/plushcap/analysis/mongodb/post-using-generative-ai-mongodb-tackle-cybersecuritys-biggest-challenges-kr

생성형 인공지능과 MongoDB를 사용하여 사이버 보안의 가장 중대한 과제 해결

What's this blog post about?

The article discusses the use of generative AI and MongoDB to address major challenges in cybersecurity. As cyber threats become more sophisticated, detecting and mitigating them becomes increasingly difficult. Additionally, the rapid expansion of digital infrastructure has widened the attack surface, making it harder for security teams to monitor and protect all entry and exit points. Another significant issue is a shortage of skilled cybersecurity professionals globally. Generative AI, which uses large language models (LLMs) to create new data or patterns based on existing datasets, can provide innovative solutions in several key areas. These include advanced threat detection and response, post-event analysis for gaining actionable insights, generating synthetic data for model training without exposing sensitive information, automating phishing detection, and enhancing overall cybersecurity practices. MongoDB enables organizations to build robust real-time cyber defense systems more quickly and efficiently by integrating AI technologies into their infrastructure. It helps manage all types of data securely and provides a document-based architecture for easy modeling of application data and vector embeddings. MongoDB's open architecture is integrated with various AI development frameworks, LLMs, and embedding providers, allowing developers to move seamlessly between different cloud providers and AI technologies without being locked in. Real-world applications of generative AI and MongoDB in cybersecurity include intelligence platforms like ExTrac, which predict public safety risks by analyzing data from thousands of sources, and VISO TRUST, a platform that streamlines third-party security assessments for businesses. To learn more about these use cases, check out the related case studies. To get started with generative AI and MongoDB in cybersecurity, explore Atlas Vector Search Learning Byte, which provides an overview of various use cases and ways to begin implementing this technology within 10 minutes.

Company
MongoDB

Date published
March 13, 2024

Author(s)
Mat Keep, Lena Smart

Word count
1098

Language
한국어

Hacker News points
None found.


By Matt Makai. 2021-2024.