• @[email protected]
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    593 months ago

    About 10 years ago, I read a paper that suggested mitigating a rubber hose attack by priming your sys admins with subconscious biases. I think this may have been it: https://www.usenix.org/system/files/conference/usenixsecurity12/sec12-final25.pdf

    Essentially you turn your user to be an LLM for a nonsense language. You train them by having them read nonsense text. You then test them by giving them a sequence of text to complete and record how quickly and accurately they respond. Repeat until the accuracy is at an acceptable level.

    Even if an attacker kidnaps the user and sends in a body double, with your user’s id, security key, and means of biometric identification, they will still not succeed. Your user cannot teach their doppelganger the pattern and if the attacker tries to get the user on a video call, the added lag of the user reading the prompt and dictating the response should introduce a detectable amount of lag.

    The only remaining avenue the attacker has is, after dumping the body of the original user, kidnap the family of another user and force that user to carry out the attack. The paper does not bother to cover this scenario, since the mitigation is obvious: your user conditioning should include a second module teaching users to value the security of your corporate assets above the lives of their loved ones.

    • @[email protected]
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      113 months ago

      Essentially you turn your user to be an LLM for a nonsense language. You train them by having them read nonsense text.

      Did you forget the word “teach”? Or even the concept?

      • @[email protected]
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        93 months ago

        I am well aware of learning, but people tend to learn by comprehension and understanding. Completing phrases without understanding the language (or the concept of language) is the realm of LLM and Scrabble players.

    • @[email protected]
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      53 months ago

      Smart. I like the idea of replacing biometrics with something that can’t easily be cloned - learned behaviour. Perhaps with a robust ML approach you could use analysis of gait, expressions, and other subtle behavioural tics rather than or in addition to facial/fingerprint/iris recognition. I suspect that would be very hard to fake - although perhaps vulnerable to, idk, having a bad day and acting “off”.

      • @[email protected]
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        63 months ago

        Ah, so only employ posh people.

        “Hi, I’m definitely Henry. My turn to take the RSA key sentry duty today.”

        “Henry, why are you acting like a commoner? You’re not like yourself at all!”

    • @[email protected]
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      3 months ago

      Having read the paper, there seems to be a glaring problem: Even though the user can’t tell an attacker the password, nothing is stopping them from demonstrating the password. It doesn’t matter if it’s an interactive sequence – the user is going to remember enough detail to describe the “prompts”.

      A rubber hose and a little time will get enough information to make a “close enough” mock-up of the password entry interface the trusted user can use to reveal the password.