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SUMMARY:Vector Commitments with Efficient Protocols for Privacy-preserving
  Smart Billing Applications - Alfredo Rial Duran\, Microsoft Research
DTSTART:20110826T130000Z
DTEND:20110826T140000Z
UID:TALK32597@talks.cam.ac.uk
CONTACT:Microsoft Research Cambridge Talks Admins
DESCRIPTION:In privacy-preserving smart billing applications\, users recei
 ve signed readings from smart meters\, calculate the total fee that should
  be paid and prove to service providers the correctness of the fee calcula
 tion without disclosing any further information. To calculate the total fe
 e and prove its correctness\, users receive a signed tariff policy from se
 rvice providers. \n\nExisting protocols allow users to prove efficiently t
 he correctness of the fee calculation when tariff policies are simple\, me
 aning that the price to be paid does not depend on users' past consumption
  and is specified by a single service provider. However\, when the price d
 ue depends on several policies signed by different entities\, the proof of
  correctness involves a computation cost linear in the amount of entities.
  History-dependent tariff policies involve recalculations on meter reading
 s.\n\nWe propose a method to efficiently calculate the total fee and prove
  its correctness when complex tariff policies are applied. Basically\, it 
 consists in creating an intermediate table that stores partial calculation
 s. The intermediate table allows to speed up the computation of the proof 
 of correctness and\, when the usage of the intermediate table surpasses a 
 threshold\, the cost of creating the intermediate table is amortized.\n\nW
 e show how to build intermediate tables based on a novel primitive we call
  vector commitments. Essentially\, vector commitments are commitments to a
  vector of values that can be opened to one of the values with cost indepe
 ndent of the size of the vector. We define vector commitments and propose 
 several constructions based on different security assumptions.
LOCATION:Small lecture theatre\, Microsoft Research Ltd\, 7 J J Thomson Av
 enue (Off Madingley Road)\, Cambridge
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