Researchers have discovered a series of theoretical attacks against Bitcoin's Nakamoto consensus; the most damaging ones are selfish mining, double-spending, and consistency delay attacks. These attacks have one common cause: block withholding. This paper proposes Crystal, which leverages quorum certificates to resist block withholding misbehavior. Crystal continuously elects committees from miners and requires each block to have a quorum certificate, i.e., a set of signatures issued by members of its committee. Consequently, an attacker has to publish its blocks to obtain quorum certificates, rendering block withholding impossible. To build Crystal, we design a novel two-round committee election in a Sybil-resistant, unpredictable and non-interactive way, and a reward mechanism to incentivize miners to follow the protocol. Our analysis and evaluations show that Crystal can significantly mitigate selfish mining and double-spending attacks. For example, in Bitcoin, an attacker with 30% of the total computation power will succeed in double-spending attacks with a probability of 15.6% to break the 6-confirmation rule; however, in Crystal, the success probability for the same attacker falls to 0.62%. We provide formal end-to-end safety proofs for Crystal, ensuring no unknown attacks will be introduced. To the best of our knowledge, Crystal is the first protocol that prevents selfish mining and double-spending attacks while providing safety proof.
The development of underlying technologies in blockchain mostly revolves around a difficult problem: how to enhance the performance of the system and reduce various costs of nodes (such as communication, storage and verification) without compromising the system's security and decentralization. Various layer-1 and layer-2 protocols have provided excellent solutions for this challenge. However, they cannot yet be considered as a ``silver bullet". This paper proposes EZchain -- a novel decentralized ``scale-out" ledger system designed for web3.0, aiming to enable blockchain technology to truly support ledger applications in large-scale fully decentralized networks. Without compromising security and decentralization, EZchain successfully accomplishes the following milestones: 1) Scalability: The theoretical throughput of EZchain can be infinitely expanded, nearly unaffected by bandwidth and other resource constraints. 2) Consumer-Grade Hardware Compatibility: EZchain is designed to be compatible with consumer-grade hardware, supporting storage, computation, and verification requirements. 3) Efficient Transaction Confirmation: EZchain strives to maintain transaction confirmation delays within one minute. Our prototype experiment demonstrates that under typical daily bandwidth network conditions, EZchain's performance in all aspects approaches that of the accounts in centralized payment systems. This provides a solid infrastructure for realizing mobile payments in web3.0.
Kartick Kolachala, Mohammed Ababneh, Roopa Vishwanathan
The Bitcoin scalability problem has led to the development of off-chain financial mechanisms such as payment channel networks (PCNs) which help users process transactions of varying amounts, including micro-payment transactions, without writing each transaction to the blockchain. Since PCNs only allow path-based transactions, effective, secure routing protocols that find a path between a sender and receiver are fundamental to PCN operations. In this paper, we propose RACED, a routing protocol that leverages the idea of Distributed Hash Tables (DHTs) to route transactions in PCNs in a fast and secure way. Our experiments on real-world transaction datasets show that RACED gives an average transaction success ratio of 98.74%, an average pathfinding time of 31.242 seconds, which is $1.65*10^3$, $1.8*10^3$, and $4*10^2$ times faster than three other recent routing protocols that offer comparable security/privacy properties. We rigorously analyze and prove the security of RACED in the Universal Composability framework.
Merkle trees have become a widely successful cryptographic data structure. Enabling a vast variety of applications from checking for inconsistencies in databases like Dynamo to essential tools like Git to large scale distributed systems like Bitcoin and other blockchains. There have also been various versions of Merkle trees like Jellyfish Merkle Trees and Sparse Merkle Trees designed for different applications. However, one key drawback of all these Merkle trees is that with a large data set the cost of computing the tree increases significantly, moreover insert operations on a single leaf require re-building the entire tree. For certain use cases building the tree this way is acceptable, however in environments where compute time needs to be as low as possible and where data is processed in parallel, we are presented with a need for asynchronous computation. This paper proposes a solution where given a batch of data that has to be processed concurrently, a Merkle Tree can be constructed from the batch asynchronously without needing to recalculate the tree for every insert.
With the rise in using immature smart contract programming languages to build a decentralized application, more vulnerabilities have been introduced to the Blockchain and were the main reasons behind critical financial losses. Moreover, the immutability of Blockchain technology makes deployed smart contracts unfixable for the whole life of the Blockchain itself. The lack of complete and up-to-date resources that explain those vulnerabilities in detail has also contributed to increasing the number of vulnerabilities in Blockchain. In addition, the lack of a standardized nomination of the existing vulnerabilities has made redundant research and made developers more confused. Therefore, in this paper, we propose the most complete list of smart contract vulnerabilities that exist in the most popular Blockchains with a detailed explanation of each one of them. In addition, we propose a new codification system that facilitates the communication of those vulnerabilities between developers and researchers. This codification, help identify the most uncovered vulnerabilities to focus on in future research. Moreover, the discussed list of vulnerabilities covers multiple Blockchain and could be used for even future built Blockchains.
Cem Bicer, Ilir Murturi, Praveen Kumar Donta, Schahram Dustdar
Internet of Things (IoT) devices pose significant security challenges due to their heterogeneity (i.e., hardware and software) and vulnerability to extensive attack surfaces. Today's conventional perimeter-based systems use credential- based authentication (e.g., username/password, certificates, etc.) to decide whether an actor can access a network. However, the verification process occurs only at the system's perimeter because most IoT devices lack robust security measures due to their limited hardware and software capabilities, making them highly vulnerable. Therefore, this paper proposes a novel approach based on Zero Trust Architecture (ZTA) extended with blockchain to further enhance security. The blockchain component serves as an immutable database for storing users' requests and is used to verify trustworthiness by analyzing and identifying potentially malicious user activities. We discuss the framework, processes of the approach, and the experiments carried out on a testbed to validate its feasibility and applicability in the smart city context. Lastly, the evaluation focuses on non-functional properties such as performance, scalability, and complexity.
Frank Christian Geyer, Hans-Arno Jacobsen, Ruben Mayer, Peter Mandl
The emergence of more and more blockchain solutions with innovative approaches to optimising performance, scalability, privacy and governance complicates performance analysis. Reasons for the difficulty of benchmarking blockchains include, for example, the high number of system parameters to configure and the effort to deploy a blockchain network. In addition, performance data, which mostly comes from system vendors, is often intransparent. We investigate and evaluate the performance of seven permissioned blockchain systems using different parameter settings in a reproducible manner. We employ an end-to-end approach, where the clients sending the transactions are fully involved in the data collection approach. Our results highlight the peculiarities and limitations of the systems under investigation. Due to the insights given, our work forms the basis for continued research to optimise the performance of blockchain systems.
Federated Learning (FL) emerges as a viable solution to facilitate data collaboration, enabling multiple clients to collaboratively train a machine learning (ML) model under the supervision of a central server while ensuring the confidentiality of their raw data. However, existing studies have unveiled two main risks: (i) the potential for the server to infer sensitive information from the client's uploaded updates (i.e., model gradients), compromising client input privacy, and (ii) the risk of malicious clients uploading malformed updates to poison the FL model, compromising input integrity. Recent works utilize secure aggregation with zero-knowledge proofs (ZKP) to guarantee input privacy and integrity in FL. Nevertheless, they suffer from extremely low efficiency and, thus, are impractical for real deployment. In this paper, we propose a novel and highly efficient approach RiseFL for secure and verifiable data collaboration, ensuring input privacy and integrity simultaneously. Firstly, we devise a probabilistic integrity check method that transforms strict checks into a hypothesis test problem, offering great optimization opportunities. Secondly, we introduce a hybrid commitment scheme to satisfy Byzantine robustness with improved performance. Thirdly, we present an optimized ZKP generation and verification technique that significantly reduces the ZKP cost based on probabilistic integrity checks. Furthermore, we theoretically prove the security guarantee of RiseFL and provide a cost analysis compared to state-of-the-art baselines. Extensive experiments on synthetic and real-world datasets suggest that our approach is effective and highly efficient in both client computation and communication. For instance, RiseFL is up to 28x, 53x, and 164x faster than baselines ACORN, RoFL, and EIFFeL for the client computation.
Davide Frey, Lucie Guillou, Michel Raynal, François Taı̈ani
This paper explores the territory that lies between best-effort Byzantine-Fault-Tolerant Conflict-free Replicated Data Types (BFT CRDTs) and totally ordered distributed ledgers, such as those implemented by Blockchains. It formally characterizes a novel class of distributed objects that only requires a First In First Out (FIFO) order on the object operations from each process (taken individually). The formalization leverages Mazurkiewicz traces to define legal sequences of operations and ensure both Strong Eventual Consistency (SEC) and Pipleline Consistency (PC). The paper presents a generic algorithm that implements this novel class of distributed objects both in a crash- and Byzantine setting. It also illustrates the practical interest of the proposed approach using four instances of this class of objects, namely money transfer, Petri nets, multi-sets, and concurrent work stealing dequeues.
Web 3.0, as the third generation of the World Wide Web, aims to solve contemporary problems of trust, centralization, and data ownership. Driven by the latest advances in cutting-edge technologies, Web 3.0 is moving towards a more open, decentralized, intelligent, and interconnected network. However, increasingly widespread data breaches have raised awareness of online privacy and security of personal data. Additionally, since Web 3.0 is a sophisticated and complex convergence, the technical details behind it are not as clear as the characteristics it presents. In this survey, we conduct an in-depth exploration of Web 3.0 from the perspectives of blockchain, artificial intelligence, and edge computing. Specifically, we begin with summarizing the evolution of the Internet and providing an overview of these three key technological factors. Afterward, we provide a thorough analysis of each technology separately, including its relevance to Web 3.0, key technology components, and practical applications. We also propose decentralized storage and computing solutions by exploring the integration of technologies. Finally, we highlight the key challenges alongside potential research directions. Through the combination and mutual complementation of multiple technologies, Web 3.0 is expected to return more control and ownership of data and digital assets back to users.
This research delves into the intricacies of Bitcoin, a decentralized peer-to-peer network, and its associated blockchain, which records all transactions since its inception. While this ensures integrity and transparency, the transparent nature of Bitcoin potentially compromises users' privacy rights. To address this concern, users have adopted CoinJoin, a method that amalgamates multiple transaction intents into a single, larger transaction to bolster transactional privacy. This process complicates individual transaction tracing and disrupts many established blockchain analysis heuristics. Despite its significance, limited research has been conducted on identifying CoinJoin transactions. Particularly noteworthy are varied CoinJoin implementations such as JoinMarket, Wasabi, and Whirlpool, each presenting distinct challenges due to their unique transaction structures. This study delves deeply into the open-source implementations of these protocols, aiming to develop refined heuristics for identifying their transactions on the blockchain. Our exhaustive analysis covers transactions up to block 760,000, offering a comprehensive insight into CoinJoin transactions and their implications for Bitcoin blockchain analysis.
We present a secure and private blockchain-based Verifiable Random Function (VRF) scheme addressing some limitations of classical VRF constructions. Given the imminent quantum computing adversarial scenario, conventional cryptographic methods face vulnerabilities. To enhance our VRF's secure randomness, we adopt post-quantum Ring-LWE encryption for synthesizing pseudo-random sequences. Considering computational costs and resultant on-chain gas costs, we suggest a bifurcated architecture for VRF design, optimizing interactions between on-chain and off-chain. Our approach employs a secure ring signature supported by NIZK proof and a delegated key generation method, inspired by the Chaum-Pedersen equality proof and the Fiat-Shamir Heuristic. Our VRF scheme integrates multi-party computation (MPC) with blockchain-based decentralized identifiers (DID), ensuring both security and randomness. We elucidate the security and privacy aspects of our VRF scheme, analyzing temporal and spatial complexities. We also approximate the entropy of the VRF scheme and detail its implementation in a Solidity contract. Also, we delineate a method for validating the VRF's proof, matching for the contexts requiring both randomness and verification. Conclusively, using the NIST SP800-22 of the statistical randomness test suite, our results exhibit a 98.86% pass rate over 11 test cases, with an average p-value of 0.5459 from 176 total tests.
Blockchains add transactions to a distributed shared ledger by arriving at consensus on sets of transactions contained in blocks. This provides a total ordering on a set of global transactions. However, total ordering is not enough to satisfy application semantics under the Byzantine fault model. This is due to the fact that malicious miners and clients can collaborate to add their own transactions ahead of correct clients' transactions in order to gain application level and financial advantages. These attacks fall under the umbrella of front-running attacks. Therefore, total ordering is not strong enough to preserve application semantics. In this paper, we propose causality preserving total order as a solution to this problem. The resulting Blockchains will be stronger than traditional consensus based blockchains and will provide enhanced security ensuring correct application semantics in a Byzantine setting.
The classical distributed key generation protocols (DKG) are resurging due to their widespread applications in blockchain. While efforts have been made to improve DKG communication, practical large-scale deployments are still yet to come due to various challenges, including the heavy computation and communication (particularly broadcast) overhead in their adversarial cases. In this paper, we propose a practical DKG for DLog-based cryptosystems, which achieves (quasi-)linear computation and communication per-node cost with the help of a common coin, even in the face of the maximal amount of Byzantine nodes. Moreover, our protocol is secure against adaptive adversaries, which can corrupt less than half of all nodes. The key to our improvements lies in delegating the most costly operations to an Any-Trust group together with a set of techniques for adaptive security. This group is randomly sampled and consists of a small number of individuals. The population only trusts that at least one member in the group is honest, without knowing which one. Moreover, we present a generic transformer that enables us to efficiently deploy a conventional distributed protocol like our DKG, even when the participants have different weights. Additionally, we introduce an extended broadcast channel based on a blockchain and data dispersal network (such as IPFS), enabling reliable broadcasting of arbitrary-size messages at the cost of constant-size blockchain storage.
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.
Romaric Duvignau, Michel Raynal, Elad Michael Schiller
Consensus, abstracting a myriad of problems in which processes have to agree on a single value, is one of the most celebrated problems of fault-tolerant distributed computing. Consensus applications include fundamental services for the environments of the Cloud and Blockchain, and in such challenging environments, malicious behaviors are often modeled as adversarial Byzantine faults. At OPODIS 2010, Mostefaoui and Raynal (in short MR) presented a Byzantine-tolerant solution to consensus in which the decided value cannot be a value proposed only by Byzantine processes. MR has optimal resilience coping with up to t < n/3 Byzantine nodes over n processes. MR provides this multivalued consensus object (which accepts proposals taken from a finite set of values) assuming the availability of a single Binary consensus object (which accepts proposals taken from the set {0,1}). This work, which focuses on multivalued consensus, aims at the design of an even more robust solution than MR. Our proposal expands MR's fault-model with self-stabilization, a vigorous notion of fault-tolerance. In addition to tolerating Byzantine, self-stabilizing systems can automatically recover after the occurrence of arbitrary transient-faults. These faults represent any violation of the assumptions according to which the system was designed to operate (provided that the algorithm code remains intact). To the best of our knowledge, we propose the first self-stabilizing solution for intrusion-tolerant multivalued consensus for asynchronous message-passing systems prone to Byzantine failures. Our solution has a O(t) stabilization time from arbitrary transient faults.
Pierre Civit, Seth Gilbert, Rachid Guerraoui, Jovan Komatovic · 6 authors
Byzantine agreement, arguably the most fundamental problem in distributed computing, operates among n processes, out of which t < n can exhibit arbitrary failures. The problem states that all correct (non-faulty) processes must eventually decide (termination) the same value (agreement) from a set of admissible values defined by the proposals of the processes (validity). Depending on the exact version of the validity property, Byzantine agreement comes in different forms, from Byzantine broadcast to strong and weak consensus, to modern variants of the problem introduced in today's blockchain systems. Regardless of the specific flavor of the agreement problem, its communication cost is a fundamental metric whose improvement has been the focus of decades of research. The Dolev-Reischuk bound, one of the most celebrated results in distributed computing, proved 40 years ago that, at least for Byzantine broadcast, no deterministic solution can do better than Omega(t^2) exchanged messages in the worst case. Since then, it remained unknown whether the quadratic lower bound extends to seemingly weaker variants of Byzantine agreement. This paper answers the question in the affirmative, closing this long-standing open problem. Namely, we prove that any non-trivial agreement problem requires Omega(t^2) messages to be exchanged in the worst case. To prove the general lower bound, we determine the weakest Byzantine agreement problem and show, via a novel indistinguishability argument, that it incurs Omega(t^2) exchanged messages.
Programmable money, enabled by digital currencies, facilitates outcomes beyond simple payments by allowing users to attach conditions to the movement of funds through code. However, there is a lack of clarity on defining programmable money, where programmability can be implemented, and the resulting tradeoffs. This paper provides a definition of programmable money with four key components: a format for representing value, a set of programmable instructions, an execution environment providing a coherence guarantee, and rules around permissioning. We discuss programmability primitives, categorizing them into levels based on expressiveness. We outline four locations programmability could be offered - hardcoded into system rules, via client-supplied programs/smart contracts, in client code, or via intermediaries - analyzing benefits and risks of each. For policymakers evaluating central bank digital currencies, we recommend considering these aspects holistically and their interplay with regulation in system design. Our framework and vocabulary enable more nuanced analysis of implementing programmability.
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.
In the realm of open and composable gaming, we envision platforms where users actively expand, create, engage, and immerse themselves in a rich world of entertainment. One promising avenue for achieving this vision is through fully on-chain (FOC) games, where both game state and logic reside on the blockchain, maximizing composability. However, we must grapple with inherent limitations and trade-offs, particularly in terms of costs and scalability. This paper proposes a framework that leverages the Solana Virtual Machine (SVM) to scale FOC games without state fragmentation or compromised trust assumptions. The framework introduces a systematic approach for discovering, utilizing, and publishing modular pieces of logic as components deeply rooted in the Entity-Component-System (ECS) pattern. To enhance scalability and resource optimization, we introduce the concept of Ephemeral Rollups (ERs) that overcome the tradeoffs of L2 horizontal scaling. These dedicated runtimes can be customized to provide higher operational speed, configurable ticking mechanisms, provable sessions and gasless transactions without composability-scalability tradeoffs.
Recently, permissioned blockchain has been extensively explored in various fields, such as asset management, supply chain, healthcare, and many others. Many scholars are dedicated to improving its verifiability, scalability, and performance based on sharding techniques, including grouping nodes and handling cross-shard transactions. However, they ignore the node vulnerability problem, i.e., there is no guarantee that nodes will not be maliciously controlled throughout their life cycle. Facing this challenge, we propose RecAGT, a novel identification scheme aimed at reducing communication overhead and identifying potential malicious nodes. First, shard testable codes are designed to encode the original data in case of a leak of confidential data. Second, a new identity proof protocol is presented as evidence against malicious behavior. Finally, adaptive group testing is chosen to identify malicious nodes. Notably, our work focuses on the internal operation within the committee and can thus be applied to any sharding permissioned blockchains. Simulation results show that our proposed scheme can effectively identify malicious nodes with low communication and computational costs.
Ibrahim Aliyu, Cho-Rong Yu, Tai-Won Um, Jinsul Kim
The computing in the network (COIN) paradigm has emerged as a potential solution for computation-intensive applications like the metaverse by utilizing unused network resources. The blockchain (BC) guarantees task-offloading privacy, but cost reduction, queueing delays, and redundancy elimination remain open problems. This paper presents a redundancy-aware BC-based approach for the metaverse's partial computation offloading (PCO). Specifically, we formulate a joint BC redundancy factor (BRF) and PCO problem to minimize computation costs, maximize incentives, and meet delay and BC offloading constraints. We proved this problem is NP-hard and transformed it into two subproblems based on their temporal correlation: real-time PCO and Markov decision process-based BRF. We formulated the PCO problem as a multiuser game, proposed a decentralized algorithm for Nash equilibrium under any BC redundancy state, and designed a double deep Q-network-based algorithm for the optimal BRF policy. The BRF strategy is updated periodically based on user computation demand and network status to assist the PCO algorithm. The experimental results suggest that the proposed approach outperforms existing schemes, resulting in a remarkable 47% reduction in cost overhead, delivering approximately 64% higher rewards, and achieving convergence in just a few training episodes.
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.
As blockchain technology continues to advance, the secure deployment of smart contracts has become increasingly prevalent, underscoring the critical need for robust security measures. This surge in usage has led to a rise in security breaches, often resulting in substantial financial losses for users. This article presents a comprehensive survey of smart contract quality assurance, from understanding vulnerabilities to evaluating the effectiveness of detection tools. Our work is notable for its innovative classification of 40 smart contract vulnerabilities, mapping them to established attack patterns. We further examine nine defense mechanisms, assessing their efficacy in mitigating smart contract attacks. Furthermore, we develop a labeled dataset as a benchmark encompassing 10 common vulnerability types, which serves as a critical resource for future research. We also conduct comprehensive experiments to evaluate 14 vulnerability detection tools, providing a comparative analysis that highlights their strengths and limitations. In summary, this survey synthesizes state-of-the-art knowledge in smart contract security, offering practical recommendations to guide future research and foster the development of robust security practices in the field.