MUMBAI, India, Sept. 22 -- Intellectual Property India has published a patent application (202547092855 A) filed by Microsoft Technology Licensing, LLC on September 27, 2025, for Finding Semantically Related Security Information.
Inventors include Bulut, Muhammed Fatih; Greenwald, Lloyd Geoffrey; Shah, Aditi Kamlesh; Betthauser, Leo Moreno; Liu, Yingqi; Xia, Ning; and Wang, Siyue.
The application for the patent was published on September 18, 2026, under issue no. 38/2026.
Abstract: Methods and apparatuses for improving the performance and energy efficiency of machine learning systems that generate security specific machine learning models and generate security related information using security specific machine learning models are described. A security specific machine learning model may comprise a security specific large language model (LLM). The security specific LLM may be trained and deployed to generate semantically related security information. The security specific LLM may be pretrained with a security specific data set that was generated using similarity deduplication and long line handling, and with security specific objectives, such as next log line prediction based on host, system, application, and cyber attacker behavior. The security specific large language model may be fine-tuned using a security specific similarity dataset that may be generated to align the security specific LLM to capture similarity between different security events.
Disclaimer: Curated by HT Syndication.
