Quantifying voter controlled privacy hugo jonker in collaboration with jun pang and sjouke mauw
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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
QuantifyingVoter-controlled PrivacyHugo Jonkerin collaboration with Jun Pang and Sjouke Mauw




Traditional view on privacy
Traditional view on privacy

?

?

?

Works for: vote-privacy, receipt-freeness, coercion-resistance


Privacy swapping
Privacy ≠ swapping


What could that have been
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


Choice groups
Choice groups

cg(

) =

}

{


Conspiring voters
Conspiring voters

  • +

=

+

=

...


How to conspire
How to conspire

sees all!

  • { }k

  • untappable channels

=

= { }k

0110101010101

1010011101010

1100110101101

0110010101011

0111011010101

+ k



Untappable channels1
Untappable channels

0110101010101

1010011101010

1100110101101

0110010101011

0111011010101

0110101010101

1010011101010

1100110101101

0110010101011

0111011010101


Effects of coercion
Effects of coercion

) =

cg(

}

{

}

{

?

cg(

) =

=


Plans
Plans

  • slight extensions to formalism

  • account for distribution in result

  • conspiring authorities, defense coalitions

  • extend to auctions, e-healthcare, …

  • Sec ote 2010



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