  With the continuous expansion of Internet of Things (IoT) devices, edge
computing mode has emerged in recent years to overcome the shortcomings of
traditional cloud computing mode, such as high delay, network congestion, and
large resource consumption. Thus, edge-thing systems will replace the classic
cloud-thing/cloud-edge-thing systems and become mainstream gradually, where IoT
devices can offload their tasks to neighboring edge nodes. A common problem is
how to utilize edge computing resources. For the sake of fairness, double
auction can be used in the edge-thing system to achieve an effective resource
allocation and pricing mechanism. Due to the lack of third-party management
agencies and mutual distrust between nodes, in our edge-thing systems, we
introduce blockchains to prevent malicious nodes from tampering with
transaction records and smart contracts to act as an auctioneer to realize
resources auction. Since the auction results stored in this blockchain-based
system are transparent, they are threatened with inference attacks. Thus in
this paper, we design a differentially private combinatorial double auction
mechanism by exploring the exponential mechanism such that maximizing the
revenue of edge computing platform, in which each IoT device requests a
resource bundle and edge nodes compete with each other to provide resources. It
can not only guarantee approximate truthfulness and high revenue, but also
ensure privacy security. Through necessary theoretical analysis and numerical
simulations, the effectiveness of our proposed mechanisms can be validated.
