TY - GEN
T1 - Verifiable social data outsourcing
AU - Yao, Xin
AU - Zhang, Rui
AU - Zhang, Yanchao
AU - Lin, Yaping
N1 - Funding Information:
ACKNOWLEDGMENT This work was partially supported by US Army Research Office through grant W911NF-15-1-0328, US National Science Foundation through grants CNS-1700032 and CNS-1700039, and National Natural Science Foundation of China through grants 61472125 and 61402161.
Publisher Copyright:
© 2017 IEEE.
PY - 2017/10/2
Y1 - 2017/10/2
N2 - Social data outsourcing is an emerging paradigm for effective and efficient access to the social data. In such a system, a third-party Social Data Provider (SDP) purchases complete social datasets from Online Social Network (OSN) operators and then resells them to data consumers who can be any individuals or entities desiring the complete social data satisfying some criteria. The SDP cannot be fully trusted and may return wrong query results to data consumers by adding fake data and deleting/modifying true data in favor of the businesses willing to pay. In this paper, we initiate the study on verifiable social data outsourcing whereby a data consumer can verify the trustworthiness of the social data returned by the SDP. We propose three schemes for verifiable queries over outsourced social data. The three schemes all require the OSN provider to generate some cryptographic auxiliary information, based on which the SDP can construct a verification object for the data consumer to verify the query-result trustworthiness. They differ in how the auxiliary information is generated and how the verification object is constructed and verified. Extensive experiments based on a real Twitter dataset confirm the high efficacy and efficiency of our schemes.
AB - Social data outsourcing is an emerging paradigm for effective and efficient access to the social data. In such a system, a third-party Social Data Provider (SDP) purchases complete social datasets from Online Social Network (OSN) operators and then resells them to data consumers who can be any individuals or entities desiring the complete social data satisfying some criteria. The SDP cannot be fully trusted and may return wrong query results to data consumers by adding fake data and deleting/modifying true data in favor of the businesses willing to pay. In this paper, we initiate the study on verifiable social data outsourcing whereby a data consumer can verify the trustworthiness of the social data returned by the SDP. We propose three schemes for verifiable queries over outsourced social data. The three schemes all require the OSN provider to generate some cryptographic auxiliary information, based on which the SDP can construct a verification object for the data consumer to verify the query-result trustworthiness. They differ in how the auxiliary information is generated and how the verification object is constructed and verified. Extensive experiments based on a real Twitter dataset confirm the high efficacy and efficiency of our schemes.
UR - http://www.scopus.com/inward/record.url?scp=85034059555&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85034059555&partnerID=8YFLogxK
U2 - 10.1109/INFOCOM.2017.8057005
DO - 10.1109/INFOCOM.2017.8057005
M3 - Conference contribution
AN - SCOPUS:85034059555
T3 - Proceedings - IEEE INFOCOM
BT - INFOCOM 2017 - IEEE Conference on Computer Communications
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE Conference on Computer Communications, INFOCOM 2017
Y2 - 1 May 2017 through 4 May 2017
ER -