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content/notes/18-ML-in-IA-2.md
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@ -17,8 +17,62 @@ tags:
- use statistical distribution of passwords then use this to generate guesses
![passGAN](https://i.imgur.com/439hrXq.png)
![passGAN sample data](https://i.imgur.com/Y7A4ygP.png)
- can generate passwords that are likely to be used
- also based off previous passwords
- passwords can be guessed in less attempts
- need to update our rules - e.g., how many guesses makes an attempt likely to be suspicious
-
- new password generate, which also provides real world indicator of password strength
- faster password guessing
- hackers will get in faster
- need to be a step ahead of this
- insight into strong but unused passwords
- passwords get close and closer to those typically used
## password "guessing"
- gets faster as machines get faster (Moore's law)
- machine learning reduces number of trials further by learning distributions of passwords
- useful for us
- even if we didn't do this research the hackers would
- use passgan to detect guesses which may have come from passgan
- can analyse the source of guesses for suspicous stuff e.g., ip, location etc
- can analyse data from antivirus programs
- useful for hackers
- hackers can conquer our strategies
## steganography
- hiding secret messages in a medium that is not meant to be secret (e.g., image, audio, video)
- used to hide content and reduce suspicion e.g., in forensic investigation
- hidden message usually encryted but not in the sense of cryptography
- goal is to decieve
![](https://i.imgur.com/JWOIBw1.png)
- embed noise into images
### signal to noise
- most signals contain noise e.g., static
- noise carries info as the least significant bits in value
- hiding data in an image in the least significant bits will be visually percieved as noise
### e.g., derek uphams JSteg
![slide](https://i.imgur.com/nGEGhPA.png)
### stegnalysis
- detecting hidden content
- usually visually undetectable
how
- analyse DCT distributions
- ![example DCT distribution](https://i.imgur.com/iki90fH.png)
F5 steganographic algorithm
- developed to fool analysis of dct distributions
-
new password generate, which also provides real world indicator of password st
# bigger issues