This research evaluates how Large Language Models can transform information-heavy news articles into concise, actionable summaries - particularly valuable for security applications.

• Addresses the critical challenge of information overload in today's digital landscape
• Provides security teams with efficient monitoring of supply chain risks and incidents
• Enables faster identification of security concerns across vast amounts of news content
• Supports compliance monitoring and supply chain resilience through automated analysis

For security professionals, this technology offers a powerful tool to stay informed about emerging threats and supplier incidents without manual review of countless news sources.

Evaluating the Effectiveness of Large Language Models in Automated News Article Summarization