A Stealthy Communication Model with Blockchain Smart Contract for Bidding Systems

Author:

Liang Qi1ORCID,Shi Ning2,Tan Yu-an3ORCID,Li Chunying45,Liang Chen1

Affiliation:

1. School of Information Management, Beijing Information Science and Technology University, Beijing 100192, China

2. Science College, Shijiazhuang University, Shijiazhuang 050035, China

3. School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing 100081, China

4. Guangdong Provincial Key Laboratory of Intellectual Property & Big Data, Guangdong Polytechnic Normal University, Guangzhou 510665, China

5. School of Computer Science, Guangdong Polytechnic Normal University, Guangzhou 510665, China

Abstract

With the widespread adoption of blockchain technology, its public ledger characteristic enhances transaction transparency but also amplifies the risk of privacy breaches. Attackers can infer users’ real identities and behaviors by analyzing public transaction patterns and address relationships, posing a severe threat to users’ privacy and security, and thus hindering further advancements in blockchain applications. To address this challenge, covert communication has emerged as an effective strategy for safeguarding the privacy of blockchain users and preventing information leakage. But existing blockchain-based covert communication schemes rely solely on the immutability of blockchain itself for robustness and suffer from low transmission efficiency. To tackle these issues, this paper proposes a stealthy communication model with blockchain smart contract for bidding systems. The model initiates by preprocessing sensitive information using a secret-sharing algorithm-the Shamir (t, n) threshold scheme-and subsequently embeds this information into bidding amounts, facilitating the covert transfer of sensitive data. We implemented and deployed this model on the Ethereum platform and conducted comprehensive performance evaluations. To assess the stealthiness of our approach, we employed a suite of statistical tests including the CDF, the Kolmogorov–Smirnov test, Welch’s t-test and K–L divergence. These analyses confirmed that amounts carrying concealed information were statistically indistinguishable from regular transactions, thus validating the effectiveness of our solution in maintaining the anonymity and confidentiality of information transmission within the blockchain ecosystem.

Funder

R&D Program of Beijing Municipal Education Commission

Key Field Special Project of Ordinary Universities in Guangdong Province

Publisher

MDPI AG

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