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Interesting… I was thinking the opposite… My personal ability to generate millions of real-looking messages has now exploded and I wonder how these proposed st
by rsync 4y ago
Interesting… I was thinking the opposite…
My personal ability to generate millions of real-looking messages has now exploded and I wonder how these proposed structures will function if everyone sends each other 1k suspicious messages every minute of every day ?
Maybe attach a zip-bomb to every message just for good measure?
- revelio 4y agoYou won't be able to do that. Spam filtering exists and mostly isn't based on message contents looking real or not.
- faeyanpiraat 4y agoYou can't use current spam filters to fight against this, provided the system is implemented correctly. Let's assume you send 1000 automated messages periodically, and they contain a mixed bag of normal looking (so that your genuine comms could hide in plain sight) and malicious messages (to make their detection systems sweat). All the messages are sent from the same origin (e.g.: a messaging app capable of this), with a specific interval (the genuine msg is timed accordingly), etc.. Let's see a small sample of normal looking messages, with an added genuine manually written message: - Let's meet up at the Riverside Park soccer field at 5 PM sharp. - Hey, can you grab a gallon of milk from the corner store on your way back? - Good morning! Wishing you a fantastic day ahead, especially during your 11 AM meeting! - Just a reminder: our dinner reservation at Luigi's Italian Bistro is at 7 PM tonight. - Could you pick up the kids from Maplewood Elementary at 3:30 PM today? Work is keeping me busy. - Caught in traffic near Main Street, but I'll be at the coffee shop in about 10 minutes! Which one is the genuine one? Just like you cannot discern which msg is genuine (are any of them?), you can generate plausible maliciously looking messages as well.
- revelio 4y agoAgain, that's not how spam filters actually work in the real world. They hardly care about message contents. They care about how many spam reports users file and those are weighed against non-reported messages for any stable identity like phone number, sending domain name, etc. Spam meanwhile is defined as messages users don't want. If users can't tell the difference between spam and non-spam then, by definition, the messages are not spam. If you send lots of "legit" messages to people who don't want them you'll be reported as a spammer and get banned. Doesn't matter what the messages say.
- faeyanpiraat 4y agoOh sorry, I missed a part, and you are misunderstanding me. I understand you know how real world spam filters work, but this is a different use case. I'm not trying to generate spam, I'm talking about an IM app, where you have your contacts, and you can talk with each other and only see the legit messages. I can elaborate, but please continue in a non-adversarial way if possible.
- ryanwaggoner 4y agoBut the IM client will need a way to differentiate the noise messages from the ones intended for the human recipient. Whatever denotes a message as being intended for humans can also be used by the surveillance apparatus to ignore the noise messages.
- feeela 4y agoBut who actually does that? We need billions of people doing that every day to have an effect.
- faeyanpiraat 4y agoHow did you arrive at this number "billions"? The equation is more like # of ppl × # of msgs in a time period = noise We can increase the # of msgs to bring down the other side from "billions" I think.
- faeyanpiraat 4y agoThe first people getting onboard the idea have to be brave and assume that others will follow suit to reach useful noise levels, otherwise those few will end up in a world of trouble.
- carapace 4y agoThe problem isn't really that it works or doesn't work. The problem is that once we accept digital "evidence" then we're on course to push-button corruption. Remember "Hacking Team" that got busted a few years back? https://en.wikipedia.org/wiki/Hacking_Team https://en.wikipedia.org/wiki/Hacking_Team One of the services they sold was the ability to plant incriminating data on a victim's computer.