An authorizable and preprocessable data transmission scheme based on elliptic curves

Z Zhongshan Zhu L Liutao Zhao Y Yong Pan X Xiaojuan Lu Z Zheng Wang F Fanyin Meng

Abstract

Abstract Current data security transmission schemes are based on the idea of signcryption, where the sender performs encryption and generates signatures within a single logical step. However, on one hand, the complexity of signing is relatively low, while the encryption and communication complexities for large amounts of data are high, leading to low overall transmission efficiency. On the other hand, once the receiver obtains the ciphertext, they can decrypt it, reducing the sender’s control over the data. Therefore, this paper proposes a data security transmission scheme that supports authorization and preprocessing. The scheme first preprocesses the computationally expensive data encryption and transmission operations, and then performs the authorization signature to improve efficiency. Specifically, based on the R value from Schnorr’s signature, the sender’s public key, and the receiver’s public key, a one-time public key is computed and used to encrypt the data before sending it to the receiver. The receiver can compute the corresponding one-time private key to decrypt and obtain the plaintext data, but only after receiving the s value from the sender’s Schnorr signature. Additionally, before the authorization signature s is published, the receiver cannot decrypt the data, ensuring both authorization unforgeability and data confidentiality, while also enhancing the sender’s control over the decryption timing. Experimental results show that for a 1KB data transmission, the execution times for the one-time public key generation algorithm, encryption algorithm, authorization algorithm, decryption algorithm, and signature verification algorithm were 3.34/28.37/0.58/3.32/4.58 ms, respectively, indicating high efficiency for each algorithm. Comparison tests show that for data sizes ranging from 50K to 1600K, using the preprocessing method can reduce execution time by about 68%.

Article Details

Volume / Issue Vol. 15, Issue 1
Published July 01, 2025
ISSN 2045-2322
Publisher Nature Portfolio

Journal Info

Scientific Reports

Nature Portfolio

ISSN: 2045-2322 Open Access Life Sciences

Authors (6)

Z

Zhongshan Zhu

L

Liutao Zhao

Y

Yong Pan

X

Xiaojuan Lu

Z

Zheng Wang

F

Fanyin Meng