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For the Inventor, By the Inventor

Boston, MA, United States of America

Roy Donald Hodgman

USPTO Granted Patents = 58 

Average Co-Inventor Count = 2.5

ph-index = 6

Forward Citations = 172(Granted Patents)

Forward Citations (Not Self Cited) = 176(Dec 10, 2025)


Location History:

  • Boston, MA (US) (2016)
  • Cambridge, MA (US) (2018 - 2024)

Company Filing History:

goldMedal58 out of 294 
 
Rapid7, Inc.
 patents

Years Active: 2016-2025

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Areas of Expertise:
Cyberattack Detection
Authentication Systems
Anomaly Detection Models
Homomorphic Encryption
Data Transfer Detection
Network Activity Monitoring
Machine Learning Models
Vulnerability Assessment
Lateral Movement Detection
Honeypot Services
Network Behavior Classification
Feature Space Analysis
58 patents (USPTO):Explore Patents
1. 12413606 - Techniques for detecting cyberattacks on an authentication system (2025-09-09),
2. 12321454 - Command line parsing for classification of process start alerts (2025-06-03),
3. 12314385 - Automated generation of anomaly scenarios for testing machine learned anomaly detection models (2025-05-27),
4. 12289404 - Password similarity checking using homomorphic encryption operations (2025-04-29),
5. 12238127 - Anomalous data transfer detection (2025-02-25),
6. 12206699 - Identifying high-influence features for model-detected anomalies (2025-01-21),
7. 12182670 - Automated dimensionality reduction for machine learning anomaly detection pipeline (2024-12-31),
8. 12120136 - Anomalous data transfer detection (2024-10-15),
9. 12101342 - System and method for monitoring network activity for detecting data exfiltration events (2024-09-24),
10. 12088600 - Machine learning system for detecting anomalies in hunt data (2024-09-10),
11. 12081575 - Anomalous connection detection using combination of online machine learning models (2024-09-03),
12. 12069079 - Generating synthetic datapoints from observed datapoints for training machine learning models (2024-08-20),
13. 11956260 - Attack monitoring service that selectively analyzes connection graphs for suspected attack paths (2024-04-09),
14. 11930108 - Password requirement conformity check (2024-03-12),
15. 11856017 - Machine learning correlator to infer network properties (2023-12-26),

Title: Innovations by Roy Donald Hodgman: Leading the Charge in Anomaly Detection

Introduction: Roy Donald Hodgman, based in Boston, MA, is an accomplished inventor with an impressive portfolio of 54 patents. His work mostly focuses on advancing technology in the realm of data transfer and security, particularly through innovative methods for detecting anomalous data activity in computer networks.

Latest Patents: Among Hodgman's latest innovations are two notable patents: "Anomalous Data Transfer Detection" and "Identifying High-Influence Features for Model-Detected Anomalies." The first patent outlines various systems and methods for identifying hotspots of data transfer activity within an organization, classifying certain days and hours based on outbound data traffic. This dataset, termed a "warmspot dataset," aids in the detection of anomalous activity, leading to timely alerts for security measures. The second patent presents an anomaly detection system leveraging machine learning to report anomalies in computer networks. This system is notable for its use of unsupervised training techniques, allowing it to adapt and improve automatically without manual labeling.

Career Highlights: Currently, Roy Hodgman works at Rapid7, Inc., a company focused on enhancing cybersecurity and detecting vulnerabilities across networks. His expertise lies in designing systems that not only detect threats but also learn from them, ensuring robust and evolving defenses against cyber attacks.

Collaborations: Hodgman collaborates with notable peers such as Vasudha Shivamoggi and Wah-Kwan Lin. These associations have allowed them to synergize their knowledge and expertise, driving forward innovative solutions in their respective fields.

Conclusion: With a remarkable array of patents and contributions to cybersecurity, Roy Donald Hodgman exemplifies the spirit of innovation. His efforts in developing systems that intelligently detect data anomalies represent significant advancements in technology, enhancing organizational security and operational efficiency. Hodgman’s work continues to inspire and elevate cybersecurity measures, reinforcing the critical need for innovation in protecting digital assets.

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