Company Filing History:

8 out of 22,566

Amazon Technologies, Inc.

Years Active: 2019-2025

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11 patents (USPTO):Sort by Forward CitationsExplore Patents

1. 12418558 - Detection of malicious domains (2025-09-16),

2. 12210622 - Deep sequential anomalous events detection (2025-01-28),

3. 12204645 - Machine learning model evaluation and comparison (2025-01-21),

4. 12028362 - Detecting anomalous storage service events using autoencoders (2024-07-02),

5. 11743282 - Enhanced cloud-based entity reputation scoring (2023-08-29),

6. 11593639 - Scoring events using noise-contrastive estimation for anomaly detection (2023-02-28),

7. 11537902 - Detecting anomalous events from categorical data using autoencoders (2022-12-27),

8. 11374952 - Detecting anomalous events using autoencoders (2022-06-28),

9. 10708288 - Computerized system and method for automatically determining malicious IP clusters using network activity data (2020-07-07),

10. 10636048 - Name-based classification of electronic account users (2020-04-28),

11. 10193915 - Computerized system and method for automatically determining malicious IP clusters using network activity data (2019-01-29),

Title: Baris Coskun: Innovator in Cybersecurity Technologies

Introduction

Baris Coskun is a prominent inventor based in Glen Rock, NJ (US), known for his significant contributions to cybersecurity technologies. With a total of 11 patents to his name, he has developed innovative solutions aimed at enhancing security measures in digital environments.

Latest Patents

Among his latest patents is a system for the detection of malicious domains. This invention discloses methods that monitor for malicious and unauthorized behaviors, categorize detected malicious activities, and provide users with information regarding the reasons a domain is deemed malicious. The system is particularly beneficial for customers of cloud services, offering protection against various cyber threats such as spam, phishing, malware, and botnets. Another notable patent is focused on deep sequential anomalous events detection. This system utilizes machine learning to monitor anomalous activities within a service provider network. By parsing activity logs and generating event objects, the system can determine anomaly scores and identify events that are considered anomalous.

Career Highlights

Baris Coskun has worked with leading technology companies, including Amazon Technologies, Inc. and Oath Inc. His experience in these organizations has allowed him to refine his skills and contribute to groundbreaking innovations in the field of cybersecurity.

Collaborations

Throughout his career, Baris has collaborated with notable professionals such as MohamadAli Torkamani and Jeffrey Earl Bickford. These collaborations have further enriched his work and expanded the impact of his inventions.

Conclusion

Baris Coskun stands out as a key figure in the realm of cybersecurity innovation. His patents reflect a commitment to enhancing digital security and protecting users from evolving cyber threats.

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