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Title: A MULTIDISCIPLINARY APPROACH TO TELEGRAM DATA ANALYSIS
A MULTIDISCIPLINARY APPROACH TO TELEGRAM DATA ANALYSIS

PlumX Article Metrics by Elsevier
Velizar Varbanov; Kalin Kopanov; Tatiana Atanasova
10.5593/sgem2024/2.1/s07.01
10.5593/sgem2024/2.1
1314-2704
978-619-7603-69-9
English
24
2.1
•    Prof. DSc. Oleksandr Trofymchuk, UKRAINE 
•    Prof. Dr. hab. oec. Baiba Rivza, LATVIA
Informatics
This paper presents a multidisciplinary approach to analyzing data from Telegram for early warning information regarding cyber threats. With the proliferation of hacktivist groups utilizing Telegram to disseminate information regarding future cyberattacks or to boast about successful ones, the need for effective data analysis methods is paramount. The primary challenge lies in the vast number of channels and the overwhelming volume of data, necessitating advanced techniques for discerning pertinent risks amidst the noise. To address this challenge, we employ a combination of neural network architectures and traditional machine learning algorithms. These methods are utilized to classify and identify potential cyber threats within the Telegram data. Additionally, sentiment analysis and entity recognition techniques are incorporated to provide deeper insights into the nature and context of the communicated information.
The study evaluates the effectiveness of each method in detecting and categorizing cyber threats, comparing their performance and identifying areas for improvement. By leveraging these diverse analytical tools, we aim to enhance early warning systems for cyber threats, enabling more proactive responses to potential security breaches. This research contributes to the ongoing efforts to bolster cybersecurity measures in an increasingly interconnected digital landscape.
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Section Informatics https://doi.org/10.5593/sgem2024/2.1/s07.01
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This work was partly supported by the National Science Program “Security and Defense”, which has received funding from the Ministry of Education and Science of the Republic of Bulgaria under the grant agreement No. Д01-74/19.05.2022.
conference
https://doi.org/10.5593/sgem2024/2.1/s07.01
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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.
3-10
1 - 7 July, 2024
website
9913
Machine Learning, FNN, LSTM, SVM, Cyber Security

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