-gram model to train a word vector after coding corresponding to an abnormal behavior; after the word vectors of the abnormal behaviors are obtained, the cosine similarity is used for calculating the similarity between the word vectors, and then the association similarity between enterprises and the association similarity between users are obtained. When an enterprise has a relatively concentrated safety event time or a relatively small number of abnormal behaviors, the safety event early warning threshold value algorithm can dynamically study and judge the early warning threshold value and the result is relatively accurate.
Description
technical field [0001] The invention relates to the field of data analysis, more specifically, it relates to a fusion analysis method for electronic credential security events. Background technique [0002] Under the background of the current "Internet +" era, it emphasizes the implementation of the development concept of innovation, coordination, green, openness and sharing. In terms of tax collection and management, the implementation of paperless evidence is the key to improving the tax collection and management methods and improving the work efficiency of functional departments. The inevitable result of modernization and intelligence. [0003] However, the electronic credential service system running in an open environment has the characteristics of business system differentiation and abnormal behavior information multi-source heterogeneity. The abnormal behavior of electronic credential applications is diverse and changeable. In order to ensure the normal operation and ...
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