Camera tampering detection
A computer, including a processor and a memory, the memory including instructions to be executed by the processor to acquire one or more images from a camera and determine first camera noise values based on the one or more images by determining reactions of camera photo receptors to light. The instructions can include further instructions to compare the first camera noise values with second camera noise values determined based on previously acquired images from the camera and output a tamper determination for the camera based on whether the first camera noise values match, within a tolerance value, the second camera noise values determined based on the previously acquired images from the camera.
1. A computer, comprising:
a processor; and
a memory, the memory including instructions executable by the processor to:
acquire one or more images from a camera;
determine first camera noise values based on the one or more images by determining reactions of camera photo receptors to light;
compare the first camera noise values with second camera noise values determined based on previously acquired images from the camera by determining covariance matrices based on the one or more images of the camera and the previously acquired images from the camera, diagonalizing the covariance matrices to determine eigenvectors, and determining first and second camera noise values that include interaction noise principal components and temporal noise components of the eigenvectors;
output a tamper determination for the camera based on whether the first camera mean and variance values of the noise values match, within a tolerance value, the second camera mean and variance values of the noise values determined based on the previously acquired images from the camera; and
when the tamper d ion indicates that the first camera noise values do not match the second camera noise values, within a tolerance value, update the second camera noise values based on successful non-biometric access.
2. The computer of claim 1 , the instructions including further instructions to, when the tamper determination indicates that the first camera noise values match the second camera noise values, within a tolerance value, output images from the camera.
3. The computer of claim 1 , the instructions including further instructions to, when the tamper determination indicates that the first camera noise values do not match the second camera noise values, within a tolerance value, do not output images from the camera.
4. The computer of claim 1 , the instructions including further instructions to, when the tamper determination indicates that the first camera noise values match the second camera noise values, output one or more images from the camera for use in one or more of biometric authentication and autonomous vehicle operation.
5. The computer of claim 1 , wherein the one or more images are acquired by periodically defeating flat field compensation in the camera.
6. The computer of claim 1 , the instructions including further instructions to determine the first camera noise values by determining photo-response non-uniformity values {circumflex over (K)} by the equation {circumflex over (K)}=Σ i=1 m W i I i /Σ i=1 m (I i ) 2 where I i is the i-th image acquired by the camera and W i is the noise residual of the i-th image.
7. The computer of claim 1 , the instructions including further instructions to determine the first camera noise values by determining camera dark current.
8. The computer of claim 1 , wherein determining camera tampering includes determining lens aberration by comparing geometry of an object in the one or more images to geometry of the object in one or more previously acquired images from the camera.
9. The computer of claim 1 , wherein determining the first camera noise values includes determining one or more components of a principal component analysis that decomposes image data into an n-dimensional component space, wherein each component corresponds to a line that best fits the image data including noise.
10. The computer of claim 9 , wherein determining the first camera noise values includes determining components of the principal component analysis that correspond to interaction noise corresponding to image artifact introduced into the image by acquisition of the one or more images.
11. The computer of claim 9 , wherein determining the first camera noise values includes determining components of the principal component analysis that correspond to temporal noise corresponding to random image noise related to electronic noise and photon quantum noise included in the one or more images.
12. The computer of claim 1 , wherein the second camera noise is updated based on determining a successful non-biometric access, wherein non-biometric access techniques include a passcode, a key, or a fob.
13. A method comprising:
acquiring one or more images from a camera;
determining first camera noise values based on the one or more images by determining reactions of camera photo receptors to light;
comparing the first camera noise values with second camera noise values determined based on previously acquired images from the camera by determining covariance matrices based on the one or more images of the camera and the previously acquired images from the camera, diagonalizing the covariance matrices to determine eigenvectors, and determining first and second camera noise values that include interaction noise principal components and temporal noise components of the eigenvectors;
output a tamper determination for the camera based on whether the first camera mean and variance values of the noise values match, within a tolerance value, the second camera mean and variance values of the noise values determined based on the previously acquired images from the camera; and
when the tamp nation indicates that the first camera noise values do not match the second camera noise values, within a tolerance value, update the second camera noise values based on successful non-biometric access.
14. The method of claim 13 , further comprising, when the tamper determination indicates that the first camera noise values match the second camera noise values, within a tolerance value, output images from the camera.
15. The method of claim 13 , further comprising, when the tamper determination indicates that the first camera noise values do not match the second camera noise values, within a tolerance value, do not output images from the camera.
16. The method of claim 13 , further comprising, when the tamper determination indicates that the first camera noise values match the second camera noise values, output one or more images from the camera for use in one or more of biometric authentication and autonomous vehicle operation.
17. The method of claim 13 , wherein the one or more images are acquired by periodically defeating flat field compensation in the camera.
18. The method of claim 13 , further comprising determining the first camera noise values by determining photo-response non-uniformity values {circumflex over (K)} by the equation {circumflex over (K)}=Σ i=1 m W i I i /Σ i=1 m (I i ) 2 where I i is the i-th image acquired by the camera and W i is the noise residual of the i-th image.
19. The method of claim 13 , further comprising determining the first camera noise values by determining camera dark current.
20. The method of claim 13 , wherein determining camera tampering includes determining lens aberration by comparing geometry of an object in the one or more images to geometry of the object in one or more previously acquired images from the camera.