Methods for detecting software implants in corporate networks

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F25840886%3A_____%2F24%3AN0000010" target="_blank" >RIV/25840886:_____/24:N0000010 - isvavai.cz</a>
Result on the web
<a href="https://ceur-ws.org/Vol-3675/paper20.pdf" target="_blank" >https://ceur-ws.org/Vol-3675/paper20.pdf</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Methods for detecting software implants in corporate networks
Original language description
With innovations in the technological sphere, the development of mechanisms that allow obtaining confidential information without the proper authorization of the owner is increasing. One of such mechanisms is software implants. This type of software is very difficult to detect because it does not use specialized signatures or code obfuscation, making it difficult to detect. This paper proposes a software implant detection system based on recurrent neural networks and a classifier. The classifier is a mechanism that describes the operating behavior of the software and provides the recurrent neural network with the ability to learn. This mechanism helps to identify behavioral patterns characteristic of software implants and notify the user of the possible risk of data loss. During the experiments, it was found that in order to successfully detect a software implant that initiates the creation of additional processes, the system needs to be trained for 50 epochs. Thus, the detection efficiency is 97.50%, which indicates the possibility of using this system as an effective mechanism for detecting software implants in corporate systems. Given the results obtained, it can be recommended for use in a wide range of information systems to ensure reliable protection against potential security threats.
Czech name
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Czech description
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Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
IntelITSIS’2024: 5th International Workshop on Intelligent Information Technologies and Systems of Information Security, March 28, 2024
ISBN
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ISSN
1613-0073
e-ISSN
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Number of pages
15
Pages from-to
270–284
Publisher name
CEUR
Place of publication
Khmelnytskyi, Ukraine
Event location
Khmelnytskyi, Ukraine
Event date
Mar 28, 2024
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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