Browsing by Subject "blockchain"

Now showing 1 - 8 of 8
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    Black Swan in Blockchain: Micro Analysis of Natural Forking
    (IEEE, 2022-11-04) Shi, Hongwei; Wang, Shengling; Hu, Qin; Cheng, Xiuzhen; Computer and Information Science, School of Science
    Natural forking is tantamount to the “black swan” event in blockchain since it emerges unexpectedly with a small probability, and may incur low resource utilization and costly economic loss. The ongoing literature analyzes natural forking mainly from the macroscopic perspective, which is insufficient to further understand this phenomenon since it roots in the instantaneous difference between block creation and propagation microscopically. Hence, in this paper, we fill this gap by leveraging the large deviation theory to conduct the first micro study of natural forking, aiming to reveal its inherent mechanism substantially. Our work is featured by 1) conceptual innovation . We creatively abstract the blockchain overlay network as a “service system”. This allows us to investigate natural forking from the perspective of “supply and demand”. Based on this, we can identify the competitive dynamics of blockchain and construct a queuing model to characterize natural forking; 2) progressiveness . We scrutinize the natural forking probability as well as its decay rate via a three-step scheme from simple to complex, which are the single-source i.i.d. scheme, the single-source non-i.i.d. scheme, and the many-source non-i.i.d. scheme. By doing so, we can answer when and how fast should we take actions and what actions should we take against natural forking. Our valuable findings can not only put forward decisive guidelines theoretically from the top level, but also engineer optimal countermeasures operationally on a practical level to thwart natural forking.
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    Blockchain-based Edge Resource Sharing for Metaverse
    (IEEE, 2022-10) Wang, Zhilin; Hut, Qin; Xu, Minghui; Jiang, Honglu; Computer and Information Science, School of Science
    Although Metaverse has recently been widely studied, its practical application still faces many challenges. One of the severe challenges is the lack of sufficient resources for computing and communication on local devices, resulting in the inability to access the Metaverse services. To address this issue, this paper proposes a practical blockchain-based mobile edge computing (MEC) platform for resource sharing and optimal utilization to complete the requested offloading tasks, given the heterogeneity of servers' available resources and that of users' task requests. To be specific, we first elaborate the design of our proposed system and then dive into the task allocation mechanism to assign offloading tasks to proper servers. To solve the multiple task allocation (MTA) problem in polynomial time, we devise a learning-based algorithm. Since the objective function and constraints of MTA are significantly affected by the servers uploading the tasks, we reformulate it as a reinforcement learning problem and calculate the rewards for each state and action considering the influences of servers. Finally, numerous experiments are conducted to demonstrate the effectiveness and efficiency of our proposed system and algorithms.
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    A Correlated Equilibrium based Transaction Pricing Mechanism in Blockchain
    (IEEE, 2020-05) Hu, Qin; Nigam, Yash; Wang, Zhilin; Wang, Yawei; Xiao, Yinhao; Computer and Information Science, School of Science
    Although transaction fees are not obligatory in most of the current blockchain systems, extensive studies confirm their importance in maintaining the security and sustainability of blockchain. To enhance blockchain in the long term, it is crucial to design effective transaction pricing mechanisms. Different from the existing schemes based on auctions with more consideration about the profit of miners, we resort to game theory and propose a correlated equilibrium based transaction pricing mechanism through solving a pricing game among users with transactions, which can achieve both the individual and global optimum. To avoid the computational complexity exponentially increasing with the number of transactions, we further improve the game-theoretic solution with an approximate algorithm, which can derive almost the same results as the original one but costs significantly reduced time. Experimental results demonstrate the effectiveness and efficiency of our proposed mechanism.
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    A distributed blockchain ledger for supply chain
    (2017) Wu, Haoyan; Miled, Zina
    Affordable and reliable supply chain visibility is becoming increasingly important as the complexity of the network underlying supply chains is becoming orders of magnitudes higher compared to a decade ago. Moreover, this increase in complexity is starting to reflect on the cost of goods and their availability to the consumers. Optimizing the physical distribution phase in supply chain by providing increased visibility to trading partners can directly reduce product cost. Current supply chain information systems often lack the ability to cost-effectively relay ground truth in- formation in near real time to all stakeholders and most importantly to the supplier and the customer during the transport of the shipment. This thesis presents a solu- tion that addresses this gap through a distributed architecture. The solution enables small, medium and large businesses to interact in a dynamic and shipment-centric manner through a private blockchain sub-ledger that digitizes the transfer of custody for each shipment. Information in this private ledger is augmented by a public event ledger that reflects the movement of the shipment in real time. Third party monitors are engaged in the validation of the geolocation of the shipments by posting their physical proximity in the form of events to the public ledger.
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    A Distributed Ledger for Supply Chain Physical Distribution Visibility
    (MDPI, 2017-11-02) Wu, Haoyan; Li, Zhijie; King, Brian; Ben Miled, Zina; Wassick, John; Tazelaar, Jeffrey; Electrical and Computer Engineering, School of Engineering and Technology
    Supply chains (SC) span many geographies, modes and industries and involve several phases where data flows in both directions from suppliers, manufacturers, distributors, retailers, to customers. This data flow is necessary to support critical business decisions that may impact product cost and market share. Current SC information systems are unable to provide validated, pseudo real-time shipment tracking during the distribution phase. This information is available from a single source, often the carrier, and is shared with other stakeholders on an as-needed basis. This paper introduces an independent, crowd-validated, online shipment tracking framework that complements current enterprise-based SC management solutions. The proposed framework consists of a set of private distributed ledgers and a single blockchain public ledger. Each private ledger allows the private sharing of custody events among the trading partners in a given shipment. Privacy is necessary, for example, when trading high-end products or chemical and pharmaceutical products. The second type of ledger is a blockchain public ledger. It consists of the hash code of each private event in addition to monitoring events. The latter provide an independently validated immutable record of the pseudo real-time geolocation status of the shipment from a large number of sources using commuters-sourcing.
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    A game theoretic analysis on block withholding attacks using the zero-determinant strategy
    (ACM, 2019-06) Hu, Qin; Wang, Shengling; Cheng, Xiuzhen; Computer and Information Science, School of Science
    In Bitcoin's incentive system that supports open mining pools, block withholding attacks incur huge security threats. In this paper, we investigate the mutual attacks among pools as this determines the macroscopic utility of the whole distributed system. Existing studies on pools' interactive attacks usually employ the conventional game theory, where the strategies of the players are considered pure and equal, neglecting the existence of powerful strategies and the corresponding favorable game results. In this study, we take advantage of the Zero-Determinant (ZD) strategy to analyze the block withholding attack between any two pools, where the ZD adopter has the unilateral control on the expected payoffs of its opponent and itself. In this case, we are faced with the following questions: who can adopt the ZD strategy? individually or simultaneously? what can the ZD player achieve? In order to answer these questions, we derive the conditions under which two pools can individually or simultaneously employ the ZD strategy and demonstrate the effectiveness. To the best of our knowledge, we are the first to use the ZD strategy to analyze the block withholding attack among pools.
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    Transaction pricing mechanism design and assessment for blockchain
    (Elsevier, 2022-03) Wang, Zhilin; Hu, Qin; Wang, Yawei; Xiao, Yinhao; Computer and Information Science, School of Science
    The importance of transaction fees in maintaining blockchain security and sustainability has been confirmed by extensive research, although they are not mandatory in most current blockchain systems. To enhance blockchain in the long term, it is crucial to design effective transaction pricing mechanisms. Different from the existing schemes based on auctions with more consideration about the profit of miners, we resort to game theory and propose a correlated equilibrium based transaction pricing mechanism through solving a pricing game among users with transactions, which can achieve both the individual and global optimum. To avoid the computational complexity exponentially increasing with the number of transactions, we further improve the game-theoretic solution with an approximate algorithm, which can derive almost the same results as the original one but costs significantly reduced time. We also propose a truthful assessment model for pricing mechanism to collect the feedback of users regarding the price suggestion. Extensive experimental results demonstrate the effectiveness and efficiency of our proposed mechanism.
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    zk-PCN: A Privacy-Preserving Payment Channel Network Using zk-SNARKs
    (IEEE, 2022-11) Yu, Wenxuan; Xu, Minghui; Yu, Dongxiao; Cheng, Xiuzhen; Hu, Qin; Xiong, Zehui; Computer and Information Science, School of Science
    Payment channel network (PCN) is a layer-two scaling solution that enables fast off-chain transactions but does not involve on-chain transaction settlement. PCNs raise new privacy issues including balance secrecy, relationship anonymity and payment privacy. Moreover, protecting privacy causes low transaction success rates. To address this dilemma, we propose zk-PCN, a privacy-preserving payment channel network using zk-SNARKs. We prevent from exposing true balances by setting up public balances instead. Using public balances, zk-PCN can guarantee high transaction success rates and protect PCN privacy with zero-knowledge proofs. Additionally, zk-PCN is compatible with the existing routing algorithms of PCNs. To support such compatibility, we propose zk-IPCN to improve zk-PCN with a novel proof generation (RPG) algorithm. zk-IPCN reduces the overheads of storing channel information and lowers the frequency of generating zero-knowledge proofs. Finally, extensive simulations demonstrate the effectiveness and efficiency of zk-PCN in various settings.