Henderson, NV, United States of America

Terry Liggett


Average Co-Inventor Count = 5.0

ph-index = 1


Company Filing History:


Years Active: 2025

where 'Filed Patents' based on already Granted Patents

1 patent (USPTO):

Title: Innovations by Terry Liggett in Endpoint Detection and Response Systems

Introduction

Terry Liggett is an accomplished inventor based in Henderson, NV (US). She has made significant contributions to the field of cybersecurity, particularly in the area of endpoint detection and response (EDR) systems. Her innovative approach utilizes machine learning to enhance threat response mechanisms.

Latest Patents

Terry Liggett holds a patent for the invention titled "Auto-detection of observables and auto-disposition of alerts in an endpoint detection and response (EDR) system using machine learning." This technique addresses the challenges associated with threat response in EDR systems. The system employs a combination of automated observable detection, threat intelligence enrichment, graph analysis, and supervised machine learning. It aims to predict analyst behavior in classifying EDR alerts as either 'true' or 'false' positives. The invention supports automated suppression of alerts classified with high confidence and provides recommendations for alerts that require analyst intervention. This innovation significantly reduces the overall workload for analysts while enhancing the efficiency of alert handling.

Career Highlights

Terry Liggett is currently employed at International Business Machines Corporation (IBM), where she continues to develop cutting-edge technologies in cybersecurity. Her work focuses on improving the effectiveness of EDR systems through advanced machine learning techniques.

Collaborations

Terry collaborates with talented professionals in her field, including Aankur Bhatia and Abhishek Basu. Their combined expertise contributes to the advancement of innovative solutions in cybersecurity.

Conclusion

Terry Liggett's contributions to the field of endpoint detection and response systems exemplify the impact of innovation in cybersecurity. Her patented techniques not only enhance threat response but also streamline the workload for analysts, showcasing the importance of machine learning in modern security solutions.

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