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SIA: Secure Information Aggregation in Sensor Networks Bartosz Przydatek, Dawn Song, and Adrian Perrig (presented by Aleksandr Yampolskiy)
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
What is a sensor network? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
What is a sensor network? (cont.) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Why do we need aggregation? ,[object Object],[object Object],[object Object],[object Object],[object Object]
Why do we need aggregation? (cont.) ,[object Object],[object Object],[object Object],[object Object]
Why this paper? ,[object Object],[object Object]
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The model sensors home server  B aggregator  A S 1 S 2 S n … ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],K A K B
The model (cont.) sensors home server  B aggregator  A S 1 S 2 S n … ,[object Object],[object Object],[object Object],[object Object],[object Object],a 1 a 2 a n y = f(a 1 , …, a n )
Attack model  sensors aggregator  A S 1 S 2 S n … ,[object Object],[object Object],[object Object],a 1 a 2 a n X X
Attack model (cont.) sensors aggregator  A S 1 S 2 S n … ,[object Object],[object Object],a 1 a 2 a n y = f(a 1 , …, a n ) ŷ the result is ŷ the value is ậ n
Attack model (cont.) sensors aggregator  A S 1 S 2 S n … a 1 a 2 a n y = f(a 1 , …, a n ) the result is ŷ the value is ậ n ,[object Object],[object Object]
Some assumptions ,[object Object],[object Object],[object Object],[object Object],[object Object]
Tradeoff forward  all inputs forward only the final result security a 1 , …, a n efficiency y = f(a 1 , …, a n )
General approach ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
General approach (cont.) ,[object Object],[object Object],[object Object],[object Object],[object Object]
General approach (cont.) v 3,0 v 3,1 v 2,0 v 3,2 v 3,3 v 2,1 v 1,0 v 3,4 v 3,5 v 2,2 v 3,6 v 3,7 v 2,3 v 1,1 v 0,0 H a 1 a 2 a 3 a 4 a 5 a 6 a 7 a 8 v 0,0  = commit(a 1 , …, a 8 )
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Computing the median ,[object Object],[object Object],[object Object]
Computing the median (cont.) ,[object Object],[object Object],[object Object],[object Object]
Computing the median (cont.) ,[object Object],[object Object],[object Object],[object Object]
Digression: spot-checkers ,[object Object],[object Object],[object Object],procedure  Sort-Check-II (A,   ): repeat  O(1/  )  times choose  i 2 r  [1, n] perform binary search as if to determine if  a i   is in  A if  not found return   FAIL return   PASS
Computing the median (cont.) ,[object Object],[object Object],[object Object],[object Object]
Computing the median (cont.) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Computing the median (cont.) ,[object Object],[object Object],[object Object]
Computing the median (cont.) ,[object Object],[object Object],[object Object]
Computing min/max ,[object Object],[object Object],[object Object]
Computing min/max (cont.) ,[object Object],S 1 S 2 S 3 S 4 3 5 4 1 i = 0 diameter = 3 id 4 1 S 4 S 4 id 3 4 S 3 S 3 id 2 5 S 2 S 2 id 1 3 S 1 S 1 id i V i p i
Computing min/max (cont.) ,[object Object],S 1 S 2 S 3 S 4 3 5 4 1 i = 1 id 4 1 S 4 S 4 id 4 1 S 4 S 3 id 1 3 S 1 S 2 id 1 3 S 1 S 1 id i V i p i
Computing min/max (cont.) ,[object Object],S 1 S 2 S 3 S 4 3 5 4 1 i = 2 id 4 1 S 4 S 4 id 4 1 S 4 S 3 id 4 1 S 3 S 2 id 1 3 S 1 S 1 id i V i p i
Computing min/max (cont.) ,[object Object],S 1 S 2 S 3 S 4 3 5 4 1 i = 3 id 4 1 S 4 S 4 id 4 1 S 4 S 3 id 4 1 S 3 S 2 id 4 1 S 2 S 1 id i V i p i
Computing min/max (cont.) ,[object Object],[object Object],[object Object],[object Object],[object Object]
Counting distinct elements ,[object Object],[object Object],[object Object]
Counting distinct elements (cont.) ,[object Object],[object Object],[object Object],[object Object]
Counting distinct elements (cont.) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Counting distinct elements (cont.) ,[object Object],[object Object],[object Object],[object Object],[object Object]
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Conclusion ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],if I were article’s author
My  conclusion ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

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Secure information aggregation in sensor networks

  • 1. SIA: Secure Information Aggregation in Sensor Networks Bartosz Przydatek, Dawn Song, and Adrian Perrig (presented by Aleksandr Yampolskiy)
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  • 15. Tradeoff forward all inputs forward only the final result security a 1 , …, a n efficiency y = f(a 1 , …, a n )
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  • 18. General approach (cont.) v 3,0 v 3,1 v 2,0 v 3,2 v 3,3 v 2,1 v 1,0 v 3,4 v 3,5 v 2,2 v 3,6 v 3,7 v 2,3 v 1,1 v 0,0 H a 1 a 2 a 3 a 4 a 5 a 6 a 7 a 8 v 0,0 = commit(a 1 , …, a 8 )
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