Unveiling Hidden Patterns in T-Pot Honeypot Logs: A Latent Topic Analysis

This paper uses latent topic analysis in T-Pot honey-pot logs to uncover hidden cyberattack patterns. By meticulously analyzing the data, we identified specific attack types targeting various honeypots, such as spam/phishing on Mailoney and malware execution on Android systems. Our findings advocate for organizing identified attack terms into n-grams for stronger cybersecurity measures. Geographical analysis highlighted distinct attack patterns across countries. Russia and the Netherlands showed spam/phishing tendencies, Romania exhibited malicious downloads and execution-oriented attacks, and Germany indicated mobile-centric threats. Additionally, SSH attacks originated pre-dominantly from Asian countries such as Japan, China, India, and Singapore. Examining IP addresses hinted at potential correlations among attackers, suggesting shared entities behind certain attacks, valuable for comprehensive investigations. In conclusion, leveraging LDA on honeypot logs provided nuanced insights into various attack types, helping to identify phishing, malware, and execution-based threats. These findings offer a more targeted approach for analysts, eliminating the need for extensive manual data sifting and improving threat detection and cybersecurity strategies.

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Publication Details

Published
2024-10-16
DOI
https://doi.org/10.1109/isctrkiye64784.2024.10779210
Citations
1
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Video Analysis and Summarization
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article
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0.25
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article

Unveiling Hidden Patterns in T-Pot Honeypot Logs: A Latent Topic Analysis

Cagri Burak Aslan, Mustafa Serkan Öztürk, Eftun Türkşanlı, R. Emre Erkan et al.
1 citations
Video Analysis and Summarization
0.25
article

Unveiling Hidden Patterns in T-Pot Honeypot Logs: A Latent Topic Analysis

Cagri Burak Aslan, Mustafa Serkan Öztürk, Eftun Türkşanlı, R. Emre Erkan, Cüneyt Akdeniz
article en
1 citations

Abstract

This paper uses latent topic analysis in T-Pot honey-pot logs to uncover hidden cyberattack patterns. By meticulously analyzing the data, we identified specific attack types targeting various honeypots, such as spam/phishing on Mailoney and malware execution on Android systems. Our findings advocate for organizing identified attack terms into n-grams for stronger cybersecurity measures. Geographical analysis highlighted distinct attack patterns across countries. Russia and the Netherlands showed spam/phishing tendencies, Romania exhibited malicious downloads and execution-oriented attacks, and Germany indicated mobile-centric threats. Additionally, SSH attacks originated pre-dominantly from Asian countries such as Japan, China, India, and Singapore. Examining IP addresses hinted at potential correlations among attackers, suggesting shared entities behind certain attacks, valuable for comprehensive investigations. In conclusion, leveraging LDA on honeypot logs provided nuanced insights into various attack types, helping to identify phishing, malware, and execution-based threats. These findings offer a more targeted approach for analysts, eliminating the need for extensive manual data sifting and improving threat detection and cybersecurity strategies.

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Video Analysis and Summarization
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