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https://dspace.ncfu.ru/handle/20.500.12258/25203| Title: | Mathematical Concept of a Model for Processing Metadata of Employee’s Psycho-States for Identifying Him as an Internal Violator (Insider) |
| Authors: | Mandritsa, I. V. Мандрица, И. В. Petrenko, V. I. Петренко, В. И. Minkina, T. V. Минкина, Т. В. |
| Keywords: | Internal intruder;Probability of state;Mathematical model;Metadata collection |
| Issue Date: | 2023 |
| Citation: | Mandritsa, I.V., Petrenko, V.I., Mandritsa, O.V., Minkina, T.V. Mathematical Concept of a Model for Processing Metadata of Employee’s Psycho-States for Identifying Him as an Internal Violator (Insider) // Lecture Notes in Networks and Systems. - 2023. - 702 LNNS, pp. 189-204. - DOI: 10.1007/978-3-031-34127-4_19 |
| Series/Report no.: | Lecture Notes in Networks and Systems |
| Abstract: | The identification of an internal violator is becoming more and more relevant with the development of information processing technologies, the security of technical and software complexes in information systems is increasing, and the person remains the most vulnerable place. An employee who processes information and has full access to it becomes the target of an attacker, as well as he himself may be an intruder and become a source of leakage of confidential information. The analysis of data about the employee allows us to make assumptions about his emotional state, willingness to honestly do the job. The collected data requires analysis according to their type, and this is what the work is dedicated to. Data from video surveillance cameras is analyzed to identify the time of the employee's appearance and his location during working hours. The metadata obtained is intended to create a model of an internal violator, followed by an assessment of the threat level emanating from the employee. |
| URI: | http://hdl.handle.net/20.500.12258/25203 |
| Appears in Collections: | Статьи, проиндексированные в SCOPUS, WOS |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
| scopusresults 2696 .pdf Restricted Access | 132.36 kB | Adobe PDF | View/Open |
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