Cybersecurity risks like ransomware attacks, phishing campaigns, data breaches, and zero-day vulnerabilities have significantly increased as a result of the quick expansion of digital infrastructure and internet-based services. For people, organizations, and cybersecurity experts, timely awareness of such threats is essential. However, cybersecurity-related information is frequently presented in complicated technical language and is highly fragmented across multiple online platforms, making it difficult for novices to understand and time-consuming for experts to analyze. Current news aggregation systems lack intelligent analysis, adaptive explanation mechanisms, and career-oriented guidance, instead concentrating on content retrieval. In order to improve cybersecurity awareness and knowledge sharing, this research paper suggests a Security News Intelligence Agent that combines automated web crawling and Large Language Models (LLMs). The suggested system retrieves news articles about cybersecurity. For people, organizations, and cybersecurity experts, timely awareness of such threats is essential. However, cybersecurity-related information is frequently presented in complicated technical language and is highly fragmented across multiple online platforms, making it difficult for novices to understand and time-consuming for experts to analyze. Current news aggregation systems lack intelligent analysis, adaptive explanation mechanisms, and career -oriented guidance, instead concentrating on content retrieval.
Cybersecurity, Web Crawling, Large Language Models, AI Agents, Security News Analysis, Threat Intelligence, Job Recommendation, Artificial Intelligence
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