ProSecutor: Protecting Mobile AIGC Services on Two-Layer Blockchain via Reputation and Contract Theoretic Approaches

Yinqiu Liu, Hongyang Du, Dusit Niyato, Jiawen Kang, Zehui Xiong, Abbas Jamalipour, Xuemin Shen

Abstract: Mobile AI-Generated Content (AIGC) has achieved great attention in unleashing the power of generative AI and scaling the AIGC services. By employing numerous Mobile AIGC Service Providers (MASPs), ubiquitous and low-latency AIGC services for clients can be realized. Nonetheless, the interactions between clients and MASPs in public mobile networks, pertaining to three key mechanisms, namely MASP selection, payment scheme, and fee-ownership transfer, are unprotected. In this paper, we design the above mechanisms in a systematic approach and present the first blockchain to protect mobile AIGC, called ${\sf ProSecutor}$. Specifically, by roll-up and layer-2 channels, ${\sf ProSecutor}$ forms a two-layer architecture, realizing tamper-proof data recording and atomic fee-ownership transfer with high resource efficiency. Then, we present the Objective-Subjective Service Assessment ($\text{OS}^{2}\mathrm{A}$) framework, which effectively evaluates the AIGC services by fusing the objective service quality with the reputation-based subjective experience of the service outcome (i.e., AIGC outputs). Deploying $\text{OS}^{2}\mathrm{A}$ on ${\sf ProSecutor}$, firstly, the MASP selection can be realized by sorting the reputation. Afterward, the contract theory is adopted to optimize the payment scheme and help clients avoid moral hazards in mobile networks. We implement the prototype of ${\sf ProSecutor}$ on BlockEmulator. Extensive experiments demonstrate that ${\sf ProSecutor}$ achieves 12.5× throughput and saves 67.5% storage resources compared with BlockEmulator. Moreover, the effectiveness and efficiency of the proposed mechanisms are validated.