An Enhanced Linearly Homomorphic Network Coding Signature Scheme for Secure Data Delivery in IoT Networks
Hao Huang, Xiaofen Wang, Man Ho Au, Sheng Cao, Qinglin Zhao, Jiguo Yu · IEEE Transactions on Information Forensics and Security · 2025
Recently, Li et al. proposed an identity-based linearly homomorphic network coding signature (IB-HNCS) scheme for secure data delivery in Internet of Things (IoT) networks, and they claimed that the IB-HNCS scheme can resist pollution attacks. However, this paper shows that the IB-HNCS scheme is vulnerable to pollution attacks, as anyone who only has the public parameter can forge a new file identifier or a valid signature on a corrupted data packet to pollute legitimate sensor data. To enhance security and performance in network coding-based IoT networks, we propose a secure and efficient certificateless linearly homomorphic network coding signature scheme for IoT data delivery, which is free of burdensome certificate management and key escrow issue. In addition, our scheme is proved to be secure against adaptive chosen identity and adaptive chosen subspace attacks under two types of adversaries in the algebraic group model and random oracle model. Therefore, our scheme can verify the validity of data packets and allow data packets to be computed, so as to resist pollution attacks. The performance evaluation demonstrates that our scheme is more efficient and practical than existing secure schemes. Specifically, for a 73-dimensional data vector, the costs of signature generation and verification in our scheme are reduced by 38.588%-86.076% and 38.570%-85.664% respectively under the symmetric bilinear pairing setting, and the costs of signature generation and verification in our scheme are reduced by 17.740%-49.752% and 29.697%-58.645% respectively under the asymmetric bilinear pairing setting.