17944887. COMPUTER-BASED SYSTEMS PROGRAMMED FOR AUTOMATIC GENERATION OF INTERACTIVE NOTIFICATIONS FOR SUSPECT INTERACTION SESSIONS AND METHODS OF USE THEREOF simplified abstract (Capital One Services, LLC)
Contents
- 1 COMPUTER-BASED SYSTEMS PROGRAMMED FOR AUTOMATIC GENERATION OF INTERACTIVE NOTIFICATIONS FOR SUSPECT INTERACTION SESSIONS AND METHODS OF USE THEREOF
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 COMPUTER-BASED SYSTEMS PROGRAMMED FOR AUTOMATIC GENERATION OF INTERACTIVE NOTIFICATIONS FOR SUSPECT INTERACTION SESSIONS AND METHODS OF USE THEREOF - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
COMPUTER-BASED SYSTEMS PROGRAMMED FOR AUTOMATIC GENERATION OF INTERACTIVE NOTIFICATIONS FOR SUSPECT INTERACTION SESSIONS AND METHODS OF USE THEREOF
Organization Name
Inventor(s)
Shabnam Kousha of Washington DC (US)
Lin Ni Lisa Cheng of Great Neck NY (US)
Asher Smith-rose of Midlothian VA (US)
Joshua Edwards of Philadelphia PA (US)
Tyler Maiman of Melville NY (US)
COMPUTER-BASED SYSTEMS PROGRAMMED FOR AUTOMATIC GENERATION OF INTERACTIVE NOTIFICATIONS FOR SUSPECT INTERACTION SESSIONS AND METHODS OF USE THEREOF - A simplified explanation of the abstract
This abstract first appeared for US patent application 17944887 titled 'COMPUTER-BASED SYSTEMS PROGRAMMED FOR AUTOMATIC GENERATION OF INTERACTIVE NOTIFICATIONS FOR SUSPECT INTERACTION SESSIONS AND METHODS OF USE THEREOF
Simplified Explanation
The patent application abstract describes a method for monitoring activities on computing devices, identifying suspect interaction sessions, and generating interaction notifications based on certain parameters.
- Obtaining permission from the user to monitor activities on the computing device
- Receiving monitoring data for a predetermined period of time
- Identifying incoming interaction sessions and verifying common session parameters
- Determining frequency metrics and threshold values for suspect interaction sessions
- Generating interaction notifications for suspect sessions
- Receiving responses to the notifications and updating the database of known session parameters
Potential Applications
This technology could be applied in cybersecurity systems to detect and prevent suspicious activities on computing devices.
Problems Solved
This technology helps in identifying and addressing potential security threats and suspicious interactions on computing devices.
Benefits
The benefits of this technology include enhanced security measures, early detection of potential threats, and improved user privacy protection.
Potential Commercial Applications
One potential commercial application of this technology could be in the development of security software for businesses to protect their sensitive data and information.
Possible Prior Art
One possible prior art for this technology could be existing cybersecurity systems that monitor and analyze user activities on computing devices.
Unanswered Questions
How does this technology handle privacy concerns of users?
This technology ensures user privacy by obtaining permission before monitoring activities and by updating the database of known session parameters to improve accuracy and reduce false positives.
What measures are in place to prevent false positives in identifying suspect interaction sessions?
The technology uses threshold values for frequency metrics and verifies common session parameters to accurately identify suspect interaction sessions and minimize false positives.
Original Abstract Submitted
In some embodiments, the present disclosure provides an exemplary method that may include steps of obtaining a permission from the user to monitor a plurality of activities executed within the computing device; receiving monitoring data of the activities executed within the plurality of computing devices for a predetermined period of time; identifying incoming interaction sessions across the plurality of computing devices; verifying one common session parameter associated with the incoming interaction sessions to identify the incoming interaction sessions as suspect interaction sessions; determining a frequency metric for the suspect interaction sessions; determining a threshold value for the frequency metric; receiving new monitoring data; determining that the new incoming interaction session has at least one common session interaction parameter with the suspect interaction sessions; automatically generating an interaction notification for transmission to the computing device; receiving a response to the interactive communication; and updating the database of known session interaction parameters.
