Examples of passive defenses against surveillance:

But why not actively combat surveillance instead of passively defending against it? Examples of active combat:

We must poison the data of those who are violating our privacy. Let us waste their time, increase their data storage costs, and waste their processing power. Let them drown in an ocean of data. Let them search for tiny needles in huge haystacks, with no way to distinguish between needles and hay.

Some ideas:

  • Sending fake data to Google Analytics (How does Google Analytics prevent fake data attacks against an entity’s traffic?)
  • Create fake contacts lists to mislead those who are building social network graphs.
  • Encrypt lots of worthless data, store them in the cloud or send them by email. If the encrypted data is intercepted by any nosy entity, they will have to waste storage space while waiting to be able to break the encryption.

What are some other possible methods?

Let us turn the tables on those who have been violating our privacy. Why do we have to be on the defense? Let us waste their resources in the same way that they are wasting ours!

  • v9CYKjLeia10dZpz88iU@programming.dev
    22·
    10 months ago

    I think all 3 are likely detectable.

    AdNauseam is my favorite though, and probably currently the least detectable. It purposefully costs advertisers the money they bid against each other for clicks. Though, if abuse of it becomes too high, I think Google would very likely separate out users they have detected as likely bots. Though, for people who do not browse the internet very often, there might not be very much data to be confident they’re a bot.

    I really don’t like that modern advertising is based on highly invasive spying. A billboard is a nuisance, but someone watching everything I do online is a stalker.

    edit: It’s about making predictions about behavior worse. An issue is that advertising has conversions or sales, which most fake clicks will not become conversions… but part of it is just creating data that might cause predictions against other people for content they don’t desire. (resulting in less impactful advertising)