IU Indianapolis ScholarWorks :: Browsing by Subject "blockchain"

Browsing by Subject "blockchain"

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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.
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.
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.
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.
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.
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.
Incentive Mechanism Design for Joint Resource Allocation in Blockchain-Based Federated Learning
(IEEE, 2023-05) Wang, Zhilin; Hu, Qin; Li, Ruinian; Xu, Minghui; Xiong, Zehui; Computer and Information Science, Purdue School of Science
Blockchain-based federated learning (BCFL) has recently gained tremendous attention because of its advantages, such as decentralization and privacy protection of raw data. However, there has been few studies focusing on the allocation of resources for the participated devices (i.e., clients) in the BCFL system. Especially, in the BCFL framework where the FL clients are also the blockchain miners, clients have to train the local models, broadcast the trained model updates to the blockchain network, and then perform mining to generate new blocks. Since each client has a limited amount of computing resources, the problem of allocating computing resources to training and mining needs to be carefully addressed. In this paper, we design an incentive mechanism to help the model owner (MO) (i.e., the BCFL task publisher) assign each client appropriate rewards for training and mining, and then the client will determine the amount of computing power to allocate for each subtask based on these rewards using the two-stage Stackelberg game. After analyzing the utilities of the MO and clients, we transform the game model into two optimization problems, which are sequentially solved to derive the optimal strategies for both the MO and clients. Further, considering the fact that local training related information of each client may not be known by others, we extend the game model with analytical solutions to the incomplete information scenario. Extensive experimental results demonstrate the validity of our proposed schemes.
Proof of User Similarity: The Spatial Measurer of Blockchain
(IEEE, 2024-05) Wang, Shengling; Shi, Lina; Shi, Hongwei; Zhang, Yifang; Hu, Qin; Cheng, Xiuzhen; Computer and Information Science, Purdue School of Science
Although proof of work (PoW) consensus dominates the current blockchain-based systems mostly, it has always been criticized for the uneconomic brute-force calculation. As alternatives, energy-conservation and energy-recycling mechanisms heaved in sight. In this article, we propose proof of user similarity (PoUS), a distinct energy-recycling consensus mechanism, harnessing the valuable computing power to calculate the similarities of users, and enact the calculation results into the packing rule. However, the expensive calculation required in PoUS challenges miners in participating, and may induce plagiarism and lying risks. To resolve these issues, PoUS embraces the best-effort schema by allowing miners to compute partially. Besides, a voting mechanism based on the secure two-party computation and Bayesian truth serum is proposed to guarantee privacy-preserved voting and truthful reports. Noticeably, PoUS distinguishes itself in recycling the computing power back to blockchain since it turns the resource wastage to facilitate refined cohort analysis of users, serving as the spatial measurer and enabling a searchable blockchain. We build a prototype of PoUS and compare its performance with PoW. The results show that PoUS outperforms PoW in achieving an average transaction per second (TPS) improvement of 24.01% and an average confirmation latency reduction of 43.64%. Besides, PoUS functions well in mirroring the spatial information of users, with negligible computation time and communication cost.
Resource Optimization for Blockchain-Based Federated Learning in Mobile Edge Computing
(IEEE, 2024-05) Wang, Zhilin; Hu, Qin; Xiong, Zehui; Computer and Information Science, Purdue School of Science
With the booming of mobile edge computing (MEC) and blockchain-based blockchain-based federated learning (BCFL), more studies suggest deploying BCFL on edge servers. In this case, edge servers with restricted resources face the dilemma of serving both mobile devices for their offloading tasks and the BCFL system for model training and blockchain consensus without sacrificing the service quality to any side. To address this challenge, this article proposes a resource allocation scheme for edge servers to provide optimal services at the minimum cost. Specifically, we first analyze the energy consumption of the MEC and BCFL tasks, considering the completion time of each task as the service quality constraint. Then, we model the resource allocation challenge into a multivariate, multiconstraint, and convex optimization problem. While solving the problem in a progressive manner, we design two algorithms based on the alternating direction method of multipliers (ADMMs) in both homogeneous and heterogeneous situations, where equal and on-demand resource distribution strategies are, respectively, adopted. The validity of our proposed algorithms is proved via rigorous theoretical analysis. Moreover, the convergence and efficiency of our proposed resource allocation schemes are evaluated through extensive experiments.
Self-sovereign identity empowered non-fungible patient tokenization for health information exchange using blockchain technology
(Elsevier, 2023-05) Zhuang, Yan; Shyu, Chi-Ren; Hong, Shenda; Li, Pengfei; Zhang, Luxia; Biomedical Engineering and Informatics, Luddy School of Informatics, Computing, and Engineering
Background: Patient tokenization is a novel approach that allows anonymous patient-level linkage across healthcare facilities, minimizing the risk of breaching protected health information in health information exchange (HIE). Most patient tokenization is the centralized approach that is unable to address data security concerns fundamentally. Non-Fungible Tokens (NFT), which are non-transferable cryptographic assets on the blockchain, have the potential to provide secure, decentralized, and trustworthy patient tokenization. Self-Sovereign Identity (SSI) is a user-centric approach to verify the ownership of NFTs in a decentralized manner. Methods We have developed a blockchain architecture that contains four modules: (1) Creation module for NFTs creation, (2) Linkage module to link the local patients' accounts to their NFTs, (3) Authentication module that allows patients to permit healthcare providers to access their token, and (4) Exchange module, which involves the HIE process and the validation of the legitimacy of the token through SSI. Results A case study has been conducted on the proposed architecture. Over 3 million transactions have been completed successfully with a blockchain validation and written time of 1.17 s on average. A stability test has also been conducted with a higher throughput of 200 transactions per second running for an hour with an average transaction processing time of 1.42 s. Conclusions This study proposed a blockchain architecture that achieves SSI-enabled NFT-based patient tokenization. Our architecture design, implementation, and case studies have demonstrated the feasibility and potential of NFT with SSI to establish a secure, transparent, and patient-centric identity management and HIE.

Browsing by Subject "blockchain"

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