Asma A. Alhussayen, Kamal Jambi, Maher Khemakhem, Fathy Eassa
Blockchain interoperability has become an essential requirement for the advancement of blockchain technology in numerous fields. Enterprise organizations are increasingly utilizing permissioned blockchains to manage and store their organizations’ data and transactions in a private immutable ledger. Interoperability enables permissioned blockchain platforms to communicate and exchange information which is paramount for fully exploiting permissioned blockchains as facilitators for B2B applications. Additionally, the cross-network invocation of smart contracts under agreed conditions enhances business operations. Blockchain oracles can enable permissioned blockchain interoperability and cross-network transactions in a seamless and private manner. However, they have not been studied in the literature as interoperability techniques between permission blockchains. This study proposes a blockchain oracle interoperability technique designed specifically for permissioned blockchain platforms. We presented the architecture of the blockchain oracle interoperability technique and a prototypical implementation to demonstrate the practicality of the proposed technique. In addition, we obtained cross-network transaction latency measurements and analyzed the results.
Process (or workflow) execution on blockchain suffers from limited scalability; specifically, costs in the form of transactions fees are a major limitation for employing traditional public blockchain platforms in practice. Research, so far, has mainly focused on exploring first (Bitcoin) and second-generation (e.g., Ethereum) blockchains for business process enactment. However, since then, novel blockchain systems have been introduced - aimed at tackling many of the problems of previous-generation blockchains. We study such a system, Algorand, from a process execution perspective. Algorand promises low transaction fees and fast finality. However, Algorand's cost structure differs greatly from previous generation blockchains, rendering earlier cost models for blockchain-based process execution non-applicable. We discuss and contrast Algorand's novel cost structure with Ethereum's well-known cost model. To study the impact for process execution, we present a compiler for BPMN Choreographies, with an intermediary layer, which can support multi-platform output, and provide a translation to TEAL contracts, the smart contract language of Algorand. We compare the cost of executing processes on Algorand to previous work as well as traditional cloud computing. In short: they allow vast cost benefits. However, we note a multitude of future research challenges that remain in investigating and comparing such results.
Capital markets post-trade processes (trade capture, clearing, settlement and reconciliation) are currently limited by excessive data fragmentation, reconciliation lag and high operational expenses. A central architecture creates "data silos" which restricts scalability, transparency and flexibility of integration between disparate financial institutions. This paper introduces a unified, technically advanced framework integrating Hyperledger Fabric (HLF); a permissioned Distributed Ledger Technology (DLT) with cloud native micro services as a means of creating a scalable, fault-tolerant and transparent ecosystem. By implementing Kubernetes based orchestration and Istio service mesh, we have shown how a legacy monolithic system can be replaced with a dynamic, distributed system capable of supporting high frequency transactions. Simulation results on large scale cloud based test beds show that our predictive resource orchestration framework achieves a 5 times greater throughput than a typical standalone DLT deployment and a 26-fold reduction in 95th percentile (p95) latency. The framework offers a scalable way of provisioning AI driven FinTech workloads with significantly increased reliability and decreased Total Cost of Ownership (TCO).
Decentralized finance (DeFi) offers a range of financial instruments and services that leverage the capabilities of web3 technology. Maker protocol, which enables users to obtain loans backed by cryptocurrencies, is one of them. Unlike traditional banks, Maker’s data is transparently recorded on the Ethereum blockchain. In this research paper, we focus on analyzing the lending aspect of Maker from a traditional finance perspective. To achieve this, we create a unique dataset with loan portfolios from the MakerDAO project, making it the first dataset of its kind in the DeFi field. This publicly available dataset contains essential financial characteristics related to borrowing, including balance, loss given default, annual equivalent rate, and probability of default. Additionally, we develop a specialized mathematical model tailored specifically to this project. This model allows us to estimate the probability of default by considering the presence of crypto-collateral and utilizing Brownian motion passage levels. The results of this study provide valuable insights into lending practices in DeFi projects. They also help bridge the gap between traditional finance and blockchain-based financial services.
In recent years, blockchain technology has received attention because of its decentralized, immutable and other characteristics, but it faces storage and retrieval challenges. To address these challenges, this paper introduces IOTA distributed ledger technology, which solves the scalability and cost problems of traditional blockchains. By analyzing and experimenting the Tangle, the underlying consensus structure of IOTA, this paper reveals the main factors affecting its development, and proposes a segmented adaptive cutting-edge transaction selection algorithm to optimize the system performance. At the same time, based on IOTA distributed ledger, this paper proposes a data encryption storage and retrieval scheme, which speeds up the data link and retrieval speed, and ensures the integrity and security of data. Finally, this paper discusses the application of blockchain in accounting informatization, and puts forward the scheme of building a new generation of accounting informatization platform, which is of great value to the construction of accounting informatization.
In the current digital landscape, almost everyone is on social media or various social media platforms. People use social media for a plethora of purposes, which include staying connected with friends and family, accessing information and updates about ongoing events, entertainment, networking with professionals, expressing themselves to a wide range of users, promoting businesses, joining online communities and engaging in various activities which has led to an increase in the consumption and usage of online social networks (OSN). One of the reasons for such a growth is their features such as ubiquitous access, on-demand service, friendship networks, user engagement strategies like recommendation engines, etc. However, there are various limitations to the current approach, such as the centralization of control, lack of data ownership, poor access control, fake news, bot accounts, censorship, digital rights management issues, etc. To address these limitations, a paradigm shift is necessary. This paper aims to develop a social media application where every post can be converted to a Non-Fungible Token (NFT) and be sold to earn money. Interplanetary File System (IPFS) is used as the decentralized storage. Algorithms for all the functionalities of the applications are given along with an algorithm for a reputation score for every user and their posts in social media are also proposed.
Open access
3 source records
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
In the evolving domain of blockchain, a critical challenge lies in the performance analysis of blockchains under controlled test conditions. This paper focuses on validating the Blockchain Benchmarking Framework (BBF), developed for the evaluation of blockchain protocols in a controlled environment. The BBF’s robustness and versatility are demonstrated through its application to the official Docker clients of Ripple’s XRP Ledger (XRPL) and Ethereum, deployed in private, local and controlled environments. These deployments are utilized to simulate network dynamics, transaction throughput, and resilience in a variety of scenarios. Our methodology encompasses tests ranging from standard operational conditions to adverse scenarios, including node failures and simulated double-spend attacks. These controlled environments are essential for evaluating the BBF’s efficacy in stress testing blockchain protocols and assessing their stability and robustness. The BBF’s ability to accurately capture and analyze performance characteristics is highlighted, providing insights into the operational mechanics, scalability, and resilience of these blockchain clients. The findings emphasize the BBF’s adaptability and effectiveness in managing different blockchain protocols, reaffirming its potential for broader application in pre-launch testing and analysis of blockchain performance. This study contributes to the understanding of how blockchain clients can be preliminarily assessed before mainnet deployment as well as to validate all the design decisions made by the protocol under different settings and synthetic scenarios.
Hyperledger Fabric (shortened to Fabric) is an open-source, enterprise-level, permissioned distributed ledger technology platform with a highly modular, configurable architecture. It supports writing smart contracts in general-purpose programing languages and has become the preferred choice for enterprise-level blockchain applications. However, the transaction throughput of the Fabric system remains a critical factor that restricts the further application of this technology in various fields. Therefore, it is necessary to evaluate and optimize the performance of the Fabric blockchain platform. Existing performance modeling methods need to be improved in terms of compatibility and effectiveness. To address this, we propose a performance-compatible modeling method for Fabric using queuing theory, which considers the limited transaction pool and the situation where node groups are attacked. Using the Fabric 2.0 version as an example, we have established a model of the transaction process in the Fabric network. By analyzing the model’s continuous 3D time Markov process, we solved the system stationary equation and obtained analytical expressions for performance indicators such as system throughput, system steady-state queue length, and system average response time. We conducted extensive analyses and simulations to verify the models’ and formulations’ accuracy and validity. We believe this approach can be extended to various scenarios in other blockchain systems.
Yi-Jen Su, Chao-Ho Chen, Tsong-Yi Chen, Chun-Wei Yeah
The main causes for the risks of used-car trading lie in the information asymmetry between buyers and sellers and the absence of a trust mechanism. This study proposed applying the Ethereum blockchain and InterPlanetary File System (IPFS) to construct a used-car trading and management information system that supports decentralized data storage services. This mechanism could support the permanent storage, immutability, and traceability of car maintenance data through the operation of smart contracts. Furthermore, car information is stored and managed by IPFS. Slither monitors the security of this system by detecting security bugs in the operation of smart contracts.
Ethereum is a rapidly evolving blockchain with new features as well as new vulnerabilities being introduced regularly. Interaction with the network is costly compared to other blockchains or traditional software systems. When starting to develop on Ethereum, a supported smart contract programming language needs to be learned, most notably Solidity. Having various pitfalls raises the question of what the best practices for the safe and efficient usage of Ethereum are. This study primarily aims to combine knowledge from existing research resources, while also introducing new approaches learned from practical smart contract development analysis and inquiry, which are subsequently compiled into lists of best practices. The most important findings are that code quality and security should be prioritized. Moreover, some simple gas-saving strategies can help to decrease interaction costs with little effort.
Ethereum has emerged as a leading platform for decentralized applications (dApps) due to its robust smart contract capabilities. One of the critical issues in the Ethereum ecosystem is Maximal Extractable Value (MEV), a concept that has gained significant attention in the blockchain community. However, MEV has remained a major challenge with significant implications for the platform's operation and integrity. This paper introduces the FairFlow protocol, a novel framework designed to mitigate the effects of MEV within Ethereum's existing infrastructure. The protocol aims to provide a more equitable environment, preventing exploitation by miners or validators, and protecting user data. The combined approach of auction-based block space allocation and randomized transaction ordering significantly reduces the potential for MEV exploitation.
Mohsin Kamal, Muhammad Tariq, Mian Ahmad Jan, Houbing Song
Blockchain technology has found applications across diverse domains owing to its ability to establish trust in a decentralized manner. Nevertheless, the integration of blockchain into critical infrastructure domains encounters significant challenges posed by the computational demands and storage requirements associated with the proof-of-work puzzle during the mining process. This scenario becomes particularly complex in the context of applications within the Industrial Internet of Things (IIoT), where stringent timeliness constraints are inherent, notably in functions such as intrusion detection and control. This paper presents a novel solution that takes into account the time-sensitive nature of application constraints within the IIoT. Specifically, we focus on online functions involving intrusion detection and control. By doing so, we address the imperative need for timely and secure data delivery, crucial in maintaining the integrity of hard-to-tamper ledger blocks. These blocks encapsulate measurements that are seamlessly utilized by various system functions and components. The proposed approach optimizes the utilization of heterogeneous resources governing blockchain computations. This optimization ensures that the desired properties for logging within the blockchain are met, enabling the prompt delivery of measurements. The novel collaborative mining technique entails the sharing of nonce ranges among miners, which effectively reduces the overall mining time and enhances the efficiency of the process.
Carlos A. Estrada, S. Naranjo, Veronica J. Toasa, Sang Guun Yoo
In the context of today's digital era, blockchain technology has established itself as one of the transformative innovations that pushes the boundaries of data management and security. Given this situation, the present work carries out a systematic literature review of this technology. It examines three essential aspects of the blockchain world. First of all, the various fields of application of this technology are analyzed, which go beyond the field of cryptocurrencies and extend to other industries such as the internet of things, supply chains, health, identity management, business, and much more. Secondly, the most used platforms for the development of blockchain applications are studied, such as Ethereum, Hyperledger Fabric, Solana among others; each platform has its particular characteristics, compatible programming languages and recommended application areas. Finally, an analysis of the consensus protocols is carried out, such as Proof of Work, Proof of Stake, Proof of Authority, RAFT, among others. This literature review provides a comprehensive overview of blockchain, shedding light on its versatility, challenges, and transformative potential in a variety of industries. It offers a solid foundation for those interested in exploring and taking advantage of the blockchain revolution in the 21st century.
In blockchains, mempool controls transaction flow before consensus, denial of whose service hurts the health and security of blockchain networks. This paper presents MPFUZZ, the first mempool fuzzer to find asymmetric DoS bugs by exploring the space of symbolized mempool states and optimistically estimating the promisingness of an intermediate state in reaching bug oracles. Compared to the baseline blockchain fuzzers, MPFUZZ achieves a > 100x speedup in finding known DETER exploits. Running MPFUZZ on major Ethereum clients leads to discovering new mempool vulnerabilities, which exhibit a wide variety of sophisticated patterns, including stealthy mempool eviction and mempool locking. Rule-based mitigation schemes are proposed against all newly discovered vulnerabilities.
Muhammad Aslam Jarwar, Sajjad Ali, Inayatullah Inayatullah, Sayed Chhattan Shah
As the growth of the Internet of Things (IoT) persists, it becomes imperative to deliberate on strategies for protecting the security and privacy inside the confines of resource constrained devices and their data, while also preserving optimal performance. This research paper offers an innovative solution at the intersection of IoT middleware and Blockchain technology, specifically the Hyperledger fabric. Through the use of a distributed decentralized ledger, we overcome many of the limitations of current IoT networks. This paper outlines a robust layered IoT model that could be applied to any use case, providing security and privacy at the edge of IoT devices. We conducted an implementation setup to test the model and validate the security measures embedded through Blockchain design. Additionally, we improved IoT devices interoperability through the use of semantic ontologies. Overall, this research contributes to the ongoing effort to create a secure and efficient IoT ecosystem.
Fernando Bereta dos Reis, Mark Borkum, Monish Mukherjee, Hayden Reeve · 5 authors
This report explores the potential of distributed ledger technology (DLT) as a transformative tool to enhance fault-tolerant operations in electrical distribution systems. Leveraging DLT's core attributes, including an immutable decentralized ledger, distributed consensus mechanisms, and state replication capabilities, this study focuses on three critical use cases. A central aspect of this research centers on the utilization of a consensus-driven ledger, providing actors within the system, such as distributed resources, with access to a reliable data repository. This empowers these actors to collaborate effectively and make informed decisions, all securely recorded on the blockchain. The first use case concentrates on data configuration, utilizing mathematical criteria---particularly, the chi-squared test for gross error detection---to identify trustworthy sensors for advanced decision-making. Building upon this foundation of trust, the second use case, topology identification, accurately determines circuit breaker states, unveiling the distribution network's topology. Ultimately, the third use case leverages this trust to execute switching actions, reconfiguring feeders and restoring power to disconnected customers after fault events. The concept of trust serves as a cornerstone in this approach, marking a departure from traditional fault location, isolation, and service restoration (FLISR) methods. Additionally, the blockchain-based architecture introduces decentralization, empowering disconnected areas to make autonomous decisions, even when communication with a central control center is disrupted. The primary contributions of this report are twofold: (1) a novel approach for evaluating distribution system voltage areas while preserving data ownership and (2) the implementation of interactions between distribution network areas using the actor model. Unlike the previous sequential approach for evaluating the area connection voltages, which required a radial network topology, this study's area model reduction enables a more versatile approach. The area model reduction addresses issues of prolonged data waiting times and multiple points of failure within the previous approach. Notably, the presented evaluation for the reduced network model area connection reveals a significant increase in the differences in voltage magnitudes. Simulation and evaluation of area agents across four distinct cases elucidate the area-level interaction behavior during a fault event. Simulations demonstrate that the proposed distributed FLISR (DFLISR) approach can successfully restore service to an affected area. Varying message delays and message loss probabilities in each simulation case underscore their impacts on restoration times, ranging from 3 min and 32 s to 6 min and 19 s. In contrast, power is not restored in an area in one of our simulation cases.
The International Conference of Artificial Intelligence, Blockchain, Cloud Computing, and Data Analytics is an annual gathering of experts, researchers, and professionals from around the world who share a passion for advancing the fields of artificial intelligence, blockchain, cloud computing, and data analytics.The conference provides a platform for knowledge exchange, networking, and collaboration in these rapidly evolving domains.Our conference is dedicated to exploring the latest research, trends, and best practices in artificial intelligence, blockchain, cloud computing, and data analytics.We seek to create an atmosphere of learning, sharing, and innovation where experts can come together to exchange ideas and collaborate on new projects.At our conference, attendees can expect to hear from a variety of thought leaders, industry professionals, and academics who are at the forefront of their fields.We offer keynote speeches, panel discussions, and technical sessions covering a wide range of topics, from machine learning and natural language processing to distributed ledgers and decentralized applications.
Huizhong Li, Yujie Chen, Shi Xiang, Xingqiang Bai · 9 authors
Enterprise-grade permissioned blockchain systems provide a promising infrastructure for data sharing and cooperation between different companies. However, performance bottlenecks seriously hinder the adoption of these systems in many industrial applications that process complex business logic and huge transaction volumes. Our research identifies two key factors that limit the system performance: 1) At the block level, the serial dependency of inter-block processing severely limits the system throughput. A new block must wait for the completion of all previous blocks. 2) At the transaction level, the lack of efficient intra-block transactions concurrency makes it difficult to achieve high performance, especially when dealing with multiple CPU-heavy contracts which are commonly used in industrial scenarios.
Scalability is a common issue among the most used permissionless blockchains, and several approaches have been proposed to solve this issue. Tackling scalability while preserving the security and decentralization of the network is a significant challenge. To deliver effective scaling solutions, Ethereum achieved a major protocol improvement, including a change in the consensus mechanism towards Proof of Stake. This improvement aimed a vast reduction of the hardware requirements to run a node, leading to significant sustainability benefits with a lower network energy consumption. This work analyzes the resource usage behavior of different clients running as Ethereum consensus nodes, comparing their performance under different configurations and analyzing their differences. Our results show higher requirements than claimed initially and how different clients react to network perturbations. Furthermore, we discuss the differences between the consensus clients, including their strong points and limitations.
Open access
3 source records
Intracranial Aneurysms: Treatment and Complications
Numerous blockchain simulators have been proposed to allow researchers to simulate mainstream blockchains. However, we have not yet found a testbed that enables researchers to develop and evaluate their new consensus algorithms or new protocols for blockchain sharding systems. To fill this gap, we developed BlockEmulator, which is designed as an experimental platform, particularly for emulating blockchain sharding mechanisms. BlockEmulator adopts a lightweight blockchain architecture so developers can only focus on implementing their new protocols or mechanisms. Using layered modules and useful programming interfaces offered by BlockEmulator, researchers can implement a new protocol with minimum effort. Through experiments, we test various functionalities of BlockEmulator in two steps. Firstly, we prove the correctness of the emulation results yielded by BlockEmulator by comparing the theoretical analysis with the observed experiment results. Secondly, other experimental results demonstrate that BlockEmulator can facilitate measuring a series of metrics, including throughput, transaction confirmation latency, cross-shard transaction ratio, the queuing status of transaction pools, workload distribution across blockchain shards, etc. We have made BlockEmulator open-source in Github.
Conor Flynn, Kristin P. Bennett, John Erickson, Aaron Green · 5 authors
With the agile development process of most academic and corporate entities, designing a robust computational back-end system that can support their ever-changing data needs is a constantly evolving challenge. We propose the implementation of a data and language-agnostic system design that handles different data schemes and sources while subsequently providing researchers and developers a way to connect to it that is supported by a vast majority of programming languages. To validate the efficacy of a system with this proposed architecture, we integrate various data sources throughout the decentralized finance (DeFi) space, specifically from DeFi lending protocols, retrieving tens of millions of data points to perform analytics through this system. We then access and process the retrieved data through several different programming languages (R-Lang, Python, and Java). Finally, we analyze the performance of the proposed architecture in relation to other high-performance systems and explore how this system performs under a high computational load.