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Year 2 - University > Digital Forensics > Flashcards

Digital Forensics Flashcards

1
Q

What is the job of the lens?

A

To focus light/image onto centre

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2
Q

What is the job of the filter?

A

Reduce the sensitivity to infrared light

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3
Q

What is the job of the sensor?

A

Turns light into a recordable image

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4
Q

What does the DSP unit do?

A

Performs some basic image processing before the image is saved

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5
Q

What is the focal point?

A

A point on the optic axis where parallel light rays converge

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6
Q

What is the optic axis?

A

A line which runs perpendicular to the lens and directly through the middle

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7
Q

What does CMOS stand for? And what is its use?

A

Complementary metal oxide semiconductor
It helps the light sensitive sensor chip to record all of the data in a very short space of time

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8
Q

What does DSLR stand for?

A

Digital single lens reflex

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9
Q

What are pixels?

A

Individual light sensitive cells which measure the amount of light that fall on them. They cover the cameras sensor

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10
Q

How are coloured images produced?

A

The light seen by the camera is split in to the three primary colours which can than be used to create an accurate image through the use of a Bayer filter

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11
Q

What is a Bayer filter?

A

A grid of coloured filters that sit over the sensor with red, green, and blue elements over individual pixels which will only allow their respective light colours through. It looks at pixels surrounding others to formulate an informed guess of what the true colour of that pixel is

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12
Q

What is the job of the colour filter array?

A

It allows the digital camera to ‘see’ colours as it is colourblind without this and can only determine light intensity

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13
Q

What are the two common configurations of the colour filter array? Can you describe them?

A

The Bayer pattern - checkered
The Stripe pattern - stripes

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14
Q

What are photo sites?

A

Each square on the sensor element is a single photo site

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15
Q

Why are there two times more green elements on the colour filter array compared to red and blue?

A

Due to the human eye being more sensitive to green light

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16
Q

What are the two main types of sensors in the camera?

A

CCD (charge coupled device) and CMOS (complementary metal oxide semiconductor)

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17
Q

Define photodiodes

A

Semiconductor devices that generate an electrical charge in proportion to the number of photons which reach them

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18
Q

Where are photodiodes typically found?

A

They are tightly packed on a silicone wafer in CCDs and CMOSs

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19
Q

What are the advantages of CCD sensors?

A
  • Proven record of technologies and commercialization
  • Low noise, high S/N because the surface is almost entirely photosensitive (compared to 1/4 in CMOS)
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20
Q

What are the disadvantages of CCD sensors?

A
  • High power consumption, slower speed
  • on-chip peripheral circuits difficult to manufacture
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21
Q

What are the advantages of CMOS sensors?

A
  • Manufacture can be simpler and less expensive
  • Use less power than CCD
  • Physical size of detector is smaller
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22
Q

What are the disadvantages of CMOS sensors?

A
  • Relatively high noise
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23
Q

Where are CMOS sensors and CCD sensors typically used?

A

CMOS - modern consumer cameras (phones)
CCD - scientific applications

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24
Q

What is the job of the DSP (digital signal processors) molecule?

A

To read out the voltages from the image sensor which are then fed into an onboard image processing module which contains proprietary algorithms for improving the perceived quality, demosaicing, and compression

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25
Q

Define spacial sampling

A

The average light intensity per pixel

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26
Q

How many values per pixel to monochrome images have?

A

One

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27
Q

Why does the image appear blurry when the light intensity pattern is continuous?

A

Each pixel only record the average light intensity

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28
Q

Define resolution

A

The dimensions by which you can measure how many pixels are on a screen

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29
Q

Why are sharper images shown on a phone compared to a laptop?

A

They both have the same number of pixels, but they are in a denser space on the phone

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30
Q

What is a byte?

A

8 bits

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31
Q

How do we make an image darker?

A

By subtracting a fixed constant from each of the RGB values

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32
Q

Define point processing

A

The process of adjusting a pixels value according to a transformation function

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33
Q

What is an image histogram?

A

A graph which records the number of pixels in an image, and the light intensity of each of these pixels, and displays this as a bar chart

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34
Q

Why is a 4-bit image sometimes used instead of an 8-bit image?

A

It makes the image histogram clearer due to there being less values

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35
Q

What is the function of a look-up table (LUT)?

A

It implements a functional mapping of pixel intensity values

36
Q

What are the seven methods for detecting photo forgery?

A
  • Reverse image search
  • EXIF data check
  • Specular reflection
  • Photogrammetry
  • Inconsistencies in shadows/reflections
  • Grey level resampling
  • JPEG signatures
37
Q

What is image processing?

A

The technique of applying a relevant mathematical operation on a digitised image to generate an enhanced image or extract some useful features such as edge, shape, and colour

37
Q

What are the six purposes of spatial filtering?

A
  • Image smoothing
  • Noise removal
  • Image sharpening
  • Edge detection
  • Inpainting
  • Pre-processing
37
Q

How does image enhancement work?

A

It alters each pixel by the same amount in order to change the appearance of the image

38
Q

Give three applications of image processing

A

Medical imaging
Self-driving cars
Satellite imaging

39
Q

Which edges does a vertical difference mask highlight?

A

The horizontal edges

40
Q

Which edges does a horizontal difference mask highlight?

A

The vertical edges

41
Q

Define median filter

A

The output pixel value is determined as the neighbourhood median

42
Q

Define correlated noise

A

There is some sort of structure or pattern in the noise

43
Q

Define uncorrelated noise

A

No structure or pattern in the noise

44
Q

Why does correlated noise appear?

A

Electrical interference, source/sensor interference

45
Q

What effect does shutter speed have on noise?

A

Slower shutter speed can result in higher noise levels

46
Q

What is Gaussian noise?

A

Noise where the majority of the pixels have the same value of 127. There is a normal distribution around this number

47
Q

What is uniform noise?

A

Where the probability of getting any light intensity for a pixel is the same, meaning the distribution is flat

48
Q

What is salt and pepper noise?

A

The pixels have either a value of 0 or 255

49
Q

Why might salt and pepper noise appear?

A

Due to errors in transmission, dead pixels in a display, or photodiode leakage

50
Q

What are the advantages of removing salt and pepper noise with a median filter?

A
  • Returns the median value of the pixels in the neighbourhood
  • Is non-linear
  • Is similar to a uniform blurring filter which returns the mean value of the pixels in a neighbourhood of a pixel
  • Unlike a mean value filter, the median tends to preserve steep edges
51
Q

Why does shot noise occur?

A

Due to the random fluctuations in photon energy captured by the image sensor

52
Q

What is readout noise?

A

Electrical charge built up within the camera from the different onboard processes

53
Q

What are the two main types of pattern noise?

A

Photo response non-uniformity (PRNU) and dark signal non-uniformity (DSNU)

54
Q

What is PRNU?

A

The variation in pixel sensitivity cause by manufacturing defects and the natural non-uniformity of the silicon used in the image sensor

55
Q

What is DSNU?

A

fixed pattern noise due to ‘dark currents’ that occur in the sensor even when no light is incident upon it

56
Q

How do you obtain the fingerprint for a specific device?

A
  1. Take at least 50 natural scene images using the suspected source camera
  2. Individually filter each image using a wavelet denoising filter
  3. Average together the filtered images to produce a unique fingerprint for the camera
57
Q

Why is the denoised image only an estimate?

A

Impossible to remove all noise

58
Q

Define latent fingerprint in terms of digital forensics

A

Pattern noise extracted from an evidential image

59
Q

Define exemplar fingerprint in terms of digital forensics

A

Average pattern noise extracted from a sample of images known to have originated from a specific imaging device

60
Q

Define steganograohy

A

The art/science of communicating by hiding secret messages in innocuous ‘cover’ objects

61
Q

Define acrostic

A

A text, usually a poem, in which particular letters, such as the first of each line, spell a word or phrase

62
Q

Define cover object

A

A message that can be transmitted without suspicion, such as an image file, digital sound, or written text

63
Q

Define stego-object

A

A cover object containing an embedded secret object

64
Q

Why should the same cover never be used more than once?

A

As two versions of one cover could easily be detected and possibly decoded

65
Q

Define stego-key

A

Used to encrypt the secret message

66
Q

Define pure steganography

A

Does not require the exchange of prior information such as a stego-key

67
Q

Define secret key steganography

A

A secret stego-key is exchanged prior to communicating using a stego-object

68
Q

Define binary image

A

Images whose pixels only have two possible intensity values

69
Q

What is the random interval method in steganography?

A

Where elements of the cover are chosen at random for hiding data. The ‘seed’ for the random places, typically a random number generator, must be available to both parties in the communication

70
Q

Define visual attack

A

A means of detecting embedded information, such as by visual inspection of the least significant bits only of a digital image

71
Q

Define statistical attack

A

Referring to non-visual methods for determining embedding

72
Q

Define image histogram

A

The frequency distribution of grey-levels within a digital image

73
Q

What does embedding in the least significant bits to do the image histogram?

A

Tends to average out pairs of values in the image histogram

74
Q

What statistical technique is used to determine the probability of embedding?

A

Chi-squared

75
Q

What do the observed values refer to in the Chi-squared equation?

A

The observed values are every other column in the image histogram

76
Q

What does a low chi-squared value imply?

A

That embedding has taken place

77
Q

What is the purpose of an image compression algorithm?

A

In order to reduce the storage requirements, sometimes at the expense of the image quality

78
Q

Define non-lossy (loseless) compression

A

Original image can be recovered exactly from compressed image file, such as portable network graphics (.png)

79
Q

Define lossy compression

A

Information lost when a file is compressed. Therefore, only an approximation to the original image is possible, such as joint experts photographic group JPEG (.jpg)

80
Q

Define coding redundancy

A

Caused by sub-optimal code words for encoding, a symbol typically represents a grey-level

81
Q

Define inter-pixel redundancy

A

Due to grey-level correlations between neighbouring pixels

82
Q

Define psycho-visual redundancy

A

Information contained within an image that is superfluous to the interpretation or aesthetics of an image

83
Q

In psycho-visual redundancy, what does clarity depend on?

A
  1. Spacial frequency
  2. Amplitude
84
Q
A

Year 2 - University (3 decks)

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