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DTSTART:19700308T020000
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DTSTAMP:20260522T150117Z
LOCATION:C140/142
DTSTART;TZID=America/Chicago:20181115T110000
DTEND;TZID=America/Chicago:20181115T113000
UID:submissions.supercomputing.org_SC18_sess208_pap468@linklings.com
SUMMARY:Adaptive Anonymization of Data with b-Edge Covers
DESCRIPTION:Arif Khan (Pacific Northwest National Laboratory), Krzysztof C
 horomanski (Google LLC), Alex Pothen and S M Ferdous (Purdue University), 
 and Mahantesh Halappanavar and Antonino Tumeo (Pacific Northwest National 
 Laboratory)\n\nWe explore the problem of sharing data that pertains to ind
 ividuals with anonymity guarantees, where each user requires a desired lev
 el of privacy.  We propose the first shared-memory as well as distributed 
 memory parallel algorithms for the adaptive anonymity problem that achieve
 s this goal, and produces high quality anonymized datasets.  \n\nThe new a
 lgorithm is based on an optimization procedure that iteratively computes w
 eights on the edges of a dissimilarity matrix, and at each iteration compu
 tes a minimum weighted b-Edge cover in the graph. We are able to solve ada
 ptive anonymity problems with hundreds of thousands of instances and hundr
 eds of features on a leadership-class supercomputer in under five minutes.
  Our algorithm scales up to 4K cores on a distributed memory supercomputer
 , while also providing good speedups on shared memory multiprocessors. On 
 smaller problems, where an algorithm based on Belief Propagation is feasib
 le, our algorithm is two orders of magnitude faster.\n\nTag: Applications,
  Graph Algorithms, Security\n\nRegistration Category: Tech Program Reg Pas
 s\n\nSession Chair: Mostofa Patwary (NVIDIA Corporation)\n\n
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