Bitcoin’s success as a global cryptocurrency has paved the way for the emergence of blockchain, a revolutionary category of distributed systems. However, the growing popularity of blockchain has led to a significant divergence from its core principles in many systems labeled as “blockchain.” This divergence has introduced complexity into the blockchain ecosystem, exacerbated by a lack of comprehensive reviews on blockchain and its variants. Consequently, gaining a clear and updated understanding of the diverse spectrum of current blockchain and blockchain-like systems has become challenging. This situation underscores the necessity for an extensive literature review and the development of thematic taxonomies. This survey seeks to offer a comprehensive and current assessment of existing blockchains and their variations while delineating the boundaries between blockchain and blockchain-like systems. To achieve this objective, we propose a holistic reference model for conceptualizing and analyzing these systems. Our layer-wise framework envisions all distributed ledger technologies (DLTs) as composed of four principal layers: data, consensus, execution, and application (DCEA). In addition, we introduce a new taxonomy that enhances the classification of blockchain and blockchain-like systems, offering a more useful perspective than existing works. Furthermore, we conduct a state-of-the-art review from a layered perspective, employing 23 evaluative criteria predefined by our framework. We perform a qualitative and quantitative comparative analysis of 44 DLT solutions and 26 consensus mechanisms while discussing differences and boundaries between blockchain and blockchain-like systems. We emphasize the significant challenges and tradeoffs encountered by distributed ledger designers, decision-makers, and project managers during the design or adoption of a DLT solution. Finally, we outline crucial research challenges and directions in the field of DLTs.
In this work, we review existing cryptocurrency wallet solutions with regard to authentication methods and factors from the user's point of view. In particular, we distinguish between authentication factors that are verified against the blockchain and the ones verified locally (or against a centralized party). With this in mind, we define notions for $k-factor$ authentication against the blockchain and $k-factor$ authentication against the authentication factors. Based on these notions, we propose a classification of authentication schemes. We extend our classification to accommodate the threshold signatures and signing transactions by centralized parties (such as exchanges or co-signing services). Finally, we apply our classification to existing wallet solutions, which we compare based on various security and key-management features.
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Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Leader Election (LE) is crucial in distributed systems and blockchain technology, ensuring one participant acts as the leader. Traditional LE methods often depend on distributed random number generation (RNG), facing issues like vulnerability to manipulation, lack of fairness, and the need for complex procedures such as verifiable delay functions (VDFs) and publicly-verifiable secret sharing (PVSS). This Bachelor's thesis presents a novel approach to randomized LE, leveraging a game-theoretic assumption that participants, aiming to be chosen as leaders, will naturally avoid actions that diminish their chances. This perspective simplifies LE by eliminating the need for decentralized RNG. Introducing PureLottery, inspired by single-elimination sports tournaments, this method offers a fair, bias-resistant, and efficient LE solution for blockchain environments. It operates on the principle of two participants competing in each match, rendering collusion efforts useless. PureLottery stands out for its low computational and communication complexity, suitable for smart contract implementation. It provides strong game-theoretic incentives for honesty and is robust against adversaries, ensuring no increase in election chances through dishonesty. The protocol guarantees that each honest player has at least a 1/n chance of winning, irrespective of adversary manipulation among the other n-1 participants. PureLottery can also address related problems like participant ranking, electing multiple leaders, and leader aversion, showcasing its versatility across various applications, including lotteries and blockchain protocols. An open-source implementation is made available for public use.
Reza Javan, Mehrzad Mohammadi, Mohammad Beheshti-Atashgah, Mohammad Reza Aref
In recent years, the healthcare sector's transition to digital platforms has intensified concerns over data security, privacy, and scalability. Blockchain technology offers a decentralized, secure, and immutable solution to these challenges. This paper presents a scalable, multi-layered blockchain architecture for secure Electronic Health Record (EHR) sharing and drug supply chain management. The proposed framework introduces five distinct layers that enhance system performance, security, and patient-centric access control. By implementing parallelism, the system significantly increases transaction throughput and reduces network traffic. Our solution ensures data integrity, privacy, and interoperability, making it compatible with existing healthcare systems. Experimental results, conducted using the Caliper benchmark, demonstrate notable improvements in transaction throughput and reduced communication overhead. Additionally, the framework provides transparency and real-time drug supply chain monitoring, empowering decision-makers with critical insights.
Recent developments in Distributed Ledger Technology (DLT), including Blockchain offer new opportunities in the manufacturing domain, by providing mechanisms to automate trust services (digital identity, trusted interactions, and auditable transactions) and when combined with other advanced digital technologies (e.g. machine learning) can provide a secure backbone for trusted data flows between independent entities. This paper presents an DLT-based architectural pattern and technology solution known as SmartQC that aims to provide an extensible and flexible approach to integrating DLT technology into existing workflows and processes. SmartQC offers an opportunity to make processes more time efficient, reliable, and robust by providing two key features i) data integrity through immutable ledgers and ii) automation of business workflows leveraging smart contracts. The paper will present the system architecture, extensible data model and the application of SmartQC in the context of example smart manufacturing applications.
Popular blockchains today have hundreds of thousands of nodes and need to be able to support sophisticated scaling solutions$\unicode{x2013}$such as sharding, data availability sampling, and layer-2 methods. Designing secure and efficient peer-to-peer (p2p) networking protocols at these scales to support the tight demands of the upper layer crypto-economic primitives is a highly non-trivial endeavor. We identify decentralized, uniform random sampling of nodes as a fundamental capability necessary for building robust p2p networks in emerging blockchain networks. Sampling algorithms used in practice today (primarily for address discovery) rely on either distributed hash tables (e.g., Kademlia) or sharing addresses with neighbors (e.g., GossipSub), and are not secure in a Sybil setting. We present Honeybee, a decentralized algorithm for sampling nodes that uses verifiable random walks and table consistency checks. Honeybee is secure against attacks even in the presence of an overwhelming number of Byzantine nodes (e.g., $\geq50\%$ of the network). We evaluate Honeybee through experiments and show that the quality of sampling achieved by Honeybee is significantly better compared to the state-of-the-art. Our proposed algorithm has implications for network design in both full nodes and light nodes.
Confidential computing alleviates the concerns of distrustful customers by removing the cloud provider from their trusted computing base and resolves their disincentive to migrate their workloads to the cloud. This is facilitated by new hardware extensions, like AMD's SEV Secure Nested Paging (SEV-SNP), which can run a whole virtual machine with confidentiality and integrity protection against a potentially malicious hypervisor owned by an untrusted cloud provider. However, the assurance of such protection to either the service providers deploying sensitive workloads or the end-users passing sensitive data to services requires sending proof to the interested parties. Service providers can retrieve such proof by performing remote attestation while end-users have typically no means to acquire this proof or validate its correctness and therefore have to rely on the trustworthiness of the service providers. In this paper, we present Revelio, an approach that features two main contributions: i) it allows confidential virtual machine (VM)-based workloads to be designed and deployed in a way that disallows any tampering even by the service providers and ii) it empowers users to easily validate their integrity. In particular, we focus on web-facing workloads, protect them leveraging SEV-SNP, and enable end-users to remotely attest them seamlessly each time a new web session is established. To highlight the benefits of Revelio, we discuss how a standalone stateful VM that hosts an open-source collaboration office suite can be secured and present a replicated protocol proxy that enables commodity users to securely access the Internet Computer, a decentralized blockchain infrastructure.
Secure aggregation enables federated learning (FL) to perform collaborative training of clients from local gradient updates without exposing raw data. However, existing secure aggregation schemes inevitably perform an expensive fresh setup per round because each client needs to establish fresh input-independent secrets over different rounds. The latest research, Flamingo (S&P 2023), designed a share-transfer-based reusable secret key to support the server continuously performing multiple rounds of aggregation. Nevertheless, the share transfer mechanism it proposed can only be achieved with P probability, which has limited reliability. To tackle the aforementioned problems, we propose a more reliable and anonymously authenticated scheme called Chu-ko-nu for multi-round secure aggregation. Specifically, in terms of share transfer, Chu-ko-nu breaks the probability P barrier by supplementing a redistribution process of secret key components (the sum of all components is the secret key), thus ensuring the reusability of the secret key. Based on this reusable secret key, Chu-ko-nu can efficiently perform consecutive aggregation in the following rounds. Furthermore, considering the client identity authentication and privacy protection issue most approaches ignore, Chu-ko-nu introduces a zero-knowledge proof-based authentication mechanism. It can support clients anonymously participating in FL training and enables the server to authenticate clients effectively in the presence of various attacks. Rigorous security proofs and extensive experiments demonstrated that Chu-ko-nu can provide reliable and anonymously authenticated aggregation for FL with low aggregation costs, at least a 21.02% reduction compared to the state-of-the-art schemes.
Blockchain, like any other complex technology, needs a strong testing methodology to support its evolution in both research and development contexts. Setting up meaningful tests for permissionless blockchain technology is a notoriously complex task for several reasons: software is complex, large number of nodes are involved, network is non ideal, etc. Developers usually adopt small virtual laboratories or costly real devnets, based on real software. Researchers usually prefer simulations of a large number of nodes, based on simplified models. In this paper, we aim to obtain the advantages of both approaches, i.e., performing large, realistic, inexpensive, and flexible experiments, using real blockchain software within a virtual environment. To do that, we tackle the challenge of running large blockchain networks in a single physical machine, leveraging Linux and Docker. We analyze a number of problems that arise when large blockchain networks are emulated and we provide technical solutions for all of them. Finally, we describe two experiences of emulating fairly large blockchain networks on a single machine, adopting both research oriented and production oriented software, and involving up to more than 3000 containers.
Francesco Salzano, Lodovica Marchesi, Remo Pareschi, Roberto Tonelli
Context: Blockchain-based Information Ecosystems (BBIEs) are a type of information ecosystem in which blockchain technology is used to provide a trust mechanism among parties and to manage shared business logic, breaking the traditional scheme of Information Ecosystems dominated by a leading company and leveraging the decentralization of data management, information flow, and business logic. Objective: In this paper, we propose architecture and technical aspects concerning the creation of a BBIE, underlining the advantages supplied and the logic decomposition among the business and storage components. Method: The requirements are derived from the current needs of the collaborative business and the data collected by surveying practitioners. To get these needs we followed the Grounded Theory research approach. We validate our architectural schema against a case study dealing with the management of a wine supply chain, also involving different companies and supervision authorities. Results: The proposed solution integrates blockchain-based applications with the existing information system as a module of the ecosystem, leveraging on the low costs, scalability, and high-level security because of the restricted access to the network. Conclusion: We must go a long way in deepening and refining the possibilities offered by technology in supporting innovative multi-organizational business models. BBIEs can contribute substantially to paving the way in such a direction.
This article discusses the implementation of programmable money on DLT-based CBDCs. After briefly introducing what programmable money is, we enumerate some initiatives worldwide and discuss the critical steps for implementation. We look at the challenges from the Computer Science perspective. Four aspects were analyzed: architectural design, security, scalability, and energy consumption.
Tao Yan, Shengnan Li, Benjamin Kraner, Luyao Zhang · 5 authors
Ethereum 2.0, as the preeminent smart contract blockchain platform, guarantees the precise execution of applications without third-party intervention. At its core, this system leverages the Proof-of-Stake (PoS) consensus mechanism, which utilizes a stochastic process to select validators for block proposal and validation, consequently rewarding them for their contributions. However, the implementation of blockchain technology often diverges from its central tenet of decentralized consensus, presenting significant analytical challenges. Our study collects consensus reward data from the Ethereum Beacon chain and conducts a comprehensive analysis of reward distribution and evolution, categorizing them into attestation, proposer and sync committee rewards. To evaluate the degree of decentralization in PoS Ethereum, we apply several inequality indices, including the Shannon entropy, the Gini Index, the Nakamoto Coefficient, and the Herfindahl-Hirschman Index (HHI). Our comprehensive dataset is publicly available on Harvard Dataverse, and our analytical methodologies are accessible via GitHub, promoting open-access research. Additionally, we provide insights on utilizing our data for future investigations focused on assessing, augmenting, and refining the decentralization, security, and efficiency of blockchain systems.
We analyze how secure a block is after the block becomes $k$-deep, i.e., security-latency, for Nakamoto consensus under an exponential network delay model. We provide the fault tolerance and extensive bounds on safety violation probabilities given mining rate, delay rate and confirmation rules. Next, modeling the blockchain system as a batch service queue with exponential network delay, we connect the security-latency analysis to sustainable transaction rate of the queue system. As our model assumes exponential network delay, batch service queue models give a meaningful trade-off between transaction capacity, security and latency. Our results indicate that, by simply picking $k=7$-block confirmation rule in Bitcoin instead of the convention of $k=6$, mining rate, latency and throughput can be increased sixfold with the same safety guarantees. We further consider adversarial attacks on the queue service to hamper the service process. In an extreme scenario, we consider the selfish-mining attack for this purpose and provide the maximum adversarial block ratio in the longest chain under the exponential delay model. The ratio in turn reflects the maximum rate of decrease in the sustainable transaction rate of the queue.
The emerging Web 3.0 paradigm aims to decentralize existing web services, enabling desirable properties such as transparency, incentives, and privacy preservation. However, current Web 3.0 applications supported by blockchain infrastructure still cannot support complex data analytics tasks in a scalable and privacy-preserving way. This paper introduces the emerging federated analytics (FA) paradigm into the realm of Web 3.0 services, enabling data to stay local while still contributing to complex web analytics tasks in a privacy-preserving way. We propose FedWeb, a tailored FA design for important frequent pattern mining tasks in Web 3.0. FedWeb remarkably reduces the number of required participating data owners to support privacy-preserving Web 3.0 data analytics based on a novel distributed differential privacy technique. The correctness of mining results is guaranteed by a theoretically rigid candidate filtering scheme based on Hoeffding's inequality and Chebychev's inequality. Two response budget saving solutions are proposed to further reduce participating data owners. Experiments on three representative Web 3.0 scenarios show that FedWeb can improve data utility by ~25.3% and reduce the participating data owners by ~98.4%.
Mikel Cortes-Goicoechea, Csaba Király, Dmitriy Ryajov, José L. Muñoz · 5 authors
Scalability in blockchain remains a significant challenge, especially when prioritizing decentralization and security. The Ethereum community has proposed comprehensive data-sharding techniques to overcome storage, computational, and network processing limitations. In this context, the propagation and availability of large blocks become the subject of research to achieve scalable data-sharding. This paper provides insights after exploring the usage of a Kademlia-based Distributed Hash Table (DHT) to enable Data Availability Sampling (DAS) in Ethereum. It presents a DAS-DHT simulator to study this problem and validates the results of the simulator with experiments in a real DHT network, InterPlanetary File System (IPFS). Our results help us understand what parts of DAS can be achieved based on existing Kademlia DHT solutions and which ones cannot. We discuss the limitations of DHT solutions and discuss other alternatives.
Conflict-free Replicated Data Types (CRDTs) are designed for replica convergence without global coordination or consensus. Recent work has achieved the same in a Byzantine environment, through DAG-like structures based on cryptographic hashes of content. The blocklace is a partially-ordered generalization of the blockchain in which each block has any finite number of signed hash pointers to preceding blocks. We show that the blocklace datatype, with the sole operation of adding a single block, is a CRDT: it is both a pure operation-based CRDT, with self-tagging; and a delta-state CRDT, under a slight generalization of the delta framework. Allowing arbitrary values as payload, the blocklace can also be seen as a universal Byzantine fault-tolerant implementation for arbitrary CRDTs, under the operation-based approach. Current approaches only care about CRDT convergence, being equivocation-tolerant (they do not detect or prevent equivocations), allowing a Byzantine node to cause an arbitrary amount of harm by polluting the CRDT state with an unbounded number of equivocations. We show that the blocklace can be used not only in an equivocation-tolerant way, but also so as to detect and eventually exclude Byzantine nodes, including equivocators, even under the presence of undetectable colluders. The blocklace CRDT protocol ensures that a Byzantine node may harm only a finite prefix of the computation.
Executing smart contracts is a compute and storage-intensive task, which currently dominates modern blockchain's performance. Given that computers are becoming increasingly multicore, concurrency is an attractive approach to improve programs' execution runtime. A unique challenge of blockchains is that all replicas (miners or validators) must execute all smart contracts in the same logical order to maintain the semantics of State Machine Replication (SMR). In this work, we study the maximal level of parallelism attainable when focusing on the conflict graph between transactions packaged in the same block. This exposes a performance vulnerability that block creators may exploit against existing blockchain concurrency solutions, which rely on a total ordering phase for maintaining consistency amongst all replicas. To facilitate the formal aspects of our study, we develop a novel generic framework for Active State Machine Replication (ASMR) that is strictly serializable. We introduce the concept of graph scheduling and the definition of the minimal latency scheduling problem, which we prove to be NP-hard. We show that the restricted version of this problem for homogeneous transactions is equivalent to the classic Graph Vertex Coloring Problem, yet show that the heterogeneous case is more complex. We discuss the practical implications of these results.
Set reconciliation, where two parties hold fixed-length bit strings and run a protocol to learn the strings they are missing from each other, is a fundamental task in many distributed systems. We present Rateless Invertible Bloom Lookup Tables (Rateless IBLTs), the first set reconciliation protocol, to the best of our knowledge, that achieves low computation cost and near-optimal communication cost across a wide range of scenarios: set differences of one to millions, bit strings of a few bytes to megabytes, and workloads injected by potential adversaries. Rateless IBLT is based on a novel encoder that incrementally encodes the set difference into an infinite stream of coded symbols, resembling rateless error-correcting codes. We compare Rateless IBLT with state-of-the-art set reconciliation schemes and demonstrate significant improvements. Rateless IBLT achieves 3--4× lower communication cost than non-rateless schemes with similar computation cost, and 2--2000× lower computation cost than schemes with similar communication cost. We show the real-world benefits of Rateless IBLT by applying it to synchronize the state of the Ethereum blockchain, and demonstrate 5.6× lower end-to-end completion time and 4.4× lower communication cost compared to the system used in production.
In recent years, the Decentralized Finance (DeFi) market has witnessed numerous attacks on the price oracle, leading to substantial economic losses. Despite the advent of truth discovery methods opening up new avenues for oracle development, it falls short in addressing high-value attacks on price oracle tasks. Consequently, this paper introduces a dynamically adjusted truth discovery method safeguarding the truth of high-value price oracle tasks. In the truth aggregation stage, we enhance future considerations to improve the precision of aggregated truth. During the credibility update phase, credibility is dynamically assessed based on the task's value and the Cumulative Potential Economic Contribution (CPEC) of information sources. Experimental results demonstrate a significant reduction in data deviation by 65.8\% and potential economic loss by 66.5\%, compared to the baseline scheme, in the presence of high-value attacks.
Bitcoin inscription marks a pivotal moment in blockchain technology. This report presents a primary exploration of Bitcoin inscriptions. We dive into the technological underpinnings and offer a detailed comparative analysis between Bitcoin inscriptions and NFTs on other blockchains. Further, we explore a wide range of use cases and significant opportunities for future innovation, including inscription derivative protocols, Bitcoin Layer2 solutions, and interoperability techniques.
In this study, we present a secure smart contract-based Verifiable Random Function (VRF) model, addressing the shortcomings of existing systems. As quantum computing emerges, conventional public key cryptography faces potential vulnerabilities. To enhance our VRF's robustness, we employ post-quantum Ring-LWE encryption for generating pseudo-random sequences. Given the computational intensity of this approach and associated on-chain gas costs, we propose a hybrid architecture of VRF system where on-chain and off-chain can communicate in a scalable and secure way. To ensure the validity and integrity of the off-chain computations (e.g., Ring-LWE encryption), we employ a quantum-secure linkable ring signature scheme on NTRU lattice and also delegated key generation (DKG) with a secure key encapsulation mechanism (KEM). Our decentralized VRF employs multi-party computation (MPC) with blockchain-based decentralized identifiers (DID), ensuring the collective efforts of enhanced randomness and security. We show the security and privacy advantages of our proposed VRF model with the approximated estimation of overall temporal and spatial complexities. We also evaluate our VRF MPC model's entropy and outline its Solidity smart contract integration. This research also provides a method to produce and verify the VRF output's proof, optimal for scenarios necessitating randomness and validation. Lastly, using NIST SP800-22 test suite for randomness, we demonstrate the commendable result with a 97.73% overall pass rate on 11 standard tests and 0.5459 of average p-value for the total 176 tests.
Quentin Kniep, Lefteris Kokoris-Kogias, Alberto Sonnino, Igor Zablotchi · 5 authors
Scalability is a crucial requirement for modern large-scale systems, enabling elasticity and ensuring responsiveness under varying load. While cloud systems have achieved scalable architectures, blockchain systems remain constrained by the need to over-provision validator machines to handle peak load. This leads to resource inefficiency, poor cost scaling, and limits on performance. To address these challenges, we introduce Pilotfish, the first scale-out transaction execution engine for blockchains. Pilotfish enables validators to scale horizontally by distributing transaction execution across multiple worker machines, allowing elasticity without compromising consistency or determinism. It integrates seamlessly with the lazy blockchain architecture, completing the missing piece of execution elasticity. To achieve this, Pilotfish tackles several key challenges: ensuring scalable and strongly consistent distributed transactions, handling partial crash recovery with lightweight replication, and maintaining concurrency with a novel versioned-queue scheduling algorithm. Our evaluation shows that Pilotfish scales linearly up to at least eight workers per validator for compute-bound workloads, while maintaining low latency. By solving scalable execution, Pilotfish brings blockchains closer to achieving end-to-end elasticity, unlocking new possibilities for efficient and adaptable blockchain systems.
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.
Iván Abellán Álvarez, Vincent Gramlich, Johannes Sedlmeir
With the increasing adoption of decentralized information systems based on a variety of permissionless blockchain networks, the choice of consensus mechanism is at the core of many controversial discussions. Ethereum's recent transition from proof-of-work (PoW) to proof-of-stake (PoS)-based consensus has further fueled the debate on which mechanism is more favorable. While the aspects of energy consumption and degree of (de-)centralization are often emphasized in the public discourse, seminal research has also shed light on the formal security aspects of both approaches individually. However, related work has not yet comprehensively structured the knowledge about the security properties of PoW and PoS. Rather, it has focused on in-depth analyses of specific protocols or high-level comparative reviews covering a broad range of consensus mechanisms. To fill this gap and unravel the commonalities and discrepancies between the formal security properties of PoW- and PoS-based consensus, we conduct a systematic literature review over 26 research articles. Our findings indicate that PoW-based consensus with the longest chain rule provides the strongest formal security guarantees. Nonetheless, PoS can achieve similar guarantees when addressing its more pronounced tradeoff between safety and liveness through hybrid approaches.