Smart contracts, the stateful programs running on blockchains, often rely on reports. Publishers are paid to publish these reports on the blockchain. Designing protocols that incentivize timely reporting is the prevalent reporting problem. But existing solutions face a security-performance trade-off: Relying on a small set of trusted publishers introduces centralization risks, while allowing open publication results in an excessive number of reports on the blockchain. We identify the root cause of this trade-off to be the standard symmetric reward design, which treats all reports equally. We prove that no symmetric-reward mechanism can overcome the trade-off. We present Personal Random Rewards for Reporting (Prrr), a protocol that assigns random heterogeneous values to reports. We call this novel mechanism-design concept Ex-Ante Synthetic Asymmetry. To the best of our knowledge, Prrr is the first game-theoretic mechanism (in any context) that deliberately forms participant asymmetry. Prrr employs a second-price-style settlement to allocate rewards, ensuring incentive compatibility and achieving both security and efficiency. Following the protocol constitutes a Subgame-Perfect Nash Equilibrium, robust against collusion and Sybil attacks. Prrr is applicable to numerous smart contracts that rely on timely reports.

ABSTRACT With the rapid development of the intelligent computing centers, multivariate time series generated from many heterogeneous devices with non‐independent and identically distributed (non‐IID) characteristic, posed a significant challenge to traditional anomaly detection models. These challenges primarily arise from the difficulty in aligning and unifying heterogeneous data and the significant reduction in model generalization due to non‐IID data distributions. Therefore, this paper proposes a novel anomaly detection framework for non‐IID data from heterogeneous devices. First, we introduce a chain of thought metric alignment and ranking mechanism based on a large language model to meet the data heterogeneity challenge. Second, we design a variational recurrent neural network model augmented with global factors to capture spatiotemporal correlation patterns across devices, effectively addressing the impact of non‐IID data distributions. Experiments on multiple real‐world datasets demonstrate that this approach achieves optimal F1‐scores across various heterogeneous datasets. And because of the metric ranking, the model communication efficiency and inference efficiency have been greatly optimized.

We consider a hierarchical structure of a permissioned blockchain with three types of participant: providers, collectors, and governors. Providers forward transactions to collectors; collectors upload received transactions to governors after verifying and labeling them; and governors validate a portion of the labeled transactions they receive, pack valid transactions into a block, and append the block to the ledger. This model has various fields of application including data collection from the Internet-of-Things and second-hand markets. Our main contribution is to propose a reputation-based protocol to help governors evaluate the reliability of collectors. Specifically, given a transaction, each governor runs a softmax-based function to calculate a probability for each collector that sent and labeled this transaction. The probabilities, calculated using collectors’ reputations as inputs, represent the likelihood of the lead governor selecting the labeled transaction from collectors to consider for further validation. After the lead governor verifies a transaction, all collectors’ reputations are updated in line with the agreement of their labeling and the validity of the transaction as found by the lead governor. We show, both theoretically and empirically, that our protocol can significantly reduce governors’ verification workloads while maintaining firm liveness and high incentives.

Nowadays, sharding is deemed a promising way to save traditional blockchain protocols from their low scalability. However, such a technique also brings several potential risks and a huge communication burden. An improper design may give rise to an inconsistent state among different committees. Further, the communication burden arising from cross-shard transactions, unfortunately, reduces the system's performance. In this paper, we first summarize five essential issues that all sharding blockchain designers face. For each issue, we discuss its key challenge and propose our suggested solutions. In order to break the performance bottlenecks, we design a committee structure and propose a reputation mechanism for selecting leaders. The term reputation in our design reflects each node's honest computation resources. In addition, we present a recovery procedure in case the leader is malicious. Theoretically, we prove that the system is robust under our design. Further simulation results also support this. In addition, the results show that selecting leaders by reputation can dramatically improve the system's performance.

With the development of blockchain applications, the requirements for file storage in blockchain are increasing rapidly. Many protocols, including Filecoin, Arweave, and Sia, have been proposed to provide scalable decentralized file storage for blockchain applications. However, the reliability is not well promised by existing protocols. Inspired by the idea of insurance, we innovatively propose a decentralized file storage protocol in blockchain, named as FileInsurer, to achieve both scalability and reliability. While ensuring scalability by distributed storage, FileInsurer guarantees reliability by enhancing robustness and fully compensating for the file loss. Specifically, under mild conditions, we prove that no more than 0.1% value of all files should be compensated even if half of the storage collapses. Therefore, only a relatively small deposit needs to be pledged by storage providers to cover the potential file loss. Because of lower burdens of deposit, storage providers have more incentives to participate in the storage network. FileInsurer can run in the top layer of the InterPlanetary File System (IPFS), and thus it can be directly applied in Web 3.0, Non-Fungible Tokens, and Metaverse.

Permissioned blockchains take more reliability on participants than permissionless ones. In this poster, we focus on a hierarchical scenario of permissioned blockchains, which includes three types of participants: providers, collectors, and governors. Such a scenario has many applications in the field of IoT data collection, horizontal strategic alliances, etc. Our object is to reduce the cost of the governor's transaction verification. For this purpose, we propose a reputation protocol to help the governor measure the reliability of collectors. Based on the measurement of collectors' reputations, governors can pack high-quality transactions from reliable collectors into blocks, and thus the cost of verifying transactions can be decreased effectively. Through theoretical analysis, our protocol dramatically reduces the verification loss of governors.

Traditional public distributed ledgers have not been able to scale-out well and work efficiently. Sharding is deemed as a promising way to solve this problem. By partitioning all nodes into small committees and letting them work in parallel, we can significantly lower the amount of communication and computation, reduce the overhead on each node’s storage, as well as enhance the throughput of the distributed ledger. Existing sharding-based protocols still suffer from several serious drawbacks. The first thing is that all non-faulty nodes must connect well with each other, which demands a huge number of communication channels in the network. Moreover, previous protocols have faced great loss in efficiency in the case where the honesty of each committee’s leader is in question. At the same time, no explicit incentive is provided for nodes to actively participate in the protocol.We present CycLedger, a scalable and secure parallel protocol for distributed ledger via sharding. Our protocol selects a leader and a partial set for each committee, who are in charge of maintaining intra-shard consensus and communicating with other committees, to reduce the amortized complexity of communication, computation, and storage on all nodes. We introduce a novel semi-commitment scheme between committees and a recovery procedure to prevent the system from crashing even when leaders of committees are malicious. To add incentive for the network, we use the concept of reputation, which measures each node’s trusty computing power. As nodes with a higher reputation receive more rewards, there is an encouragement for nodes with strong computing ability to work honestly to gain reputation. In this way, we strike out a new path to establish scalability, security, and incentive for the sharding-based distributed ledger.