17937917. DELAYED INFERENCE ATTACK DETECTION FOR IMAGE SEGMENTATION-BASED VIDEO SURVEILLANCE APPLICATIONS simplified abstract (Dell Products L.P.)
Contents
- 1 DELAYED INFERENCE ATTACK DETECTION FOR IMAGE SEGMENTATION-BASED VIDEO SURVEILLANCE APPLICATIONS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 DELAYED INFERENCE ATTACK DETECTION FOR IMAGE SEGMENTATION-BASED VIDEO SURVEILLANCE APPLICATIONS - 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
DELAYED INFERENCE ATTACK DETECTION FOR IMAGE SEGMENTATION-BASED VIDEO SURVEILLANCE APPLICATIONS
Organization Name
Inventor(s)
Pablo Nascimento Da Silva of Niterói (BR)
Hugo de Oliveira Barbalho of Rio de Janeiro (BR)
Roberto Nery Stelling Neto of Rio de Janeiro (BR)
DELAYED INFERENCE ATTACK DETECTION FOR IMAGE SEGMENTATION-BASED VIDEO SURVEILLANCE APPLICATIONS - A simplified explanation of the abstract
This abstract first appeared for US patent application 17937917 titled 'DELAYED INFERENCE ATTACK DETECTION FOR IMAGE SEGMENTATION-BASED VIDEO SURVEILLANCE APPLICATIONS
Simplified Explanation
The abstract describes a method for dynamically monitoring image portions classified by a segmentation model in a video surveillance system, detecting attacks, and implementing remedial actions.
- The method involves monitoring image portions classified by a segmentation model in a video surveillance system.
- The system evaluates the image portions to determine if an attack is occurring or has occurred.
- If an attack is detected, the system implements a remedial action to address the attack.
Potential Applications
This technology can be applied in various industries such as security, surveillance, and defense to enhance threat detection and response capabilities.
Problems Solved
This technology helps in early detection of attacks on video surveillance systems, allowing for timely intervention to prevent potential security breaches.
Benefits
The benefits of this technology include improved security measures, enhanced threat detection capabilities, and quicker response times to potential attacks on video surveillance systems.
Potential Commercial Applications
One potential commercial application of this technology is in the development of advanced video surveillance systems for high-security facilities, public spaces, and critical infrastructure.
Possible Prior Art
Prior art in this field may include existing video surveillance systems with basic threat detection capabilities, but none that specifically focus on dynamically monitoring image portions classified by a segmentation model for attack detection and remediation.
Unanswered Questions
How does this technology impact privacy concerns in video surveillance systems?
This article does not address the potential privacy implications of implementing such advanced threat detection technologies in video surveillance systems.
What are the scalability limitations of this method in large-scale video surveillance systems?
The article does not provide information on how this method may perform in large-scale video surveillance systems with a high volume of image portions to monitor and evaluate.
Original Abstract Submitted
One example method includes dynamically monitoring a stream of image portions that have been classified by a segmentation model of a video surveillance system, evaluating the image portions, based on the evaluating, determining that an attack on the video surveillance system is occurring, or has occurred, and implementing, or causing the implementation of, a remedial action with regard to the attack. The image portions may be image portions that have been classified by a segmentation model.
