Yingying Tang

Ms. Yingying Tang


Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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31 December 2023 in Entropy
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Journal Article
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忠何忠祥 何
忠祥 何
YCYuling Chen
Yuling Chen
YLYun Luo
Yun Luo
LZLingyun Zhang
Lingyun Zhang
YTYingying Tang
Yingying Tang
The emerging cloud storage technology has significantly improved efficiency and productivity in the traditional electronic healthcare field. However, it has also brought about many security concerns. Ciphertext policy attribute-based encryption (CP-ABE) holds immense potential in achieving fine-grained access control, providing robust security for electronic healthcare data in the cloud. However, current CP-ABE schemes still face issues such as inflexible attribute revocation, relatively lower computational capabilities, and key management. To address these issues, this paper introduces a revocable and traceable undeniable ciphertext policy attribute-based encryption scheme (MA-RUABE). MA-RUABE not only enables fast and accurate data traceability, effectively preventing malicious user key leakage, but also includes a direct revocation feature, significantly enhancing computational efficiency. Furthermore, the introduction of a multi-permission mechanism resolves the issue of centralization of power caused by single-attribute permissions. Furthermore, a security analysis demonstrates that our system ensures resilience against chosen plaintext attacks. Experimental results demonstrate that MA-RUABE incurs lower computational overhead, effectively enhancing system performance and ensuring data-sharing security in cloud-based electronic healthcare systems.

24 March 2023 in Applied Sciences
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Journal Article
Open access
PDF file
YTYingying Tang
Yingying Tang
YCYuling Chen
Yuling Chen
YLYun Luo
Yun Luo
SDSen Dong
Sen Dong
TLTao Li
Tao Li
Public key encryption with keyword search (PEKS) allows users to perform keyword searches of ciphertext on untrusted cloud storage servers, protecting data privacy while sharing data. However, it faces several security problems in practical applications. First, an attacker can launch a keyword guessing attack to obtain keywords of interest to users, causing the leakage of their sensitive information. Second, untrusted cloud servers may return incorrect or incomplete results. In addition, with the continuous development of quantum computers, existing PEKS schemes face the problem of quantum attacks. Since cloud servers are mostly untrusted, verifiable search has become a hot research topic among scholars. However, most of the current schemes are based on bilinear pairing constructions, which are vulnerable to quantum attacks. To solve these problems, we propose a new ciphertext retrieval scheme based on fully homomorphic encryption (FHE), called VR-PEKS. This scheme implements verifiable search and is able to solve the problems of keyword guessing attacks and quantum attacks. We propose to improve the security of the scheme by using the oblivious pseudorandom function to randomize keywords and then encrypt them using FHE. An encrypted verified index structure is constructed and exposed by the data owner, enabling the data recipient to achieve verification of the correctness and integrity of the retrieved results without relying on a trusted third party. We demonstrate the security of the proposed scheme in a stochastic prediction model, and prove that our scheme satisfies keyword ciphertext indistinguishability and keyword trapdoor indistinguishability under adaptive keyword selection attacks. The comparison shows that our scheme is secure and feasible.