TY - JOUR
T1 - A large-scale concurrent data anonymous batch verification scheme for mobile healthcare crowd sensing
AU - Liu, Jingwei
AU - Cao, Huijuan
AU - Li, Qingqing
AU - Cai, Fanghui
AU - Du, Xiaojiang
AU - Guizani, Mohsen
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2019/4
Y1 - 2019/4
N2 - Recently, with the rapid development of big data, Internet of Things (IoT) brings more and more intelligent and convenient services to people's daily lives. Mobile healthcare crowd sensing (MHCS), as a typical application of IoT, is becoming an effective approach to provide various medical and healthcare services to individual or organizations. However, MHCS still have to face to different security challenges in practice. For example, how to quickly and effectively authenticate masses of bio-information uploaded by IoT terminals without revealing the owners' sensitive information. Therefore, we propose a large-scale concurrent data anonymous batch verification scheme for MHCS based on an improved certificateless aggregate signature. The proposed scheme can authenticate all sensing bio-information at once in a privacy preserving way. The individual data generated by different users can be verified in batch, while the actual identity of participants is hidden. Moreover, assuming the intractability of computational Diffie-Hellman problem, our scheme is proved to be secure. Finally, the performance evaluation shows that the proposed scheme is suitable for MHCS, due to its high efficiency.
AB - Recently, with the rapid development of big data, Internet of Things (IoT) brings more and more intelligent and convenient services to people's daily lives. Mobile healthcare crowd sensing (MHCS), as a typical application of IoT, is becoming an effective approach to provide various medical and healthcare services to individual or organizations. However, MHCS still have to face to different security challenges in practice. For example, how to quickly and effectively authenticate masses of bio-information uploaded by IoT terminals without revealing the owners' sensitive information. Therefore, we propose a large-scale concurrent data anonymous batch verification scheme for MHCS based on an improved certificateless aggregate signature. The proposed scheme can authenticate all sensing bio-information at once in a privacy preserving way. The individual data generated by different users can be verified in batch, while the actual identity of participants is hidden. Moreover, assuming the intractability of computational Diffie-Hellman problem, our scheme is proved to be secure. Finally, the performance evaluation shows that the proposed scheme is suitable for MHCS, due to its high efficiency.
KW - Aggregate signature (AS)
KW - batch verification
KW - mobile healthcare crowd sensing (MHCS)
KW - privacy preservation
UR - http://www.scopus.com/inward/record.url?scp=85045722663&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85045722663&partnerID=8YFLogxK
U2 - 10.1109/JIOT.2018.2828463
DO - 10.1109/JIOT.2018.2828463
M3 - Article
AN - SCOPUS:85045722663
VL - 6
SP - 1321
EP - 1330
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 2
M1 - 8341503
ER -