Is COVID-19 Being Used to Spread Malware.

Area of Science:

• Cybersecurity
• Machine Learning
• Social Media Analysis

Background:

• The COVID-19 pandemic led to increased social media usage, creating opportunities for cybercriminals.
• Twitter's URL auto-shortening feature facilitates the distribution of malicious links within tweets.
• Detecting and mitigating malware propagation through social media is crucial.

Purpose of the Study:

• To collect COVID-19-related tweets from Twitter.
• To extract relevant features from these tweets for analysis.
• To develop machine learning models for identifying malicious tweets.

Main Methods:

• Data collection of COVID-19 tweets from Twitter.
• Feature extraction from tweet content and metadata.
• Development and application of machine learning algorithms for classification.

Main Results:

• Identified key features distinguishing malicious from legitimate tweets.
• Developed a machine learning model capable of detecting malicious tweets with high accuracy.
• Established a foundation for real-time detection and blocking of malware propagation.

Conclusions:

• Machine learning offers an effective approach to combatting malware distribution via social media.
• The study provides a framework for enhancing cybersecurity measures against pandemic-related cyber threats.
• Further research can refine models for more robust and adaptive threat detection.