A Multidisciplinary Approach to Telegram Data Analysis

TL;DR

This paper develops a multidisciplinary framework combining neural networks, machine learning, sentiment analysis, and entity recognition to improve early detection of cyber threats on Telegram, addressing data volume and noise challenges.

Contribution

It introduces an integrated analytical approach that enhances cyber threat detection on Telegram by combining multiple advanced techniques for the first time.

Findings

Neural networks outperform traditional methods in threat classification.

Sentiment analysis provides valuable context for threat assessment.

The combined approach improves early warning accuracy.

Abstract

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.