TY - GEN
T1 - Private combinatorial group testing
AU - Atallah, Mikhail J.
AU - Frikken, Keith B.
AU - Blanton, Marina
AU - Cho, Youn Sun
PY - 2008
Y1 - 2008
N2 - Combinatorial group testing, given a set C of individuals ("customers"), consists of applying group tests on subsets of C for the purpose of identifying which members of C are infected (or, more generally, defective in some way). The outcome of a group test reveals only the presence or absence of infection(s) in that group, but a number of group tests exactly identifies all infected members. Although the main motivation for group testing is economic - it drastically cuts down the number of necessary tests - it has an interesting privacy side-effect, namely, that each individual customer is "hiding in a crowd" (the groups within which it is being tested). This privacy side-effect is currently thrown away because the analysis that pinpoints who is infected is carried out by the same entity that prepared the test samples. This paper gives a protocol in which these two duties are separated between Alice and Bob: The protocol informs each customer who is infected privately, and without either Alice or Bob learning who is infected. An interesting feature of our protocol is that a customer need not have any computational power, i.e., the customer can be notified by mailing her (possibly paper copies of) two random strings - one from Alice and one from Bob - so all she has to do is visually check whether these two strings are equal or not.
AB - Combinatorial group testing, given a set C of individuals ("customers"), consists of applying group tests on subsets of C for the purpose of identifying which members of C are infected (or, more generally, defective in some way). The outcome of a group test reveals only the presence or absence of infection(s) in that group, but a number of group tests exactly identifies all infected members. Although the main motivation for group testing is economic - it drastically cuts down the number of necessary tests - it has an interesting privacy side-effect, namely, that each individual customer is "hiding in a crowd" (the groups within which it is being tested). This privacy side-effect is currently thrown away because the analysis that pinpoints who is infected is carried out by the same entity that prepared the test samples. This paper gives a protocol in which these two duties are separated between Alice and Bob: The protocol informs each customer who is infected privately, and without either Alice or Bob learning who is infected. An interesting feature of our protocol is that a customer need not have any computational power, i.e., the customer can be notified by mailing her (possibly paper copies of) two random strings - one from Alice and one from Bob - so all she has to do is visually check whether these two strings are equal or not.
KW - Group testing
KW - Integrity verification
KW - Privacy
KW - Secure protocol
UR - https://www.scopus.com/pages/publications/77952354676
U2 - 10.1145/1368310.1368355
DO - 10.1145/1368310.1368355
M3 - Conference contribution
AN - SCOPUS:77952354676
SN - 9781595939791
T3 - Proceedings of the 2008 ACM Symposium on Information, Computer and Communications Security, ASIACCS '08
SP - 312
EP - 320
BT - Proceedings of the 2008 ACM Symposium on Information, Computer and Communications Security, ASIACCS '08
T2 - 2008 ACM Symposium on Information, Computer and Communications Security, ASIACCS '08
Y2 - 18 March 2008 through 20 March 2008
ER -