Even if you have encrypted your traffic with a VPN (or the Tor Network), advanced traffic analysis is a growing threat against your privacy. Therefore, we now introduce DAITA.
Through constant packet sizes, random background traffic and data pattern distortion we are taking the first step in our battle against sophisticated traffic analysis.
If I were to send packets to a single entity over time, I’d have no use for DAITA. I agree with you on this.
However, let’s say that I run a bunch of VPN endpoints across VPSes, and the entity trying to track me doesn’t know about all of these IP ranges. I could be renting from a colo, the cloud and even a a bunch of friends who have their ports open. If I were to mix this in with my usual internet traffic, it becomes significantly harder for third-parties to figure out what I’m doing connecting to all of these different IPs. A state actor could put the resources behind it, but the average third-party will have a hard time with it. I can certainly see use-cases for it.
I think we’re mixing up vocabulary.
Every IP you talk to is visible to anybody monitoring your network. The sale of net flow data is commonly acknowledged by ISPs. So every computer you talk to is common knowledge for sale.
In your scenario, let’s say you have five VPN connections set up to go to five endpoints that you control. But if nobody else is using those same endpoints. Your net flow data still exposes exactly what you’re doing. There’s no ambiguity. Your traffic is plainly obvious to anybody observing the network. Even if those VPN connections are adding randomized traffic onto the links.
Except that I will not necessarily be connecting to the exact same IPs over time, just going to do so in specific ranges which the VPS/colo owns. There’s plenty of people who are going to be renting VPSes and will have their traffic originate from the same IP range as mine, which means that if everybody using TCP had their traffic anonymized like so, the third party wouldn’t actually know that MigratingToLemmy specifically was connecting to AWS at a certain time and from a certain location, so to speak. This hypothesis doesn’t include correlation through other data in the threat model. But it could definitely prevent correlation with traffic across locations, which is similar to what Mullvad states
