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A User-Friendly Approach to Human Authentication of Messages Jeff - - PowerPoint PPT Presentation

Sep 29, 2022 210 likes •450 views

A User-Friendly Approach to Human Authentication of Messages Jeff King Andr e dos Santos Georgia Institute of Technology { peff,andre } @cc.gatech.edu 1 A User-Friendly Approach to Human Authentication of Messages Motivation Suppose

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A User-Friendly Approach to Human Authentication of Messages

Jeff King Andr´ e dos Santos

Georgia Institute of Technology {peff,andre}@cc.gatech.edu

A User-Friendly Approach to Human Authentication of Messages

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Motivation

  • Suppose Alice is on a trip to a computer security conference.
  • Alice has to digitally sign an important document to send to a colleague back at the
  • ffice.
  • She uses one of the conference’s computers to, using her smart card, sign the

document and send through e-mail.

Smart Card

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Problem Solved?

  • Did she really sign the document?
  • What did the smartcard actually receive?
  • How does Alice know it’s the same thing that was on her screen?
  • How does she know if anything was even sent to her card?

Smart Card

? ? ?

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The Problem

  • How can a human interact with a (remote) Trusted Computing Base using an

untrusted computing system?

Solutions

  • Use a trusted computing system to interact

– availability? – security perimeter?

  • Directly interact with TCB

– extra hardware? – complexity and tamper resistance?

  • Require the human to be a trusted computing system!

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TCB to Human Secure Channel Requirements

TCB

Integrity, Authenticity

  • Human must recognize some unique secret held only by TCB (authenticity)
  • Inseparable binding of secret to message contents (integrity)
  • Easy for a human to do without computation or memory aid

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Outline

  • Motivation
  • Definition of Keyed Hard AI Problems (KHAP)
  • KHAP Using 3-D images
  • KHAP-Based Protocol
  • Conclusion
  • Future Work

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Hard AI Problems

  • Informally, something that humans can do easily but computers can’t.
  • More formally (von Ahn, 2003)

– S - a set of problem instances – f - a function mapping instances to answers – For human H, H(x) = f(x) with high probability – Security parameters - (α,τ)-hard – For any algorithm A running in time τ, Pr[A(x) = f(x)] ≤ α

  • CAPTCHA - Completely Automated Turing Test to Tell Computers and Humans Apart
  • Generate random message, transform it, ask human to repeat it

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KHAP: Keyed Hard AI Problems

  • A transformation problem that includes a shared secret key
  • Instances generated with different keys are distinguishable
  • Computers can’t steal keys from messages
  • Formalisms (simplified):

– Hd(m,m′) - human distinguishes between messages with different keys – |k −k′| - difference between two keys (quantifiable?) – Security parameters - (α,ε,τ)-hard – Given |k −k′| > ε, Pr[Hd(m,m′)] > α – For any algorithm A running in time τ, Pr[Hd(m,A(m′,m))] > α

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KHAP: Checking Message Authenticity

TCB

?

message message

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KHAP: Checking Message Authenticity

TCB

message

  • ther
  • ther

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KHAP: Parameters

  • Desirable:

– Easy for a human to understand the message. – Easy for a human to distinguish messages with different keys. – Difficult for a computer to “break”

∗ Change message meaningfully ∗ Extract keys ∗ Extract message?

  • Parameters define difficulty and easiness
  • Different applications have different parameter requirements
  • Problem: how to evaluate parameters for a given problem
  • Solution: empirical testing

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3-D Keyed Transformation

  • Render text and objects in a 3-D scene to 2-D image (raytrace)
  • Randomize parameters (lighting, position, rotation, size, colors)
  • Human can read text from 2-D image
  • Key is appearance of certain objects
  • Human looks for particular objects in scene
  • Scene is hard to modify in a meaningful way (shadows, reflections, finding objects)
  • Provide authenticity (presence of keys) and integrity (modifications can be detected

by human)

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3-D Example

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Attacks

  • Key Guessing
  • Convert from 2-D to 3-D
  • Extract Key

– Only one perspective Easy to guess keys? vs

  • Modify 2-D message
  • Replays
  • Human Adversary

– The most powerful – May not be able to describe key and/or modify scene in time – Beauty of the approach: The intended recipient does not have to describe the key!

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Tradeoffs

Easy for humans Difficult for Computers

  • Easy for humans to recognize message

– Choice of parameters (text size, fonts, colors, etc) needs to be bounded – Message length limitations – Maybe by itself static 3-D is not a good domain (animation?)

  • Difficult for computers to fake image or extract key

– Mirror reflections and shadows make cut and paste difficult – Obstructions of line of sight make it difficult to reconstruct 3-D keys – Text embedded in objects makes cut and paste difficult

  • Recognizing fake image

– How close is close enough? Small changes (1 char)?

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Pluggable Problems

  • Hard AI problems are “pluggable” into applications
  • 3-D KHAP (already discussed)
  • Speech KHAP

– message is speech-synthesized audio clip – key is voice parameters; user recognizes voice (parameters selected randomly at key generation) – audio distortion used to increase difficulty of analysis

  • Handwriting KHAP

– message is rendered using handwriting sample – key is writing style; user recognizes (too hard?) – visual distortion used to increase difficulty of analysis

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Protocol: Human sends to TCB

  • 8. Signed

Message

  • 2. Unsecured

Message

  • 6. Confirmation
  • 1. Unsecured

Message

  • 5. Confirmation
  • 4. KHAP
  • 3. KHAP
  • 7. Signed

Message

TCB

How can step 5 be performed?

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Human to TCB Confirmation

  • Only one bit is needed.
  • Insertion or extraction of a portable device

– Does not work for remote trusted server – Extraction: timing depends on application – Insertion to confirm is awkward

  • Confirmation word/object

– Pre-arranged (requires memory aid!) or type/click element from KHAP – Requires no special devices – Human adversary can be effective

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Confirmation Word Example

message

TCB

message

TCB TCB

cat

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Conclusions

  • Approach is general (mobile device, network, etc)
  • Many of the techniques map directly to what humans to do insure security in pencil

and paper world – Nobody signs a document that has patches covering some words – People authenticate each other on the phone by voice characteristics

  • Secure

– Security depends on AI problem parameters – Advances in AI break problems (as factoring breaks RSA)

  • Easy to use

– Avoid computation, memory aids: ask humans to do what they do best – Some problems are intuitive (e.g., recognizing voice)

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Future Work

  • Develop specific KHAP problems

– Evaluate usability (empirical studies) – Evaluate security (empirical + expert opinion)

  • Collaboration with AI, graphics, speech, human-computer interactions, OCR
  • Performance issues for low-power devices
  • Key generation and re-keying
  • Analyze human attacks (general and specific applications)

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Questions?

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