Daniel Alfasi

Reichman University

Herzliya, Israel.

Hello, I’m Daniel Alfasi, a Data Scientist at CyberArk and a researcher at DEEPNESS-Lab. My interests revolve around solving real-world problems in cybersecurity using deep-learning methods. In addition, I’m interested in Knowledge graph reasoning, NLP methods, and generative AI.

Feel free to reach out to me if you want to discuss my research, have any questions, or are interested in collaborating.

news

Oct 2, 2023	Redefining “libwebp” Vulnerability Scoping with LLMs and Knowledge Graphs
Jun 9, 2023	Next-Generation Security Entity Linkage - SYSTOR 23'
Apr 18, 2023	Our Research Poster Accepted for SYSTOR 23’ Conference!

selected publications

Next-Generation Security Entity Linkage: Harnessing the Power of Knowledge Graphs and Large Language Models

Anat Bremler-Barr, Tal Shapira, and Daniel Alfasi

In Proceedings of the 16th ACM International Systems and Storage Conference (SYSTOR), 2023

Abs PDF

With the continuous increase in reported Common Vulnerabilities and Exposures (CVEs), security teams are overwhelmed by vast amounts of data, which are often analyzed manually, leading to a slow and inefficient process. To address cybersecurity threats effectively, it is essential to establish connections across multiple security entity databases, including CVEs, Common Weakness Enumeration (CWEs), and Common Attack Pattern Enumeration and Classification (CAPECs). In this study, we introduce a new approach that leverages the RotatE knowledge graph embedding model, initialized with embeddings from Ada language model developed by OpenAI. Additionally, we extend this approach by initializing the embeddings for the relations.