TY - GEN
T1 - Privacy Protection Routing and a Self-organized Key Management Scheme in Opportunistic Networks
AU - Qin, Yang
AU - Zhang, Tiantian
AU - Li, Mengya
N1 - Publisher Copyright:
© 2020, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
PY - 2020
Y1 - 2020
N2 - The opportunistic network adopts the disconnected store-and-forward architecture to provide communication support for the nodes without an infrastructure. As there is no stable communication link between the nodes, so that forwarding messages is via any encountered nodes. Social networks based on such opportunistic networks will have privacy challenges. In this paper, we propose a privacy protection scheme routing based on the utility value. We exploit the Bloom filter to obfuscate the friends lists and the corresponding utility values of nodes in order to make the routing decisions. This is easy to implement with high performance. Considering no infrastructure and stable link in opportunistic networks, this paper presents a self-organized key management system consisting of an identity authentication scheme based on the zero-knowledge proof of the elliptic curve and a key agreement scheme based on the threshold cryptography. The nodes prove their identities by themselves, and each node carries a certificate library to improve the authentication efficiency and success rate. In order to ensure the forward security and improve the session key agreement rate and the success rate, we exploit threshold cryptography to divide the session key, which could reduce the communication consumption of the traditional Diffie-Hellman (DH) algorithm. The experimental simulation results show that the proposed schemes are much better than the existing schemes for opportunistic networks.
AB - The opportunistic network adopts the disconnected store-and-forward architecture to provide communication support for the nodes without an infrastructure. As there is no stable communication link between the nodes, so that forwarding messages is via any encountered nodes. Social networks based on such opportunistic networks will have privacy challenges. In this paper, we propose a privacy protection scheme routing based on the utility value. We exploit the Bloom filter to obfuscate the friends lists and the corresponding utility values of nodes in order to make the routing decisions. This is easy to implement with high performance. Considering no infrastructure and stable link in opportunistic networks, this paper presents a self-organized key management system consisting of an identity authentication scheme based on the zero-knowledge proof of the elliptic curve and a key agreement scheme based on the threshold cryptography. The nodes prove their identities by themselves, and each node carries a certificate library to improve the authentication efficiency and success rate. In order to ensure the forward security and improve the session key agreement rate and the success rate, we exploit threshold cryptography to divide the session key, which could reduce the communication consumption of the traditional Diffie-Hellman (DH) algorithm. The experimental simulation results show that the proposed schemes are much better than the existing schemes for opportunistic networks.
KW - Key management system
KW - Opportunistic network
KW - Privacy protection
KW - Routing
UR - https://www.scopus.com/pages/publications/85079087431
U2 - 10.1007/978-3-030-38819-5_16
DO - 10.1007/978-3-030-38819-5_16
M3 - 会议稿件
AN - SCOPUS:85079087431
SN - 9783030388188
T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
SP - 252
EP - 268
BT - Quality, Reliability, Security and Robustness in Heterogeneous Systems - 15th EAI International Conference, QShine 2019, Proceedings
A2 - Chu, Xiaowen
A2 - Jiang, Hongbo
A2 - Li, Bo
A2 - Wang, Wei
A2 - Wang, Dan
PB - Springer
T2 - 15th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, QShine 2019
Y2 - 22 November 2019 through 23 November 2019
ER -