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Michael Roytman

This inventor holds 19 USPTO granted patents and 8 published patent applications. Top assignees: Kenna Security, Inc., Cisco Technology, Inc., Risk I/o, Inc.. Active years: 2015-2026.

USPTO Granted Patents = 19 (Patent Applications = 8)

% Patents Active = 100.0

Average Co-Inventor Count = 2.7

ph-index = 5

Forward Citations = 138(Granted Patents)

Company Filing History:

Cisco Technology, Inc.

where one patent can have more than one assignee

Years Active: 2015-2026

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19 patents (USPTO):Sort by Forward CitationsExplore Patents

1. 12732544 - LLM technology with human input reinforcement learning for suggesting the follow up response actions to detections and incidents (2026-09-08),

2. 12657310 - LLM technology for polymorphic generation of samples of malware for modeling, grouping, detonation and analysis (2026-06-16),

3. 12615292 - System and method for detecting malicious messages generated by a large language model (LLM) (2026-04-28),

4. 12554861 - Text-based tagging of security deficiencies using generative machine learning models (2026-02-17),

5. 12499221 - Systems and methods for generating attack tactic probabilities for historical text documents (2025-12-16),

6. 12438900 - Risk-based vulnerability remediation timeframe recommendations (2025-10-07),

7. 12079346 - Exploit prediction based on machine learning (2024-09-03),

8. 11888887 - Risk-based vulnerability remediation timeframe recommendations (2024-01-30),

9. 11861016 - Multi-stage training of machine learning models (2024-01-02),

10. 11275844 - Exploit prediction based on machine learning (2022-03-15),

11. 11250137 - Vulnerability assessment based on machine inference (2022-02-15),

12. 10970400 - Multi-stage training of machine learning models (2021-04-06),

13. 10762212 - Exploit prediction based on machine learning (2020-09-01),

14. 10503908 - Vulnerability assessment based on machine inference (2019-12-10),

15. 10305925 - Ordered computer vulnerability remediation reporting (2019-05-28),

Title: Michael Roytman: Innovating Cybersecurity Solutions

Introduction

Michael Roytman, a distinguished inventor based in Chicago, IL, has made significant contributions to the field of cybersecurity through his innovative patents. With a remarkable portfolio of 13 patents, Roytman's work focuses on enhancing the prediction and remediation of vulnerabilities in digital systems.

Latest Patents

Roytman's most recent patents include groundbreaking advancements in machine learning for cybersecurity. One of his key inventions, titled "Exploit prediction based on machine learning," involves generating models that predict the development and use of exploits for various vulnerabilities. By selecting relevant training data, including prevalence features for vulnerabilities, the models can potentially forecast whether an exploit will arise or be utilized during an attack. This innovation is critical for preemptively addressing security threats.

Another notable patent, "Risk-based vulnerability remediation timeframe recommendations," describes systems and methods for calculating remediation times for asset vulnerabilities. This invention leverages retrieved vulnerability data to recommend timely actions for addressing identified threats, significantly enhancing response strategies within organizations.

Career Highlights

Throughout his career, Michael Roytman has been associated with prominent companies such as Kenna Security, Inc. and Risk I/o, Inc., where he played pivotal roles in advancing cybersecurity technologies. His expertise in understanding vulnerabilities and developing predictive models has made substantial impacts in safeguarding digital environments against emerging threats.

Collaborations

Roytman has collaborated with notable professionals in the field, including Edward T Bellis and Jeffrey Heuer. These partnerships have facilitated the sharing of ideas and the development of innovative solutions aimed at improving cybersecurity measures for various entities.

Conclusion

In summary, Michael Roytman's remarkable contributions to the field of cybersecurity, underscored by his numerous patents, demonstrate his commitment to innovation and safety in digital security. His work not only advances technological understanding but also provides practical solutions for vulnerability predictions and remediation, solidifying his standing as a leading inventor in the industry.

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