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Quantifying Voter-controlled Privacy Hugo Jonker in collaboration with Jun Pang and Sjouke Mauw

Quantifying Voter-controlled Privacy Hugo Jonker in collaboration with Jun Pang and Sjouke Mauw. Why care about privacy?. A random set of voters. Traditional view on privacy. ?. ?. ?. Works for: vote-privacy, receipt-freeness, coercion-resistance. Privacy ≠ swapping.

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Quantifying Voter-controlled Privacy Hugo Jonker in collaboration with Jun Pang and Sjouke Mauw

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  1. QuantifyingVoter-controlled PrivacyHugo Jonkerin collaboration with Jun Pang and Sjouke Mauw

  2. Why care about privacy?

  3. A random set of voters

  4. Traditional view on privacy ? ? ? Works for: vote-privacy, receipt-freeness, coercion-resistance

  5. Privacy ≠ swapping

  6. What could that have been? • - ρ( ) = - ρ( ) = (ρ( ), ρ( )) , - ρ({ }K) = {ρ( )}K if k is known 0110101010101 1010011101010 1100110101101 0110010101011 0111011010101 - ρ({ }K) = if k is unknown

  7. Choice groups cg( ) = } {

  8. Conspiring voters • + = + = ...

  9. How to conspire sees all! • { }k • untappable channels = = { }k 0110101010101 1010011101010 1100110101101 0110010101011 0111011010101 + k

  10. Untappable channels ? ? ?

  11. Untappable channels 0110101010101 1010011101010 1100110101101 0110010101011 0111011010101 0110101010101 1010011101010 1100110101101 0110010101011 0111011010101

  12. Effects of coercion ) = cg( – } { } { ? cg( ) = = –

  13. Plans • slight extensions to formalism • account for distribution in result • conspiring authorities, defense coalitions • extend to auctions, e-healthcare, … • Sec ote 2010

  14. Thanks for your attention • /

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