The process of reaching an agreement on a value within a distributed network, known as a consensus problem, is a defining feature of blockchain. This consensus problem can be seen in various applications like load balancing, transaction validation in blockchain, and distributed computing. In recent years, many researchers have provided solutions to this problem. Hence we have presented a survey in which we delved into blockchain consensus algorithms and conducted a comparative analysis of all the consensus algorithms to provide information about each protocol’s advantages and drawbacks. This survey starts with the standard proof-of-work consensus protocol applied in bitcoin cryptocurrency and its limitations on the ground of the following parameters: throughput (transactions per second), latency, forks, fault tolerance, double spending attacks, and power consumption. The rest of the consensus algorithms in this paper have been systematically covered to address the limitations of proof-of-work. This paper also covered Raft and PBFT consensus algorithms suitable for permissioned networks. Although the PBFT consensus protocol has a high throughput and a low latency, it has limited node scalability. The PBFT has a low byzantine fault tolerant rate. This paper also covers PoEWAL for blockchain-based IoT applications and WBFT, which prevents corrupt nodes from taking part in consensus. A comparative analysis of the consensus algorithms provides an explicit knowledge of the present research, which also offers guidance for future study.
We present a simple approach to mitigate transaction-ordering dependent Maximum-Extractable-Value (MEV) opportunities in Ethereum. The approach is built on top of Proposer-Builder-Separation, restricts the freedom to order transactions within a block arbitrarily, and relies primarily on a non-malleable signature scheme and separation of responsibilities. In addition, we generalize the proposed approach to show that the property of unpredictable transaction arrangement can be transferred also to other blockchain systems. We discuss the gain in MEV mitigation, important limitations, and open issues.
The use of information technology to trade information, deliver services, and other things is becoming more and more commonplace in the era of technological advancement. Tendering is one such area where the public and private sectors collaborate. E-tendering is a procurement technique that uses the internet and digital technologies to automate and simplify the whole bidding or tendering process. This makes it easier for the bidders to browse through all of the open tenders and select one to proceed with. But it frequently results in a number of challenges that both bids and bidders must deal with. The system is inefficient because of scale and transparency problems brought on by its centralized architecture. Additionally, the system frequently shares information about tenders with other outside organizations, which compromises the confidentiality and integrity of the tenders. To manage these issues, a decentralized method is used in the deployment of the Blockchain e-tendering system. Consequently, the procurement procedures will have the opportunity to leverage the potential of blockchain technology to enhance security and transparency. This research aims to provide an electronic tendering system that is transparent, liquidate, and safe. It will manage tender allocation and use smart contracts to automate the underlying processes with the least amount of human interaction possible.
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Payment channels (PC) greatly improve blockchain scalability by allowing an unlimited number of off-chain transactions instead of committing every transaction to the blockchain. However, the payment channel structure is limited to only two nodes, which is inadequate in scenarios where one node frequently receives money from multiple nodes, such as Cafe. Recent proposals have extended the 2-node structure to a multi-node structure. Unfortunately, these approaches either require all participants to always be online, which is not realistic, or underestimate the efficiency problem of withdrawing funds, leading to higher fees and storage costs. What’s worse, the payment scope in these proposals is limited to their respective structures and is not mutually compatible. In this paper, we propose MPC+, a smart contract that enables multiple nodes to engage in off-chain transactions. MPC+ is designed to cater to scenarios where one node frequently receives money from multiple nodes, such as Cafe, shops, and more. The nodes in MPC+ can conduct off-chain transactions internally or with nodes in existing payment channel networks externally, and they only need to be online during off-chain transactions. Furthermore, MPC+ enhances the withdrawal logic through a binding strategy, effectively reducing the number of on-chain transactions required for fund withdrawals from O(n) to O(1), and it works over any blockchain system that supports Turing-complete smart contracts. The security is formally proven under the Universal Composability framework, and it is specifically implemented on the Ethereum platform. The experimental results clearly demonstrate that MPC+ surpasses other designs in terms of fees and storage costs.
Xianghe Ye, Qingxu Di, Xinyuan Du, Ayong Bao · 5 authors
In this paper, we present an innovative solution to overcome the limitations of blockchain systems, particularly in terms of communication costs and storage resources. Our ap-proach leverages blockchain sharding, a technique that partitions a blockchain into multiple parallel shards. We underscore the im-portance of selecting a sharding algorithm that accounts for the temporal dimension, often overlooked in prior studies. This algorithm is designed to minimize inter-shard communication and en-sure a well-balanced distribution of nodes. Additionally, we intro-duce a novel methodology that integrates the gated recurrent unit (GRU) and graph neural network (GNN) for the sharding algorithm, incorporating time-related information. This involves a graph extractor for extracting temporal graph data from block-chain data and a Dual-GRU-GNN model for learning from these temporal graphs to enhance prediction results. Our proposed so-lution is specifically crafted to handle dynamic Ethereum-like blockchain networks that evolve over time, aiming to yield supe-rior results in the realm of blockchain sharding. Compared to clas-sical neural network models such as Graph Neural Network (GCN), Graph Sage, and Graph Attention Network (GAT), our proposed model exhibits superior overall performance. It achieves a more evenly distributed number of nodes within each shard and establishes stronger correlations among nodes within the same shard, minimizing the need for cross-shard communication.
Blockchain performance has historically faced challenges posed by the throughput limitations of consensus algorithms. Recent breakthroughs in research have successfully alleviated these constraints by introducing a modular architecture that decouples consensus from execution. The move toward independent optimization of the consensus layer has shifted attention to the execution layer. While concurrent transaction execution is a promising solution for increasing throughput, practical challenges persist. Its effectiveness varies based on the workloads, and the associated increased hardware requirements raise concerns about undesirable centralization. This increased requirement results in full nodes and stragglers synchronizing from signed checkpoints, decreasing the trustless nature of blockchain systems. In response to these challenges, this paper introduces Chiron, a system designed to extract execution hints for the acceleration of straggling and full nodes. Notably, Chiron achieves this without compromising the security of the system or introducing overhead on the critical path of consensus. Evaluation results demonstrate a notable speedup of up to 30%, effectively addressing the gap between theoretical research and practical deployment. The quantification of this speedup is achieved through realistic blockchain benchmarks derived from a comprehensive analysis of Ethereum and Solana workloads, constituting an independent contribution.
The Double Secure Hash Algorithm (DSHA) is utilized in the cryptographic Proof-of-Work (PoW) consensus mechanism of blockchain networks, including many cryptocurrencies and the Bitcoin (BTC) network. The widespread usage of BTC has raised concerns about its environmental impact, as its annual energy consumption and emissions are estimated to be 125.21 TWh and 63.38 million metric tonnes of carbon dioxide equivalent, respectively. As PoW-based blockchain networks expand, fast and energy efficient Application Specific Integrated Circuits (ASICs) that integrate security hash primitives become vital to their sustainability. Low power ASIC design flows targeting the minimization of a circuit’s power consumption may negatively affect its speed, and its overall energy efficiency. In this brief, we propose a novel Multi-threshold Voltage (Multi-Vt) based energy efficiency optimization flow for DSHA designs that reduces their static power consumption without impacting their performed hash rate. When applied to DSHA designs synthesized with a 32 nm CMOS Technology, it reduces their static power consumption by up to 71.1%, and improves their energy efficiency by up to 49.1%. The proposed optimization flow offers prospects of sustainability, if broadly adopted by commercial mining equipment vendors, as it has the potential to almost halve the global energy consumed for BTC mining.
Low-power high-performance VLSI design
Physical Unclonable Functions (PUFs) and Hardware Security
Integrating sharded blockchain with IoT presents a solution for trust issues and optimized data flow. Sharding boosts blockchain scalability by dividing its nodes into parallel shards, yet it's vulnerable to the $1\%$ attacks where dishonest nodes target a shard to corrupt the entire blockchain. Balancing security with scalability is pivotal for such systems. Deep Reinforcement Learning (DRL) adeptly handles dynamic, complex systems and multi-dimensional optimization. This paper introduces a Trust-based and DRL-driven (\textsc{TbDd}) framework, crafted to counter shard collusion risks and dynamically adjust node allocation, enhancing throughput while maintaining network security. With a comprehensive trust evaluation mechanism, \textsc{TbDd} discerns node types and performs targeted resharding against potential threats. The model maximizes tolerance for dishonest nodes, optimizes node movement frequency, ensures even node distribution in shards, and balances sharding risks. Rigorous evaluations prove \textsc{TbDd}'s superiority over conventional random-, community-, and trust-based sharding methods in shard risk equilibrium and reducing cross-shard transactions.
Jalel Ktari, Tarek Frikha, Monia Hamdi, Habib Hamam
Because of its versatility across various applications, Blockchain has emerged as a technology garnering significant interest. It has effectively addressed the challenge of transitioning from a low-trust, centralized ledger maintained by a single third-party to a high-trust, decentralized structure maintained by multiple entities, often referred to as validating nodes. Consequently, numerous blockchain systems have arisen for a multitude of purposes. Nevertheless, a considerable number of these blockchain systems are plagued by significant deficiencies concerning their performance and security. These issues have to be rectified before the realization of a widespread adoption. An essential element within any blockchain system is its foundational consensus algorithm, a crucial determinant of both its performance and security attributes. Consequently, to tackle the shortcomings observed in various blockchain systems, the hardware implementation of a series of established and innovative consensus algorithms was carried out as part of this work. This paper aims to compare and analyze the different consensus methods in blockchain, namely PoS (Proof of Stake), PoW (Proof of Work) and PoA (Proof of Authority) using VHDL (Very High-Speed Integrated Circuit Hardware Description Language). Each of these methods has unique characteristics that influence the validation of transactions and the addition of blocks to the blockchain. In this context, we aim to demonstrate the importance of optimizing consensus execution time via IPs (Intellectual Property) in VHDL. We also evaluate their impact on security, scalability and performance for IoT applications.
Soosan Naderi Mighan, Jelena Mišić, Vojislav B. Mišić, Xiaolin Chang
In this paper, we analyze the performance of Ethereum data distribution network using a probabilistic model which allows accurate modeling of data propagation. We then apply the model to analyze the performance of data propagation in Ethereum when using geth protocol under block withholding attack, Eclipse attack, and block slowdown attack. We also propose countermeasures for the block withholding attack and Eclipse attack.
Maximum Extractable Value (MEV) refers to the maximum benefit obtained from the Decentralized Finance (DeFi) protocol during the block production process by utilizing the power of transaction ordering in the block. Although MEV plays a role in incentivizing the efficiency of DeFi projects, excessive abuse of this power can pose a series of problems and challenges to the blockchain, including an increased risk of chain forks. The State Sharding technique can fundamentally enhance the scalability of blockchain, but its consensus security also faces the potential threat of MEV. To mitigate the negative impact of MEV on state sharding, a scheme combining the Proposer-Builder Separation (PBS) and the State Merge is proposed. This scheme allows high-performance nodes to synchronize the state of adjacent shards and form a higher-level virtual shard, establishing a logical relationship resembling a complete binary tree among the shards. And through role separation, nodes participate in consensus within a leaf shard and composite virtual shards. At the same time, they can participate in block construction and seize MEV opportunities in other shards that are already synchronized. By confining transaction ordering authority outside the consensus shards, the security risk to the State Sharding consensus network from the MEV is reduced. However completely eliminating the MEV threats is very difficult and requires further research. Analytical and simulation-based validation shows that the proposed approach can mitigate the issue of decreased resistance to censorship and incentivize nodes to fully utilize their performance by leveraging MEV opportunities, thereby improving the blockchain's throughput capacity.
Non-fungible tokens (NFTs) could potentially have a broader transformational effect than mere blockchain because they challenge the traditional notions of ownership and is, therefore, a more fundamental challenge to our established economic and social structures. This paper provides a systematic review of the NFT literature outlining the research opportunities for NFTs.
In this paper, we present the first bare metal comparison of modern blockchains, including Algorand, Avalanche, Diem, Ethereum, Quorum and Solana. This evaluation was conducted with the recent Diablo benchmark suite, a framework to evaluate the performance of different blockchains on the same ground. By tuning network delays in our controlled environment we were able to reproduce performance trends obtained in geo-distributed settings, hence demonstrating the relevance of bare metal evaluations to better understand blockchain performance.
There is a growing interest in deploying blockchain, a distributed and decentralized immutable ledger, on alternate form of hardware to improve the performance, security, energy usage and hardware cost of blockchain. However, so far, the success in utilizing alternate form of hardware has not gained popularity due to the limited benefits of using proposed alternate hardware. For example, running blockchain on a dedicated hardware setup that is separate from the primary infrastructure, such as Raspberry Pi, has limited the energy, hardware and efficiency as you need to manage an entirely separate and dedicated hardware with additional setup, wiring and more. A recent advancement in networking brought a new type of network interface card (NIC) called SmartNIC that allows users to run more advanced and customized programs on a NIC. The main set of benefits of SmartNICs include increased programmability, increased security and increased hardware cost and energy efficiency, as it provides additional computing power to a device that already must be present in a server, and freeing the CPUs to perform other important tasks. Given such benefit, this paper focuses on running customized blockchain application, based on Proof of Work mechanism, on the SmartNIC that utilizes all its available resources, which helps in removing the dependency on expensive, dedicated and specialized hardware and at the same time reduce the hardware needs for running blockchain application. The results are promising as the processing time of Proof of Work based blockchain application on a SmartNIC showed up to 72% improvement when the host is experiencing high load, all the while eliminating the need to add miscellaneous hardware dedicated for blockchain.
In order to fully unlock the transformative power of distributed ledgers and blockchains, it is crucial to develop innovative consensus algorithms that can overcome the obstacles of security, scalability, and interoperability, which currently hinder their widespread adoption. This paper introduces HybridChain that combines the advantages of sharded blockchain and DAG distributed ledger, and a consensus algorithm that leverages decentralized learning. Our approach involves validators exchanging perceptions as votes to assess potential conflicts between transactions and the witness set, representing input transactions in the UTXO model. These perceptions collectively contribute to an intermediate belief regarding the validity of transactions. By integrating their beliefs with those of other validators, localized decisions are made to determine validity. Ultimately, a final consensus is achieved through a majority vote, ensuring precise and efficient validation of transactions. Our proposed approach is compared to the existing DAG-based scheme IOTA and the sharded blockchain Omniledger through extensive simulations. The results show that IOTA has high throughput and low latency but sacrifices accuracy and is vulnerable to orphanage attacks especially with low transaction rates. Omniledger achieves stable accuracy by increasing shards but has increased latency. In contrast, the proposed HybridChain exhibits fast, accurate, and secure transaction processing, and excellent scalability.
Estimates of energy usage in layers of computing from devices to algorithms have been determined and analyzed. Building on the previous analysis [3], energy needed from single devices and systems including three large-scale computing applications such as Artificial Intelligence (AI)/Machine Learning for Natural Language Processing, Scientific Simulations, and Cryptocurrency Mining have been estimated. In contrast to the bit-level switching, in which transistors achieved energy efficiency due to geometrical scaling, higher energy is expended both at the at the instructions and simulations levels of an application. Additionally, the analysis based on AI/ML Accelerators indicate that changes in architectures using an older semiconductor technology node have comparable energy efficiency with a different architecture using a newer technology. Further comparisons of the energy in computing systems with the thermodynamic and biological limits, indicate that there is a 27–36 orders of magnitude higher energy requirements for total simulation of an application. These energy estimates underscore the need for serious considerations of energy efficiency in computing by including energy as a design parameter, enabling growing needs of compute-intensive applications in a digital world.
Motivated by proof-of-stake (PoS) blockchains such as Ethereum, two key desiderata have recently been studied for Byzantine-fault tolerant (BFT) state-machine replication (SMR) consensus protocols: Finality means that the protocol retains consistency, as long as less than a certain fraction of validators are malicious, even in partially-synchronous environments that allow for temporary violations of assumed network delay bounds. Accountable safety means that in any case of inconsistency, a certain fraction of validators can be identified to have provably violated the protocol. Earlier works have developed impossibility results and protocol constructions for these properties separately. We show that accountable safety implies finality, thereby unifying earlier results.
Patikiri Arachchige Don Shehan Nilmantha Wijesekara, Subodha Gunawardena
Knowledge-Defined Networking (KDN) necessarily consists of a knowledge plane for the generation of knowledge, typically using machine learning techniques, and the dissemination of knowledge, in order to make knowledge-driven intelligent network decisions. In one way, KDN can be recognized as knowledge-driven Software-Defined Networking (SDN), having additional management and knowledge planes. On the other hand, KDN encapsulates all knowledge-/intelligence-/ cognition-/machine learning-driven networks, emphasizing knowledge generation (KG) and dissemination for making intelligent network decisions, unlike SDN, which emphasizes logical decoupling of the control plane. Blockchain is a technology created for secure and trustworthy decentralized transaction storage and management using a sequence of immutable and linked transactions. The decision-making trustworthiness of a KDN system is reliant on the trustworthiness of the data, knowledge, and AI model sharing. To this point, a KDN may make use of the capabilities of the blockchain system for trustworthy data, knowledge, and machine learning model sharing, as blockchain transactions prevent repudiation and are immutable, pseudo-anonymous, optionally encrypted, reliable, access-controlled, and untampered, to protect the sensitivity, integrity, and legitimacy of sharing entities. Furthermore, blockchain has been integrated with knowledge-based networks for traffic optimization, resource sharing, network administration, access control, protecting privacy, traffic filtering, anomaly or intrusion detection, network virtualization, massive data analysis, edge and cloud computing, and data center networking. Despite the fact that many academics have employed the concept of blockchain in cognitive networks to achieve various objectives, we can also identify challenges such as high energy consumption, scalability issues, difficulty processing big data, etc. that act as barriers for integrating the two concepts together. Academicians have not yet reviewed blockchain-based network solutions in diverse application categories for diverse knowledge-defined networks in general, which consider knowledge generation and dissemination using various techniques such as machine learning, fuzzy logic, and meta-heuristics. Therefore, this article fills a void in the content of the literature by first reviewing the diverse existing blockchain-based applications in diverse knowledge-based networks, analyzing and comparing the existing works, describing the advantages and difficulties of using blockchain systems in KDN, and, finally, providing propositions based on identified challenges and then presenting prospects for the future.
Abstract SDN revolutionises network management by providing a centralised controller that enables flexible and effortless configuration of networks. However, this flexibility also leads to a vulnerability that enables the adversary to trick the security system into allowing the installation of unauthorised flow rules in the switches. Blockchain provides us with a way to protect against malicious tampering with flow rules by storing them in the distributed ledger. In this work, we propose FTISCON, a mechanism to preserve the integrity of the OpenFlow flow table that utilizes blockchain technology. We employ the Ethereum Private Blockchain to implement the proof-of-concept and conduct a comparative analysis of the proposed scheme and existing related schemes, evaluating their performance in terms of delay, computation time, transaction cost, and detection rate. The proposed work is found to perform better in each of these. The study results suggest that the proposed approach offers a practical and efficient remedy to prevent flow modification attacks within SDN networks.