An Online Multi-Item Auction With Differential Privacy in Edge-Assisted Blockchains.

In recent years, the blockchain-based Internet of Things (IoT) has been widely studied and applied, and every IoT device can act as a node in the blockchain. However, these lightweight nodes usually do not have enough computing power to complete the consensus or other computing-required tasks. Edge computing network gives a platform to provide computing power to IoT devices. A fundamental problem is how to allocate limited edge servers to IoT devices in a highly untrusted environment. In a fair competitive environment, the allocation mechanism should be online, truthful, and privacy-preserved. In order to meet these three challenges, we propose an online multi-item double auction (MIDA) mechanism by means of auction theory, where IoT devices are buyers and edge servers are sellers. However, ensuring truthfulness is often contradictory to protecting users’ privacy. The participants’ private information is at risk of being exposed to inference attacks, which may lead to malicious manipulation of the market by adversaries. Thus, we enhance our MIDA mechanism with differential privacy to protect sensitive information from being leaked. It slightly interferes with the auction results in performance but guarantees privacy protection with high confidence. In addition, we upgrade our privacy-preserved MIDA mechanism such that it adapts to more complex and realistic scenarios. In the end, the effectiveness and correctness of algorithms are evaluated and verified by theoretical analysis and numerical simulations.