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Cipher-block chaining (CBC) is a widely used encryption mode for smart grid data, however, the chain structure leads to low encryption and decryption efficiency. To overcome this issue, this paper proposes a novel tree-CBC (TCBC) block encryption method. First, the smart grid plaintext is preprocessed according to the security level of the data. Second, the chain structure of the CBC mode is converted into a tree structure, and for the data block with a higher security level, its location is deeper in the encryption tree. Third, since the overall security and encryption time of data encrypted by TCBC depend on the number of forks of the encryption tree, this paper proposes a method to determine the optimal number of forks of TCBC based on the weights of the encryption time and security of the data blocks. The experiment shows that the encryption efficiency of the TCBC mode is improved by nearly 50% compared to the original CBC mode. And as the data size increases, the efficiency improvement becomes more obvious. Furthermore, compared with widely used encryption modes such as CFB, OFB, CTR, and PCBC, the proposed TCBC mode has higher encryption and decryption efficiency.

Despite the great efforts to secure wireless sensor network (WSN), the dynamic nature and the limited resources of sensor nodes make searching for a secure and optimal network structure an open challenge. In this paper, we propose a novel encryption schema based on Elliptic Curve Cryptography (ECC) and homomorphic encryption to secure data transmission in WSN. The proposed encryption schema is built upon GASONeC algorithm (Elhoseny et al., 2014) that uses genetic algorithm to build the optimum network structure in the form of clusters. ECC is used to exchange public and private keys due to its ability to provide high security with small key size. The proposed encryption key is 176-bit and is produced by combining the ECC key, node identification number, and distance to its cluster head (CH). To reduce energy consumption of CH, homomorphic encryption is used to allow CH to aggregate the encrypted data without having to decrypt them. We demonstrated that the proposed method is capable to work with different sensing environments that need to capture text data as well as images. Compared with the state-of-the-art methods, our experimental results demonstrated that our proposed method greatly improve the network performance in terms of lifetime, communication overhead, memory requirements, and energy consumption.