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NONADAPTIVE MASTERMIND ALGORITHMS FOR STRING AND VECTOR
DATABASES, WITH CASE STUDIES
ABSTRACT:
In this paper, we study sparsity-exploiting Mastermind algorithms for attacking the privacy of an
entire database of character strings or vectors, such as DNA strings, movie ratings, or social
network friendship data. Based on reductions to nonadaptive group testing, our methods are able
to take advantage of minimal amounts of privacy leakage, such as contained in a single bit that
indicates if two people in a medical database have any common genetic mutations, or if two
people have any common friends in an online social network.
We analyze our Mastermind attack algorithms using theoretical characterizations that provide
sublinear bounds on the number of queries needed to clone the database, as well as experimental
tests on genomic information, collaborative filtering data, and online social networks. By taking
advantage of the generally sparse nature of these real-world databases and modulating a
parameter that controls query sparsity, we demonstrate that relatively few nonadaptive queries
are needed to recover a large majority of each database.
ECWAY TECHNOLOGIES
IEEE PROJECTS & SOFTWARE DEVELOPMENTS
OUR OFFICES @ CHENNAI / TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE
CELL: +91 98949 17187, +91 875487 2111 / 3111 / 4111 / 5111 / 6111
VISIT: www.ecwayprojects.com MAIL TO: ecwaytechnologies@gmail.com

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Nonadaptive mastermind algorithms for string and vector databases, with case studies

  • 1. NONADAPTIVE MASTERMIND ALGORITHMS FOR STRING AND VECTOR DATABASES, WITH CASE STUDIES ABSTRACT: In this paper, we study sparsity-exploiting Mastermind algorithms for attacking the privacy of an entire database of character strings or vectors, such as DNA strings, movie ratings, or social network friendship data. Based on reductions to nonadaptive group testing, our methods are able to take advantage of minimal amounts of privacy leakage, such as contained in a single bit that indicates if two people in a medical database have any common genetic mutations, or if two people have any common friends in an online social network. We analyze our Mastermind attack algorithms using theoretical characterizations that provide sublinear bounds on the number of queries needed to clone the database, as well as experimental tests on genomic information, collaborative filtering data, and online social networks. By taking advantage of the generally sparse nature of these real-world databases and modulating a parameter that controls query sparsity, we demonstrate that relatively few nonadaptive queries are needed to recover a large majority of each database. ECWAY TECHNOLOGIES IEEE PROJECTS & SOFTWARE DEVELOPMENTS OUR OFFICES @ CHENNAI / TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE CELL: +91 98949 17187, +91 875487 2111 / 3111 / 4111 / 5111 / 6111 VISIT: www.ecwayprojects.com MAIL TO: ecwaytechnologies@gmail.com