Peer-reviewed articles 17,970 +



Title: MODEL OF ASSOCIATIVE MEMORY IN A BIG DATA PROCESSING ENVIRONMENT

MODEL OF ASSOCIATIVE MEMORY IN A BIG DATA PROCESSING ENVIRONMENT
I. V. Kalinin; V. A. Sevostyanov
10.5593/sgem2024/2.1
1314-2704
English
24
2.1
•    Prof. DSc. Oleksandr Trofymchuk, UKRAINE 
•    Prof. Dr. hab. oec. Baiba Rivza, LATVIA
In the modern world, neural networks are becoming an integral part of human life. In particular, neural networks began to be used for the task of constructing information security tools; in connection with this, the need gradually began to arise to strengthen and improve the mechanisms of artificial intelligence itself, including when using big data technology.
Let's consider the basic concepts of working with Big Data technology, in particular the processing of assimilation memory to build a general visual picture of the current situation of the presence of user agents and software. The assimilative memory model is an important component that evaluates the state of the system, remembers events, produces correlation indicators, and accumulates information for a potential intellectual intrusion detection system.
The constructed associative memory can be used to build, for example, efficient structures of on-board geoinformation databases, especially when used in autonomous vehicles (for example, UAVs). The use of an intrusion detection system to protect on-board geoinformation databases in vehicles can improve the security and integrity of data.
[1] Shterenberg, S. I. design of the architecture of an intrusion detection system with deep and machine learning based on the quasi-biological paradigm / S. I. Shterenberg, O. I. Shelukhin, A. D. Lebedeva // Bulletin of the St. Petersburg State University of Technology and Design. Series 1: Natural and technical sciences. – 2023. – No. 1. – P. 86-91.
[2] Shterenberg S.I. Development of a methodology for protecting artificial intelligence systems in distributed information systems. // Bulletin of SibGUTI. 2023;17(3): pp. 78-86.
[3] Krasov A.V., Shterenberg S.I., Goluzina D.R. Methods for visualizing big data in information security systems for generating vulnerability reports // Electrosvyaz. 2019. No. 11. pp. 39-47.
[4] Shterenberg S.I. Methodology for managing systems for processing and collecting big data with monitoring support by built-in software agents // Bulletin of the St. Petersburg State University of Technology and Design. Series 1: Natural and technical sciences. 2020. No. 4. pp. 26-35.
conference
Proceedings of 24th International Multidisciplinary Scientific GeoConference SGEM 2024
24th International Multidisciplinary Scientific GeoConference SGEM 2024, 1 - 7 July, 2024
Proceedings Paper
STEF92 Technology
International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM
SWS Scholarly Society; Acad Sci Czech Republ; Latvian Acad Sci; Polish Acad Sci; Russian Acad Sci; Serbian Acad Sci and Arts; Natl Acad Sci Ukraine; Natl Acad Sci Armenia; Sci Council Japan; European Acad Sci, Arts and Letters; Acad Fine Arts Zagreb Croatia; Croatian Acad Sci and Arts; Acad Sci Moldova; Montenegrin Acad Sci and Arts; Georgian Acad Sci; Acad Fine Arts and Design Bratislava; Russian Acad Arts; Turkish Acad Sci.
59-64
1 - 7 July, 2024
website
9920
intrusion detection system, neural networks, artifi

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