Patents by Inventor Arjun Krishnaiah

Arjun Krishnaiah has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20230379438
    Abstract: Introduced here is a surveillance system that is able to employ an approach to sharing security information, such that organizations have the ability to voluntarily share relevant security information with the individuals who frequent the corresponding buildings. The surveillance system introduced here may not only be able to protect the safety of organizations, but also the privacy of users. In order for a member of the public to truly feel safe—not only from material loss or bodily harm—it is crucial for her to know what information is being recorded, stored, and used.
    Type: Application
    Filed: May 16, 2023
    Publication date: November 23, 2023
    Inventors: Karl Erik Gustav Rehnby, Julia Lin, Arjun Krishnaiah, Matthew Timothy Bornski
  • Patent number: 11049116
    Abstract: A system and method for automated anomaly detection in automated disposal decisions of an automated decisioning workflow includes collecting a time-series of automated disposal decision data for a current period from an automated decisioning workflow, wherein the automated decisioning workflow computes one of a plurality of distinct disposal decisions for each distinct input comprising subject online event data and a machine learning-based threat score computed for the subject online event data; selecting an anomaly detection algorithm from a plurality of distinct anomaly detection algorithms based on a type of online abuse or online fraud that the automated decisioning workflow is configured to evaluate; evaluating, using the selected anomaly detection algorithm, the time-series of automated decision data for the current period; computing whether anomalies exist in the time-series of automated disposal decision data for the current period based on the evaluation; and generating an anomaly alert based on the
    Type: Grant
    Filed: February 12, 2021
    Date of Patent: June 29, 2021
    Assignee: Sift Science, Inc.
    Inventors: Kostyantyn Gurnov, Vera Dadok, Duy Tran, Arjun Krishnaiah, Hui Wang, Yuan Zhuang, Wei Liu
  • Publication number: 20210182874
    Abstract: A system and method for automated anomaly detection in automated disposal decisions of an automated decisioning workflow includes collecting a time-series of automated disposal decision data for a current period from an automated decisioning workflow, wherein the automated decisioning workflow computes one of a plurality of distinct disposal decisions for each distinct input comprising subject online event data and a machine learning-based threat score computed for the subject online event data; selecting an anomaly detection algorithm from a plurality of distinct anomaly detection algorithms based on a type of online abuse or online fraud that the automated decisioning workflow is configured to evaluate; evaluating, using the selected anomaly detection algorithm, the time-series of automated decision data for the current period; computing whether anomalies exist in the time-series of automated disposal decision data for the current period based on the evaluation; and generating an anomaly alert based on the
    Type: Application
    Filed: December 2, 2020
    Publication date: June 17, 2021
    Inventors: Kostyantyn Gurnov, Vera Dadok, Duy Tran, Arjun Krishnaiah, Hui Wang, Yuan Zhuang, Wei Lui
  • Patent number: 11037173
    Abstract: A system and method for automated anomaly detection in automated disposal decisions of an automated decisioning workflow includes collecting a time-series of automated disposal decision data for a current period from an automated decisioning workflow, wherein the automated decisioning workflow computes one of a plurality of distinct disposal decisions for each distinct input comprising subject online event data and a machine learning-based threat score computed for the subject online event data; selecting an anomaly detection algorithm from a plurality of distinct anomaly detection algorithms based on a type of online abuse or online fraud that the automated decisioning workflow is configured to evaluate; evaluating, using the selected anomaly detection algorithm, the time-series of automated decision data for the current period; computing whether anomalies exist in the time-series of automated disposal decision data for the current period based on the evaluation; and generating an anomaly alert based on the
    Type: Grant
    Filed: December 2, 2020
    Date of Patent: June 15, 2021
    Assignee: Sift Science, Inc.
    Inventors: Kostyantyn Gurnov, Vera Dadok, Duy Tran, Arjun Krishnaiah, Hui Wang, Yuan Zhuang, Wei Liu