Transactional Consistency Research Articles

AChain: A SQL-Empowered Analytical Blockchain as a Database

In various multi-party cooperations data stored on blockchains (i.e., on-chain data) should be decentralized consistent, verifiable, traceable, and immutable. Online analytical processing (OLAP) services are critical requirements in these applications. However, OLAP performances of existing blockchain systems are much worse than those of relational databases due to the lack of SQL support. In this paper, we propose a novel SQL-empowered analytical blockchain framework, aChain. It fully provides SQL-based OLAP services, while keeping the secure characteristics. Specifically, aChain relationally reorganizes on-chain data to support full SQL executions. Then, a relational versioning scheme is designed to ensure the atomicity and consistency of transactions. Furthermore, SQL-based APIs are designed based on an execute-order-validate architecture. Finally, we demonstrate that the performance of aChain and MySQL (in both cluster and non-cluster models) is at the same level on a typical OLAP benchmark, TPC-H.

Efficient and Secure Data Sharing Scheme on Interoperable Blockchain Database

Interoperable Blockchain Database (IBD) can enable users to execute transactions for sharing data stored in various blockchains maintained by different organizations or communities in a transparent manner. However, compared to traditional distributed databases, IBD can hardly provide high-level security and scalability, which are caused by many factors, such as system architecture, consensus protocol, and interactive pattern. Among them, the consensus protocol is the most critical factor, since the credibility of consensus nodes inside the corresponding blockchains are difficult to be guaranteed. Additionally, the consensus protocol directly affects the verification efficiency for given transactions in IBD. In this paper, we formally concern the problem of secure data sharing in IBD. We present a scheme named <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Hybridchain</i> to execute transactions for sharing data securely and efficiently. We first propose a novel concept named <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Interoperable Consensus Group</i> (ICG) which organizes a set of basic consensus nodes into a group, each of which is responsible for managing at least one local blockchain. Then, we present an interoperable cross-chains consensus protocol to achieve eventual consistency of blockchain transactions. We conduct extensive experiments, and the evaluation results show that our proposed approach achieves superior performance.

Impact of emerging technology on recent criminal scenario

Today the world is fully acknowledged by the digital Technology with a constant dependency of staying connected with everything. In this era of world and after the world experiencing covid pandemic, a new dimension of use of digital/ cyber technology and digitalization in all area including home to office work in day-to-day life emerged with broad spectrum. Technology has given a significant contribution in societal change with digital world in all aspects such as the medical instruments used in surgical treatment of various cardiac, pulmonary diseases orthopedic as well as carcinogenic diseases; cellular connectivity with accuracy &amp;consistency and timeless feasibility of data transfer and money transactions from one hand to another hand. With advancement of technology on a daily basis a significant impact can be seen on the society. This also creates a major impact on the current criminal scenario as well as it has imposed new challenges in the criminal justice system. The present research article is based on the recent case study encountered by the experts in forensic science which will be discuss in detail with their own experiences during presentation.

ADEFGuard: Anomaly detection framework based on Ethereum smart contracts behaviours

Smart contracts are the building blocks of blockchain systems that enable automated peer-to-peer transactions and decentralized services. Smart contracts certainly provide a powerful functional surplus for maintaining the consistency of transactions in applications governed by blockchain technology. Smart contracts have become lucrative and profitable targets for attackers because they can hold a large amount of money. Formal verification and symbolic analysis have been employed to combat these destructive scams by analysing the codes and function calls, yet each scam's vulnerability should be discreetly predefined. In this work, we introduce ADEFGuard, a new anomaly detection framework based on the behaviour of smart contracts, as a new feature. We design a learning and monitoring module to determine fraudulent smart contract behaviours.Our framework is advantageous over basic algorithms in three aspects. First, ADEFGuard provides a unified solution to different genres of scams, relieving the need for code analysis skills. Second, ADEFGuard's inference is orders of magnitude faster than code analysis. Third, the experimental results show that ADEFGuard achieves high accuracy (85%), precision (75%), and recall (90%) for malicious contracts and is potentially useful in detecting new malicious behaviours of smart contracts.

Evaluation of the financial performance of companies using blockchain technology and with high brand value by TOPSIS method

Purpose- Nowadays, thanks to data security, consistency and full-time traceability of transactions, blockchain technology is widely used by companies with high brand value operating in technology, retail, commercial services, media, banking, logistics and defense sectors. Blockchain technology will contribute to these companies reducing their costs, increasing customer satisfaction and thus increasing their financial performance. The purpose of this study is to compare the financial performances of 15 companies that are both among the first Forbes Blockchain 50 companies using blockchain technology and announced in the Brand Finance Global 500 company list with the highest brand value in 2021. Firms in the banking and insurance sector were excluded from the scope of the study. Methodology- TOPSIS method, which is a multi-criteria decision-making method, was applied in the evaluation of the financial performance of these companies. Performance index scores were calculated by using the profitability ratios of the companies. Findings- The analysis reveals that the performance index scores of companies operating in the technology, logistics and commercial services sectors are higher than those of other companies. In addition, it was observed that the brand values of the companies that are in the top 5 according to the performance index score were also high. Conclusion-According to the results of the analysis, the performance index scores of especially technology companies that use blockchain technology and have high brand value were high. It was also observed that the brand values of these companies have increased compared to the previous year. Based upon the findings, it may be concluded that using blockchain technology has a positive effect on the financial performance and brand values of companies. Keywords: Blockchain, TOPSIS, financial performance, financial ratios, brand value JEL Codes: M41, M49, C44

Wolverine: A Scalable and Transaction-Consistent Redactable Permissionless Blockchain

The immutability of blockchains makes it a critical technology for cryptocurrencies, but an imperative need arises for the redaction of on-chain data due to privacy-protecting laws like GPDR. Recently, Ateniese et al. (EuroS&P 2017) proposed an elegant solution to this problem based on chameleon hash functions, followed by many subsequent works. While these works offered a solution to the permissioned blockchain, the approaches were not efficient enough for the permissionless setting, in terms of either security (which may cause inconsistent historical transactions) or performance (only up to a few hundred nodes). In this paper, we investigate this problem and present Wolverine, a redactable permissionless blockchain. First, we present a formal redactable blockchain model, carefully considering transaction consistency. Next, towards a practical scheme, we introduce the novel concept of non-interactive chameleon hash (NITCH). NITCHs dynamically distribute a trapdoor key among a group and each party in the group can compute its partial share without communicating with others. Anyone who possesses enough shares can then find a valid hash collision. To prevent the static group from being compromised after a sufficiently long time, we provide a generic transform from NITCHs to decentralized random beacons (DRBs) and design a committee evolution protocol based on DRBs that refresh the group after every fixed interval of time. Based on NITCH and the committee evolution protocol, we construct Wolverine which offers important features such as scalability, transaction consistency, and public accountability. Finally, we demonstrate the practicality of Wolverine by giving a proof-of-concept implementation based on Bitcoin in Golang.

A Novel Epoch-Based Transaction Consistency Sorting Protocol for DAG Distributed Ledger

Because of the characteristics of decentralization, immutability, and transparency, blockchain has gradually become a new and revolutionary technology, which has far-reaching significance for the development of modern technology. However, the traditional Bitcoin blockchain that supports synchronous consensus suffers from the fatal flaw of low throughput. To improve throughput, a number of DAG distributed ledgers have been proposed that support asynchronous consensus, all of which allow multiple nodes to process concurrent transactions asynchronously. However, most DAG distributed ledgers do not implement consistent sorting of transactions, making it difficult to deploy smart contracts. To overcome this problem, in this paper, an epoch-based transaction consistency sorting protocol for DAG distributed ledger is proposed, which not only provides the possibility for the deployment of smart contracts but also can be used to resolve conflicting transactions in the ledger. Transaction consistency sorting protocol provides a more reasonably ordered list of all transactions by taking scalars, such as the set of their own past and future, parent block, and timestamp. In addition, through theoretical analysis, the stability and rationality of the transaction consistency sorting protocol are proved, and there is no Condorcet cycle. Finally, the simulation results demonstrate the protocol is efficient and achieve a throughput of at least 2000 transactions per second.

A Hierarchical and Location-Aware Consensus Protocol for IoT-Blockchain Applications

Blockchain-based IoT systems can manage IoT devices and achieve a high level of data integrity, security, and provenance. However, incorporating existing consensus protocols in many IoT systems limits scalability and leads to high computational cost and consensus latency. In addition, location-centric characteristics of many IoT applications paired with limited storage and computing power of IoT devices bring about more limitations, primarily due to the location-agnostic designs in blockchains. We propose a hierarchical and location-aware consensus protocol (LH-Raft) for IoT-blockchain applications inspired by the original Raft protocol to address these limitations. The proposed LH-Raft protocol forms local consensus candidate groups based on nodes’ reputation and distance to elect the leaders in each sub-layer blockchain. It utilizes a threshold signature scheme to reach global consensus and the local and global log replication to maintain consistency for blockchain transactions. To evaluate the performance of LH-Raft, we first conduct an extensive numerical analysis based on the proposed reputation mechanism and the candidate group formation model. We then compare the performance of LH-Raft against the classical Raft protocol from both theoretical and experimental perspectives. We evaluate the proposed threshold signature scheme using Hyperledger Ursa cryptography library to measure various consensus nodes’ signing and verification time. Experimental results show that the proposed LH-Raft protocol is scalable for large IoT applications and significantly reduces the communication cost, consensus latency, and agreement time for consensus processing.

A Hierarchy Byzantine Fault Tolerance Consensus Protocol Based on Node Reputation.

A blockchain has been applied in many areas, such as cryptocurrency, smart cities and digital finance. The consensus protocol is the core part of the blockchain network, which addresses the problem of transaction consistency among the involved participants. However, the scalability, efficiency and security of the consensus protocol are greatly restricted with the increasing number of nodes. A Hierarchy Byzantine Fault Tolerance consensus protocol (HBFT) based on node reputation has been proposed. The two-layer hierarchy structure is designed to improve the scalability by assigning nodes to different layers. Each node only needs to exchange messages within its group, which deducts the communication complexity between nodes. Specifically, a reputation model is proposed to distinguish normal nodes from malicious ones by a punish and reward mechanism. It is applied to ensure that the malicious node merely existing in the bottom layer and the communication complexity in the high layer can be further lowered. Finally, a random selection mechanism is applied in the selection of the leader node. The mechanism can ensure the security of the blockchain network with the characteristics of unpredictability and randomicity. Some experimental results demonstrated that the proposed consensus protocol has excellent performance in comparison to some state-of-the-art models.

A Random and Scalable Blockchain Consensus Mechanism

The central piece of blockchain technologies is the consensus algorithm. The consensus is reached via consensus algorithms in the distributed network of the blockchain. The consensus becomes stronger if nearly all the nodes in the blockchain network take part in building the blockchain. Even if some nodes misbehave or malfunction, the consensus should not break down then. Since blockchain networks are distributed, even if some regions of the network or some nodes of the network leave, the blockchain network should not malfunction and it should be consistent. Therefore, the consistency of the blockchain transactions should be assured by all the nodes or nearly all the nodes, or most of the nodes. In other words, the consensus should be the issue of all the nodes. In this work, a novel consensus algorithm is presented to diffuse the mission of building the blockchain to all the nodes. In other words, the consensus should be the issue of all the nodes. In this work, a novel consensus algorithm is presented to diffuse the mission of building the blockchain to all the nodes. The algorithm increases the randomness of nodes and enforces the blockchain network to be more decentralized. Randomness is realized by employing the power of cryptography, especially by using public keys as a characteristic for miners, which are also called signers. Moreover, since the algorithm is realized with a few operations, it contributes to the scalability of the blockchain. Furthermore, digital signatures improve the security level and consistency of the blockchain.

A Partitioned DAG Distributed Ledger with Local Consistency for Vehicular Reputation Management

Vehicular reputation maintenance with distributed ledger is aimed at establishing trust among vehicles randomly meeting in a Vehicular Ad-hoc Network (VANET). It is, however, challenging in VANET, as congested areas in road networks, brought by traffic tides or accidents, challenge the ledger performance. Meanwhile, the reputation update is highly dependent on transaction consensus of the distributed ledger. To solve the problem, this paper proposes deploying directed acyclic graph- (DAG-) based distributed ledgers on vehicles, which use the vehicular distribution to adapt the unpredictable reputation update. Specifically, we first propose a partitioned DAG-based distributed ledger to manage vehicular reputation in partitioned VANET. Secondly, we introduce a novel reputation evaluation method to encourage vehicles to contribute to VANET interaction and ledger consensus maintenance, which can remedy the topology churn of the ledger network due to the mobility of VANET. Finally, we design a reputation update method based on the consistency of transactions in the partition to facilitate trust establishment. Experimental results on a real-world dataset show that the proposed ledger and reputation update method is effective and feasible in the large-scale dynamic VANET.

Privacy Preserving distributed smart grid system based on Hyperledger Fabric and Wireguard

SummarySmart grid has drawn a lot of attention and investment in recent years, which not only helps the modern generation and distribution of traditional power but also highly widens the application of renewable energy sources. However, the main challenges in the application of smart grid are 1. the privacy preservation of users' information and 2. the trustful transmission channel among peers. In order to solve these problems, VPN and blockchain can be considered since they have some features perfectly suitable for these situations. In this paper, we propose a smart grid system based on WireGuard and Hyperledger Fabric to solve the problems mentioned above. And we also implement the whole system and give a view by web application. What's more, all the functionalities are displayed and tested, including building a smart device simulator, deploying data visualization and making some performance evaluations about transactions and WireGuard communication. Experiment results show that the introduction of WireGuard into network infrastructure does not cause too much loss of bandwidth and delay, but it ensures a certain degree of communication security. And Fabric provides the consistency and traceability of transactions in smart grid system.

Extending LADM to support workflows and process models

In order to be able to guarantee the overall correctness of data, updating of Land administration system’s data must be executed following a formally and technically clearly defined and controllable procedure (process). In general technical sense, correctness of data primarily depends on its consistency. Databases natively support enforcing consistency of transactions over the data but lack the flexibility needed for modelling business processes and do not natively support operating in heterogeneous IT environments (web services, various external and loosely coupled systems). WorkFlow Management Systems (WFMS) with integrated transactional properties provide a technological platform which supports enforcing consistency within heterogeneous IT environments. Within the scope of our previous work and in order to provide a standardised means for modelling of dynamic component of Land Administration Systems (LASs), we developed an extension to LADM for integrating processes into LADM. We propose to extend the LADM with a new class LA_Process, as a sub-class of the existing LADM class LA_Source. Also, LA_Process is associated to descendants of LA_Source (spatial and administrative source) and versioned object. Associating those classes to LA_Process enables executing processes over instances of LADM classes in a versioning supported manner and linked to underlying formal documents. This extension is proposed to be included in the second edition of the LADM which is under development (Lemmen et al., 2019). Within this work we further revise LA_Process in order to broaden its scope and to consider processes on LADM classes outside of the SpatialUnit package. In addition to this proposed extension of the LADM we give an example of hierarchical modelling of LAS-processes. We define topmost two levels of processes with a basic set of activities which are applicable to any LAS. As the granularity of activities increases, processes may become dependent on a particular LAS but the general concepts from topmost level should be followed. We use UML (Unified Modelling Language) Activity Diagrams to model processes in LAS.

A Dynamic Data Slice Approach to the Vulnerability Analysis of E-Commerce Systems

The e-commerce business process net (EBPN) is a novel formal model for describing an e-commerce system and its interactive parts, such as shoppers, merchants, and the third-party payment platforms. Vulnerability analysis has a great impact on the trustworthiness of EBPN, which is an issue stemming from data inconsistency problems. Data inconsistency problems affect the consistency of the EBPN transaction analysis. The underlying causes of inconsistent data are closely related to concurrent operations, such as control flow and data flow. However, most of the existing detection methods have difficulties characterizing the vulnerabilities and interactions of control and data flows. In this paper, we propose a new method based on the dynamic data slice (DDS) that considers both transaction consistency and data state consistency. First, by analyzing control flow characteristics of EBPN, we obtain the dynamic slice. This dynamic slice is based on all paths of the EBPN reachability graph. Second, we perform the data inconsistency analysis by considering both transaction consistency and data-state consistency. Based on these, we construct a DDS to characterize the behavioral logic and the data-dependence information. The DDS acquires the dynamic data firing sequence. Based on that sequence and a given data marking, we can construct the DDSs for several types of EBPNs. Constructing the DDS can be completed in polynomial time. The DDS is designed to characterize the behavioral logic and data-dependence information. Based on these, we design a method to judge the data constraints. This method satisfies the EBPN need for transaction consistency by considering both the control and data states. In addition, according to the data-dependence information, we can lock the vulnerable regions caused by abnormal trading data in the system. Finally, we give a method to compute the vulnerability level.

Research on Data Verification and Exchange of Heterogeneous Blockchains for Electricity Application

This paper proposes a verification and exchange method for cross-chain transactions of heterogeneous blockchains for electricity application scenarios and designs a chain-level cross-chain event verification mechanism. For a blockchain platform that requires cross-chain transactions, a Merkel-structured cross-chain event tree is systematically constructed with the collected cross-chain transactions in the generation stage of the block. The target blockchain platform verifies the credibility of cross-chain events based on the Merkel-structured cross-chain event tree and related credible proofs. Cross-chain events are captured through smart contract events, and cross-chain event Merkel trees and Merkel paths are constructed to achieve credible and rapid verification of cross-chain events. The cross-chain experiments are carried out in the main-side chain mode of electricity business scenario, and the integrity of cross-chain transaction is ensured by a cross-chain transaction consistency guarantee mechanism, so as to achieve the purpose of trusted circulation and secure transactions of electricity business data between different application chains.

Asymmetric-partition replication for highly scalable distributed transaction processing in practice

Database replication is widely known and used for high availability or load balancing in many practical database systems. In this paper, we show how a replication engine can be used for three important practical cases that have not previously been studied very well. The three practical use cases include: 1) scaling out OLTP/OLAP-mixed workloads with partitioned replicas, 2) efficiently maintaining a distributed secondary index for a partitioned table, and 3) efficiently implementing an online re-partitioning operation. All three use cases are crucial for enabling a high-performance shared-nothing distributed database system. To support the three use cases more efficiently, we propose the concept of asymmetric-partition replication , so that replicas of a table can be independently partitioned regardless of whether or how its primary copy is partitioned. In addition, we propose the optimistic synchronous commit protocol which avoids the expensive two-phase commit without sacrificing transactional consistency. The proposed asymmetric-partition replication and its optimized commit protocol are incorporated in the production versions of the SAP HANA in-memory database system. Through extensive experiments, we demonstrate the significant benefits that the proposed replication engine brings to the three use cases.

Legal Transitions without Legitimate Expectations*

Legal Transitions without Legitimate Expectations*

Analysis of Proof-of-Work-Based Blockchains Under an Adaptive Double-Spend Attack

In this article, we study the performance of blockchains by analyzing the common prefix depth, chain quality coefficient, and chain growth speed coefficient. These three parameters characterize the liveness and consistency of transactions which are important for the proper operation of the blockchain. We examine how these three parameters are affected under an adaptive double-spend attack (ADSA). To maintain the performance of a blockchain against ADSA, the user nodes can use a larger number, $z$ , of confirmation blocks for validating a transaction. A comparison of the values of $z$ needed to achieve a given target probability of successful attack is provided for ADSA and the traditional double-spend attack with different system models. The results indicate that a larger value of $z$ is required under ADSA. A more realistic reward model for attackers is also introduced. It is found that the expected reward of an attacker decreases rapidly to zero as $z$ is increased.

A pure hardware-driven scheduler for enhancing bank-level parallelism in a persistent memory controller

Researchers are attempting to exploit the non-volatile nature of Persistent Memory (PM) in various applications. To utilize persistence, many solutions enforce strict, sequential write orderings that are propagated through the cache hierarchy, inevitably resulting in extra write requests. Other solutions introduce persistence logging operations to ensure transactional consistency, which also introduces extra writes. To rationally schedule these write requests, current work classifies the sources of write requests into subtypes at the software level based on the characteristics of the application, subsequently transferring the classified requests as hint messages to the memory controller level for guiding scheduling. However, categorizing diverse applications requires incompatible modifications to software and can degrade both the performance and fairness of the results with respect to low bank-level parallelism and low row-buffer locality. To address these problems, we bypass software intervention and propose PHD-scheduler, a Pure Hardware-Driven scheduler for enhancing bank-level parallelism in PM controller. PHD-scheduler is composed of three main ideas: (1) PHD-scheduler moves the classification into the PM’s controller level rather than intervening in the compatibility of the software, (2) it introduces a dynamic computing mechanism to ensure bank access from centralization to distribution, and (3) it maximizes row buffer locality by reshuffling memory requests with three novel criteria to achieve an appropriate batch scheduling. The experimental results show that PHD-scheduler achieves an average bank-level parallelism improvement of 11.8%. Moreover, performance and fairness are improved by 4.2% and 3.3%, respectively.

Revealing the Character of Nodes in a Blockchain With Supervised Learning

The term blockchain has its roots in cryptocurrencies. However, its applications are now more widespread, and in many areas, this technology has become the foundation of the distributed ledger. The blockchain protocol assumes that all the participants of the system are both contributors and safeguards of this ledger, since the lack of a trusted third party requires other security precautions in order to maintain the consistency of transactions. In this work, we investigate whether for the participants of a blockchain-based system that does not require revealing the character explicitly, it can be discovered by other means. In order to verify this, we built and publicly released a dataset of nearly 9,000 addresses of nodes in the most popular cryptocurrency - Bitcoin, and then labelled them. These labels represent the character the nodes have in the network, e.g. miners or exchanges. We then developed a set of features that quantify the behaviour of nodes in the network and used supervised machine learning algorithms to find out whether the character of nodes can be revealed based on these features. Our results demonstrate, due to the F-score reaching over 95% in the best-performing algorithms, that it is hard to hide the role the node has in a blockchain-based network. These results indicate that to build trustworthy blockchain-based systems that fully comply with original blockchain assumptions, specific countermeasures are needed in order to preserve the desired level of anonymity.