Attacks against machine learning – an overview
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Re: Attacks against machine learning – an overview
#2Very related: about a year ago, I wrote about weaknesses of neural networks specifically: https://matt.life/papers/security_privacy_neural_networks.pd...
With powerful machine learning systems, we need to think about security a little differently. See especially the section 4.8 about function approximation:
> Given a task for which no discrete algorithm is known to solve, there is a good chance a neural network can at least approximate it. The extreme value of neural networks are their ability, in many cases, to act as an unknown function that can map inputs to outputs with good enough generalization almost as if the actual function was known. This makes any system that relies on the difficulty of implementing an unknown function vulnerable to the malignant use of neural networks
Re: Attacks against machine learning – an overview
#3It'd be great if there was a service that you could sign up for, which would "deceive" Facebook, Twitter, and other social media websites by producing false information about you. For example, if I don't want FB to know what movies I'm interested in, how about liking "random" movie pages on FB? If I don't want FB to know about my political orientations, how about run with the hare and hunt with the hounds?
Re: Attacks against machine learning – an overview
#4Very related: about a year ago, I wrote about weaknesses of neural networks specifically: https://matt.life/papers/security_privacy_neural_networks.pd... With powerful machine learning systems, we need to think about security a little differently. See especially the section 4.8 about function approximation: > Given a task for which no discrete algorithm is known to solve, there is a good chance a neural network can a…
could you place a 'backdoor' in these neural networks? Releasing a publicly beneficial AI while allowing it to be activated like a Manchurian candidate.
Re: Attacks against machine learning – an overview
#5It'd be great if there was a service that you could sign up for, which would "deceive" Facebook, Twitter, and other social media websites by producing false information about you. For example, if I don't want FB to know what movies I'm interested in, how about liking "random" movie pages on FB? If I don't want FB to know about my political orientations, how about run with the hare and hunt with the hounds?
AdNauseum[1] is that "service", but Google blocked it from the Chorome Add On Store for obvious reasons.
Re: Attacks against machine learning – an overview
#6It'd be great if there was a service that you could sign up for, which would "deceive" Facebook, Twitter, and other social media websites by producing false information about you. For example, if I don't want FB to know what movies I'm interested in, how about liking "random" movie pages on FB? If I don't want FB to know about my political orientations, how about run with the hare and hunt with the hounds?
I actually had the strategy on fb to just like very random stuff like movies, groups etc. I’m not sure whether it has helped but it makes me feel better
Re: Attacks against machine learning – an overview
#7It'd be great if there was a service that you could sign up for, which would "deceive" Facebook, Twitter, and other social media websites by producing false information about you. For example, if I don't want FB to know what movies I'm interested in, how about liking "random" movie pages on FB? If I don't want FB to know about my political orientations, how about run with the hare and hunt with the hounds?
Could you just give fake info? Or else use multiple fake profiles?
I don't know how you an deceive Facebook without also deceiving your friends and contacts though.
Re: Attacks against machine learning – an overview
#8Very related: about a year ago, I wrote about weaknesses of neural networks specifically: https://matt.life/papers/security_privacy_neural_networks.pd... With powerful machine learning systems, we need to think about security a little differently. See especially the section 4.8 about function approximation: > Given a task for which no discrete algorithm is known to solve, there is a good chance a neural network can a…
could you place a 'backdoor' in these neural networks? Releasing a publicly beneficial AI while allowing it to be activated like a Manchurian candidate.
That's basically what adversarial inputs are; except that those are unintentional. A true backdoor would probably look more like a ML system trained to give a nefarious output for the "backdoor" input (but this is like poisoning), and then whatever program relies on the output of the ML system would handle that accordingly; not unlike backdoors in conventional software. The output of a neural network is only as useful or effective as the software (or person) that makes decisions based on it.
Re: Attacks against machine learning – an overview
#9I just watched a presentation about using deep learning to detect cheaters in CounterStrike: Go (https://youtu.be/ObhK8lUfIlc) and the question he didn't seem to have an answer for was data poisoning -- what if the cheaters all volunteer to be on the anti-cheater jury? Of course they are cross checking juror reliability ratings and stuff, but it's definitely a treadmill.
Re: Attacks against machine learning – an overview
#10It'd be great if there was a service that you could sign up for, which would "deceive" Facebook, Twitter, and other social media websites by producing false information about you. For example, if I don't want FB to know what movies I'm interested in, how about liking "random" movie pages on FB? If I don't want FB to know about my political orientations, how about run with the hare and hunt with the hounds?
Could you just give fake info? Or else use multiple fake profiles? I don't know how you an deceive Facebook without also deceiving your friends and contacts though.
Does the api support creating old posts and back dating them?
FB is really good at hiding old activity and being utterly worthless at searching your feed, so if you can just put all the fake stuff in the past you'd be fine with your real friends.