US 12,271,475 B2
Delayed inference attack detection for image segmentation-based video surveillance applications
Pablo Nascimento da Silva, Niterói (BR); Hugo de Oliveira Barbalho, Rio de Janeiro (BR); and Roberto Nery Stelling Neto, Rio de Janeiro (BR)
Assigned to Dell Products L.P., Round Rock, TX (US)
Filed by Dell Products L.P., Round Rock, TX (US)
Filed on Oct. 4, 2022, as Appl. No. 17/937,917.
Prior Publication US 2024/0111868 A1, Apr. 4, 2024
Int. Cl. G06F 21/56 (2013.01); G06F 21/55 (2013.01); G06V 10/764 (2022.01); G06V 10/776 (2022.01); G06V 20/40 (2022.01); G06V 20/52 (2022.01)
CPC G06F 21/566 (2013.01) [G06F 21/554 (2013.01); G06V 10/764 (2022.01); G06V 10/776 (2022.01); G06V 20/49 (2022.01); G06V 20/52 (2022.01); G06F 2221/034 (2013.01)] 12 Claims
OG exemplary drawing
 
1. A method, comprising:
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,
wherein the evaluating comprises classifying each of the image portions as either ‘noise’ or ‘conformant’,
wherein the image portions are evaluated on a rolling time window basis,
the rolling time window basis comprising:
1. splitting a time window into a plurality of time frames;
2. creating a linked list from the plurality of time frames, where a head of the linked list corresponds to a current time frame of the plurality of time frames, and the tail of the linked list is an oldest time frame of the plurality of time frames;
3. predicting a probability of each image portion in the time frame as either a ‘noise’ image or a ‘conformant’ image using a discriminator; and
4. for each time frame within the linked list, storing a respective counter of ‘conformant’ image classifications and another counter of ‘noise’ image classifications based on the predicted probability.