Neural network for analysis of additional authentication behavioral biometrie characteristics

Ivutin, Alexey; Savenkov, Pavel A.; Veselova, Aleksandra V.

doi:10.1109/meco.2018.8406032

Cited by 5 publications

(1 citation statement)

References 3 publications

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“…Due to the application of various algorithms and methods of data analysis and machine learning in mobile UBA it has been possible to improve the informativity of the resulting data. Early anomaly detection will allow the system administrator to make balanced management decisions, reduce operational costs, and increase enterprise competitiveness [8].…”

Section: Correct/incorrect Identificationmentioning

confidence: 99%

Methods of Machine Learning in System Abnormal Behavior Detection

Savenkov

Ivutin

2020

Lecture Notes in Computer Science

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The aim of the research is to develop mathematical and program support for detecting abnormal behavior of users. It will be based on analysis of their behavioral biometric characteristics. One of the major problems in UEBA/DSS intelligent systems is obtaining useful information from a large amount of unstructured, inconsistent data. Management decision-making should be based on real data collected from the analysed feature. However, based on the information received, it is rather difficult to make any management decision, as the data are heterogeneous and their volumes are extremely large. Application of machine learning methods in implementation of mobile UEBA/DSS system is proposed. This will make it possible to achieve a data analysis high quality and find complex dependencies in it. A list of the most significant factors submitted to the input of the analysing methods was formed during the research.

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Section: Correct/incorrect Identificationmentioning

confidence: 99%