Patients living in a digitized world can now interact with medical professionals through online services such as chat applications, video conferencing or indirectly through consulting services. These applications need to tackle several fundamental trust issues: 1. Checking and confirming that the person they are interacting with is a real person; 2. Validating that the healthcare professional has competence within the field in question; and 3. Confirming that the healthcare professional has a valid license to practice. In this paper, we present VerifyMed -- the first proof-of-concept platform, built on Ethereum, for transparently validating the authorization and competence of medical professionals using blockchain technology. Our platform models trust relationships within the healthcare industry to validate professional clinical authorization. Furthermore, it enables a healthcare professional to build a portfolio of real-life work experience and further validates the competence by storing outcome metrics reported by the patients. The extensive realistic simulations show that with our platform, an average cost for creating a smart contract for a treatment and getting it approved is around 1 USD, and the cost for evaluating a treatment is around 50 cents.
Lei Wu, Siwei Wu, Yajin Zhou, Runhuai Li · 8 authors
As one of the representative blockchain platforms, Ethereum has attracted lots of attacks. Due to the existed financial loss, there is a pressing need to perform timely investigation and detect more attack instances. Though multiple systems have been proposed, they suffer from the scalability issue due to the following reasons. First, the tight coupling between malicious contract detection and blockchain data importing makes them infeasible to repeatedly detect different attacks. Second, the coarse-grained archive data makes them inefficient to replay transactions. Third, the separation between malicious contract detection and runtime state recovery consumes lots of storage. In this paper, we present the design of a scalable attack detection framework on Ethereum. It overcomes the scalability issue by saving the Ethereum state into a database and providing an efficient way to locate suspicious transactions. The saved state is fine-grained to support the replay of arbitrary transactions. The state is well-designed to avoid saving unnecessary state to optimize the storage consumption. We implement a prototype named EthScope and solve three technical challenges, i.e., incomplete Ethereum state, scalability, and extensibility. The performance evaluation shows that our system can solve the scalability issue, i.e., efficiently performing a large-scale analysis on billions of transactions, and a speedup of around 2,300x when replaying transactions. It also has lower storage consumption compared with existing systems. The result with three different types of information as inputs shows that our system can help an analyst understand attack behaviors and further detect more attacks. To engage the community, we will release our system and the dataset of detected attacks.
Lei Wu, Siwei Wu, Yajin Zhou, Runhuai Li · 8 authors
As one of the representative blockchain platforms, Ethereum has attracted
lots of attacks. Due to the potential financial loss, there is a pressing need
to detect malicious smart contracts and understand their behaviors. Though
there exist multiple systems for smart contract analysis, they cannot
efficiently analyze a large number of transactions and re-execute smart
contracts to introspect malicious behaviors. In this paper, we urge for a transaction-centric security analytics framework
for Ethereum, which provides an efficient way to quickly locate suspicious ones
from a large number of transactions and extensible way to detect malicious
smart contracts with analyst-provided scripts. We present the system design in
the paper, which solves three technical challenges, i.e., incomplete states,
scalability and extensibility. We have implemented a prototype system named
EthScope to solve these challenges. In particular, the first component Data
Aggregator collects and recovers critical blockchain states. The second
component Replay Engine is able to {replay} arbitrary and a large number of
transactions. The third component Instrumentation Framework exposes interfaces
for an analyst to dynamically instrument smart contracts and introspect the
execution of suspicious transactions. The comprehensive evaluation with six
types of attacks demonstrated the effectiveness of our system. The performance
evaluation shows that our system can perform a large-scale analysis on
suspicious transactions (more than 8 million ones) and has a speed up of around
2,300x compared with the JSTracer provided by Go-Ethereum. To engage the
community, we will release our system and a dataset of detected attacks on
https://github.com/zjuicsr/ethscope.
The selfdestruct function is provided by Ethereum smart contracts to destroy a contract on the blockchain system. However, it is a double-edged sword for developers. On the one hand, using the selfdestruct function enables developers to remove smart contracts ( SCs ) from Ethereum and transfers Ethers when emergency situations happen, e.g., being attacked. On the other hand, this function can increase the complexity for the development and open an attack vector for attackers. To better understand the reasons why SC developers include or exclude the selfdestruct function in their contracts, we conducted an online survey to collect feedback from them and summarize the key reasons. Their feedback shows that 66.67% of the developers will deploy an updated contract to the Ethereum after destructing the old contract. According to this information, we propose a method to find the self-destructed contracts (also called predecessor contracts) and their updated version (successor contracts) by computing the code similarity. By analyzing the difference between the predecessor contracts and their successor contracts, we found five reasons that led to the death of the contracts; two of them (i.e., Unmatched ERC20 Token and Limits of Permission ) might affect the life span of contracts. We developed a tool named LifeScope to detect these problems. LifeScope reports 0 false positives or negatives in detecting Unmatched ERC20 Token . In terms of Limits of Permission , LifeScope achieves 77.89% of F-measure and 0.8673 of AUC in average. According to the feedback of developers who exclude selfdestruct functions, we propose suggestions to help developers use selfdestruct functions in Ethereum smart contracts better.
Edge computing draws a lot of recent research interests because of the performance improvement by offloading many workloads from the remote data center to nearby edge nodes. Nonetheless, one open challenge of this emerging paradigm lies in the potential security issues on edge nodes and end devices, e.g., sensors and controllers. This paper proposes a cooperative protocol, namely DEAN, across edge nodes to prevent data manipulation, and to allow fair data sharing with quick recovery under resource constraints of limited storage, computing, and network capacity. Specifically, DEAN leverages a parallel mechanism equipped with three independent core components, effectively achieving low resource consumption while allowing secured parallel block processing on edge nodes. We have implemented a system prototype based on DEAN and experimentally verified its effectiveness with a comparison with three popular blockchain implementations: Ethereum, Parity, and Hyperledger Fabric. Experimental results show that the system prototype exhibits high resilience to arbitrary failures: the percentile of trusty nodes is much higher than the required 50\% in most cases. Performance-wise, DEAN-based blockchain implementation outperforms the state-of-the-art blockchain systems with up to $25\times$ higher throughput and $18\times$ lower latency on 1,000 nodes.
USDOE Office of Electricity Delivery and Energy Reliability (OE), Mariola Rodríguez, Peter L. Fuhr, Gary Hahn · 6 authors
This paper provides descriptions of the key components of different distributed ledger technology platforms.Distributed ledger technology (DLT) allows for distribution of databases among different organizations and devices.The platforms use cryptographically linked "blocks" to store and verify transactional information between these organizations.DLT increases data security, data integrity, trust among its participants.Different organizations are looking to deploy this distributed and decentralized approach to avoid the single-point-of-failure vulnerabilities associated with centralized data repositories.In this study we examine twelve different DLT platforms.There is agreement within the community that of all the platforms considered here, Hyperledger and Ethereum are the most mature when it comes to privacy and permissions.These DLT platforms are being used for applications such as transactive energy, health care, and the food and goods supply chain.However, further development is required to realize the full promise of DLT.Our assessment includes a general description of each DLT and its key characteristics.Such characteristics include consensus protocol and cryptography used, public vs. private, and permissioned or permissionless.The selection and implementation of a DLT architecture depends heavily on the use case and performance requirements.During this research we found key parameters to measure performance and existing tools for assessment.Four different parameters were identified 1) consensus, 2) throughput, 3) latency, and 4) scalability.The architectures of Hyperledger Caliper and Blockbench are described as different performance assessment frameworks.From this preliminary study it is evident that there are dissimilarities on the performance assessments methods developers and users are characterizing DLT architectures.The purpose of this paper is to identify key parameters to test performance, tools that are being used and provide information on results from previous studies.
Sean Cao, Lin William Cong, Meng Han, Qixuan Hou · 5 authors
Business transactions by public firms are required to be reported, verified, and audited periodically, which is traditionally a labor-intensive and time-consuming process. To streamline this procedure, we design FutureAB (Future Auditing Blockchain) which aims to automate the reporting and auditing process, thereby allowing auditors to focus on discretionary accounts to better detect and prevent fraud. We demonstrate how distributed-ledger technologies build investor trust and disrupt the auditing industry. Our multi-functional design indicates that auditing firms can automate transaction verification without the need for a trusted third party by collaborating and sharing their information while preserving data privacy (commitment scheme) and security (immutability). We also explore how smart contracts and wallets facilitate the computerization and implementation of our system on Ethereum. Finally, performance evaluation reveals the efficacy and scalability of FutureAB in terms of both encryption (0.012 seconds per transaction) and verification (0.001 seconds per transaction).
With the release of Satoshi Nakamoto's Bitcoin system in 2008 a new decentralized computation paradigm, known as blockchain, was born. Bitcoin promised a trading network for virtual coins, publicly available for anyone to participate in but owned by nobody. Any participant could propose a transaction and a lottery mechanism decided in which order these transactions would be recorded in a ledger with an elegant mechanism to prevent double spending. The remarkable achievement of Nakamoto's protocol was that participants did not have to trust each other to behave correctly for it to work. As long as more than half of the network participants adhered to the correct code, the recorded transactions on the ledger would both be valid and immutable. \n \nEthereum, as the next major blockchain to appear, improved on the initial idea by introducing smart contracts, which are decentralized Turing-complete stored procedures, thus making blockchain technology interesting for the enterprise setting. However, its intrinsically public data and prohibitive energy costs needed to be overcome. This gave rise to a new type of systems called permissioned blockchains. With these, access to the ledger is restricted and trust assumptions about malicious behaviour have been weakened, allowing more efficient consensus mechanisms to find a global order of transactions. One of the most popular representatives of this kind of blockchain is Hyperledger Fabric. While it is much faster and more energy efficient than permissionless blockchains, it has to compete with conventional distributed databases in the enterprise sector. \n \nThis thesis aims to mitigate Fabric's three major shortcomings. First, compared to conventional database systems, it is still far too slow. This thesis shows how the performance can be increased by a factor of seven by redesigning the transaction processing pipeline and introducing more efficient data structures. Second, we present a novel solution to Fabric's intrinsic problem of a low throughput for workloads with transactions that access the same data. This is achieved by analyzing the dependencies of transactions and selectively re-executing transactions when a conflict is detected. Third, this thesis tackles the preservation of private data. Even though access to the blockchain as a whole can be restricted, in a setting where multiple enterprises collaborate this is not sufficient to protect sensitive proprietary data. Thus, this thesis introduces a new privacy-preserving blockchain protocol based on network sharding and targeted data dissemination. It also introduces an additional layer of abstraction for the creation of transactions and interaction with data on the blockchain. This allows developers to write applications without the need for low-level knowledge of the internal data structure of the blockchain system. In summary, this thesis addresses the shortcomings of the current generation of permission blockchain systems.
The commercial real estate market is a significant part of the global economy, currently dominated by a small set of firms and organizations that lack transparency. The process of property transfers also requires third party intervention which is expensive. In many countries, the process of title transfers is problematic. We are still in the initial steps of digitization, due to the improvement required in terms of use of technology to represent assets in digital forms. Increase in liquidity of investments and purchases, proper management, documentation as well as ease of access is the future of real estate. Blockchain technologies have the potential to drive these changes as explained in Chapter 1. Blockchain technologies like Ethereum[1] include asset tokenization, and act as immutable and decentralized transaction ledgers. Tokens on the ledger can represent the real estate assets. Particulary, the non-fungible tokens on Ethereum can serve as a representation of transfer of resources. Ethereum grants trusted and distributed smart contracts for token operations. My project is a system for real estate cadastral record keeping and title transfers that uses the ERC-721 specification[2] related to the non-fungible tokens. Testing of the implementation is done using Government records from District of Columbia[3]. Ethereum is a natural choice for this project due to its evolution, an active development community, and many supporting languages and tools that facilitate use of smart contracts. This paper gives the background, implementation details and significance of such a system. Some cost-related and defensive mechanisms offered by the system are discussed later in the report.
Abstract A smart contract (SC) is a programme stored in the Ethereum blockchain by a contract‐creation transaction. SC developers deploy an instance of the SC and attempt to execute it in exchange for a fee, paid in Ethereum coins (Ether). If the computation needed for their execution turns out to be larger than the effort proposed by the developer (i.e., the gasLimit ), their client instantiation will not be completed successfully. In this paper, we examine SCs from 11 Ethereum blockchain‐oriented software projects hosted on GitHub.com , and we evaluate the resources needed for their deployment (i.e., the gasUsed ). For each of these contracts, we also extract a suite of object‐oriented metrics, to evaluate their structural characteristics. Our results show a statistically significant correlation between some of the object‐oriented (OO) metrics and the resources consumed on the Ethereum blockchain network when deploying SCs. This result has a direct impact on how Ethereum developers engage with a SC: evaluating its structural characteristics, they will be able to produce a better estimate of the resources needed to deploy it. Other results show specific source code metrics to be prioritised based on application domains when the projects are clustered based on common themes.
Clara Schneidewind, Ilya Grishchenko, Markus Scherer, Matteo Maffei
Ethereum has emerged as the most popular smart contract development platform, with hundreds of thousands of contracts stored on the blockchain and covering a variety of application scenarios, such as auctions, trading platforms, and so on. Given their financial nature, security vulnerabilities may lead to catastrophic consequences and, even worse, they can be hardly fixed as data stored on the blockchain, including the smart contract code itself, are immutable. An automated security analysis of these contracts is thus of utmost interest, but at the same time technically challenging for a variety of reasons, such as the specific transaction-oriented programming mechanisms, which feature a subtle semantics, and the fact that the blockchain data which the contract under analysis interacts with, including the code of callers and callees, are not statically known. In this work, we present eThor, the first sound and automated static analyzer for EVM bytecode, which is based on an abstraction of the EVM bytecode semantics based on Horn clauses. In particular, our static analysis supports reachability properties, which we show to be sufficient for capturing interesting security properties for smart contracts (e.g., single-entrancy) as well as contract-specific functional properties. Our analysis is proven sound against a complete semantics of EVM bytecode and an experimental large-scale evaluation on real-world contracts demonstrates that eThor is practical and outperforms the state-of-the-art static analyzers: specifically, eThor is the only one to provide soundness guarantees, terminates on 95% of a representative set of real-world contracts, and achieves an F-measure (which combines sensitivity and specificity) of 89%.
Electric Vehicles (EVs) have generated a lot of interest in recent years, due to the advances in battery life and low pollution. Similarly, the expansion of the Internet of Things (IoT) allowed more and more devices to be interconnected. One major problem EVs face today is the limited range of the battery and the limited number of charging or battery swapping stations. A solution is to not only build the necessary infrastructure, but also to be able to correctly estimate the remaining power using an efficient battery management system (BMS). For some EVs, battery swapping can also be an option, either at registered stations, or even directly from other EV drivers. Thus, a network of EV information is required, so that a successful battery charge or swap can be made available for drivers. In this paper two blockchain implementations for an EV BMS are presented, using blockchain as the network and data layer of the application. The first implementation uses Ethereum as the blockchain framework for developing smart contracts, while the second uses a directed acyclic graph (DAG), on top of the IOTA tangle. The two approaches are implemented and compared, demonstrating that both platforms can provide a viable solution for an efficient, semi-decentralized, data-driven BMS.
Clara Schneidewind, Ilya Grishchenko, M. Schérer, Matteo Maffei
Ethereum has emerged as the most popular smart contract development platform,\nwith hundreds of thousands of contracts stored on the blockchain and covering a\nvariety of application scenarios, such as auctions, trading platforms, and so\non. Given their financial nature, security vulnerabilities may lead to\ncatastrophic consequences and, even worse, they can be hardly fixed as data\nstored on the blockchain, including the smart contract code itself, are\nimmutable. An automated security analysis of these contracts is thus of utmost\ninterest, but at the same time technically challenging for a variety of\nreasons, such as the specific transaction-oriented programming mechanisms,\nwhich feature a subtle semantics, and the fact that the blockchain data which\nthe contract under analysis interacts with, including the code of callers and\ncallees, are not statically known.\n In this work, we present eThor, the first sound and automated static analyzer\nfor EVM bytecode, which is based on an abstraction of the EVM bytecode\nsemantics based on Horn clauses. In particular, our static analysis supports\nreachability properties, which we show to be sufficient for capturing\ninteresting security properties for smart contracts (e.g., single-entrancy) as\nwell as contract-specific functional properties. Our analysis is proven sound\nagainst a complete semantics of EVM bytecode and an experimental large-scale\nevaluation on real-world contracts demonstrates that eThor is practical and\noutperforms the state-of-the-art static analyzers: specifically, eThor is the\nonly one to provide soundness guarantees, terminates on 95% of a representative\nset of real-world contracts, and achieves an F-measure (which combines\nsensitivity and specificity) of 89%.\n
Summary Smart contracts can be implemented using either centralized or decentralized (blockchain) platforms. However, for a large class of applications, neither of these two alternatives on its own can provide adequate scalability, performance, quality of service, security, and trust requirements. We argue that for many applications, hybrid solutions that combine both on and off‐blockchain components are more adequate. In this article, we introduce the design and implementation of a novel hybrid smart contract architecture built using the Ethereum blockchain connected to a centralized smart contract management system developed by us. We then compare and evaluate the implementation of an asset tracking service using three different architectures: on‐chain, off‐chain, and hybrid. We demonstrate that using a hybrid architecture, we can substantially improve performance of applications while retaining security and trust for critical tasks.
Paulo Silva, David Vavřička, João Barreto, Miguel Matos
Given the large adoption and economical impact of permissionless blockchains, the complexity of the underlying systems and the adversarial environment in which they operate, it is fundamental to properly study and understand the emergent behavior and properties of these systems. We describe our experience on a detailed, one-month study of the Ethereum network from several geographically dispersed observation points. We leverage multiple geographic vantage points to assess the key pillars of Ethereum, namely geographical dispersion, network efficiency, blockchain efficiency and security, and the impact of mining pools. Among other new findings, we identify previously undocumented forms of selfish behavior and show that the prevalence of powerful mining pools exacerbates the geographical impact on block propagation delays. Furthermore, we provide a set of open measurement and processing tools, as well as the data set of the collected measurements, in order to promote further research on understanding permissionless blockchains.
Kerolly Kedma Felix do Nascimento, Fábio Sandro dos Santos, Jader da Silva Jale, Tiago A. E. Ferreira
Os mercados financeiros são sistemas complexos em que os negociadores interagem usando as mais variadas estratégias. Técnicas computacionais que usam agentes inteligentes podem auxiliar na tomada de decisão com o objetivo de maximizar os ganhos. Neste sentido, o objetivo deste artigo é observar o comportamento dos agentes financeiros participantes de mercados simulados e inferir sobre os ganhos destes agentes. Por meio do algoritmo Particle Swarm Optimization, utilizamos dois grupos distintos de agente inteligentes: um grupo utiliza um grau de crença na previsão dos ativos para o dia seguinte e o outro grupo não utiliza, em que ambos interagem entre si buscando maximizar seus ganhos. Foi realizada uma pesquisa exploratória, com análise de natureza quantitativa sobre os dados. Os resultados mostraram que o grupo que usa a previsão é mais homogêneo, apresentando maiores ganhos de riqueza média, com concentrações de capital e de ações adquiridos variando de acordo com a série histórica de preços utilizada (Bitcoin, Ethereum, Litcoin ou Ripple). Diante disso, o procedimento implementado pode ser aperfeiçoado e utilizado para o desenvolvimento de ambientes que visem a melhor compreensão dos mercados financeiros e auxiliem os agentes participantes dos mercados na definição de estratégias de negociação que possibilitem a minimização de perdas financeiras.
In the blockchain-based, distributed computing platform Ethereum, programs called smart contracts are compiled to bytecode and executed on the Ethereum Virtual Machine (EVM). Executing EVM bytecode is subject to monetary fees---a clear optimization target. Our aim is to superoptimize EVM bytecode by encoding the operational semantics of EVM instructions as SMT formulas and leveraging a constraint solver to automatically find cheaper bytecode. We implement this approach in our EVM Bytecode SuperOptimizer ebso and perform two large scale evaluations on real-world data sets.
Yuefeng Du, Huayi Duan, Anxin Zhou, Cong Wang · 6 authors
How to audit outsourced data in centralized storage like cloud is well-studied, but it is largely under-explored for the rising decentralized storage network (DSN) that bodes well for a billion-dollar market. To realize DSN as a usable service in a truly decentralized manner, the blockchain comes in handy -- to record and verify audit trails in forms of proof of storage, and based on that, to handle fair payments with necessary dispute resolution. Leaving the audit trails on the blockchain offers transparency and fairness, yet it 1) sacrifices privacy, as they may leak information about the data under audit, and 2) overwhelms on-chain resources, as they may be practically large in size and expensive to verify. Prior auditing designs in centralized settings are not directly applicable here. A handful of proposals targeting DSN cannot satisfactorily address these issues either. We present an auditing solution that addresses on-chain privacy and efficiency, from a synergy of homomorphic linear authenticators with polynomial commitments for succinct proofs, and the sigma protocol for provable privacy. The solution results in, per audit, 288-byte proof written to the blockchain, and constant verification cost. It can sustain long-term operation and easily scale to thousands of users on Ethereum.
Volker Strobel, Eduardo Castelló Ferrer, Marco Dorigo
Consensus achievement is a crucial capability for robot swarms, for example, for path selection, spatial aggregation, or collective sensing. However, the presence of malfunctioning and malicious robots (Byzantine robots) can make it impossible to achieve consensus using classical consensus protocols. In this work, we show how a swarm of robots can achieve consensus even in the presence of Byzantine robots by exploiting blockchain technology. Bitcoin and later blockchain frameworks, such as Ethereum, have revolutionized financial transactions. These frameworks are based on decentralized databases (blockchains) that can achieve secure consensus in peer-to-peer networks. We illustrate our approach in a collective sensing scenario where robots in a swarm are controlled via blockchain-based smart contracts (decentralized protocols executed via blockchain technology) that serve as "meta-controllers" and we compare it to state-of-the-art consensus protocols using a robot swarm simulator. Additionally, we show that our blockchain-based approach can prevent attacks where robots forge a large number of identities (Sybil attacks). The developed robot-blockchain interface is released as open-source software in order to facilitate future research in blockchain-controlled robot swarms. Besides increasing security, we expect the presented approach to be important for data analysis, digital forensics, and robot-to-robot financial transactions in robot swarms.
Internet of Things (IoT) is a set of technologies that enable network-connected devices to perform an action or share data among several connected devices or to a shared database. The actions can be anything from switching on an Air Conditioning device remotely to turning on the ignition of a car through a command issued from a remote location or asking Alexa or Google Assistant to search for weather conditions in an area. IoT has proved to be game-changing for many industries such as Supply Chain, Shipping and Transportation providing updates on the status of shipments in real time. This has resulted in a huge amount of data created by a lot of these devices all of which need to be processed in real time. In this thesis, we propose a method to collect sensor data from IoT devices and use blockchain to store and retrieve the collected data in a secure and decentralized fashion within a closed system, suitable for a single enterprise or a group of companies in industries like shipping where sharing data with each other is required. Much like blockchain, we envision a future where IoT devices can connect and disconnect to distributed systems without causing downtime for the data collection or storage or relying on a cloud-based storage system for synchronizing data between devices. We also look at how the performance of some of these distributed systems like Inter Planetary File System (IPFS) and Ethereum Swarm compare on low-powered devices like the raspberry pi.
Ethereum Research team has proposed a family of Casper blockchain consensus protocols for Ethereum 2.0. It has been shown in the literature that Casper Friendly Finality Gadget (Casper FFG) for Ethereum 2.0's beacon network cannot achieve liveness property in partially synchronous networks such as the Internet environment. The ``Correct-by-Construction'' family of Casper blockchain consensus protocols (CBC Casper) has been proposed as a finality gadget for the future release of Ethereum 2.0 blockchain. Unfortunately, neither constructive finality rule nor satisfactory liveness property has been obtained for CBC Casper, and it is commonly believed that CBC Casper could not achieve liveness property in asynchronous networks. This paper provides the first probabilistic CBC Casper protocol that achieves liveness property against $t=\lfloor \frac{n-1}{3}\rfloor$ Byzantine participants in complete asynchronous networks. The seminal work by Fisher, Lynch, and Paterson (FLP) shows that there does not exist a deterministic BFT protocol in complete asynchronous networks against a single failure. Existing BFT protocols for complete asynchronous networks are all probabilistic which are based either on individual coin-flipping or on common coin-flipping. This paper proposes the first secure and deterministic leaderless blockchain BFT protocol XP against $t=\lfloor \frac{n-1}{3}\rfloor$ Byzantine participants in complete asynchronous networks. This result does not contradict with FLP's impossibility results since XP leverages the total order properties of candidate blocks in blockchains (similar properties may not hold for general BFT application scenarios).
Ethereum Research team has proposed a family of Casper blockchain consensus protocols for Ethereum 2.0. It has been shown in the literature that Casper Friendly Finality Gadget (Casper FFG) for Ethereum 2.0's beacon network cannot achieve liveness property in partially synchronous networks such as the Internet environment. The "Correct-by-Construction" family of Casper blockchain consensus protocols (CBC Casper) has been proposed as a finality gadget for the future release of Ethereum 2.0 blockchain. Unfortunately, neither constructive finality rule nor satisfactory liveness property has been obtained for CBC Casper, and it is commonly believed that CBC Casper could not achieve liveness property in asynchronous networks. This paper provides the first probabilistic CBC Casper protocol that achieves liveness property against (n-1)/3 Byzantine participants in complete asynchronous networks.
Ward Beullens, Tim Beyne, Aleksei Udovenko, Giuseppe Vitto
The Legendre PRF relies on the conjectured pseudorandomness properties of the Legendre symbol with a hidden shift. Originally proposed as a PRG by Damgård at CRYPTO 1988, it was recently suggested as an efficient PRF for multiparty computation purposes by Grassi et al. at CCS 2016. Moreover, the Legendre PRF is being considered for usage in the Ethereum 2.0 blockchain. This paper improves previous attacks on the Legendre PRF and its higher-degree variant due to Khovratovich by reducing the time complexity from O(< (p log p/M) to O(p log2 p/M2) Legendre symbol evaluations when M ≤ 4√ p log2 p queries are available. The practical relevance of our improved attack is demonstrated by breaking three concrete instances of the PRF proposed by the Ethereum foundation. Furthermore, we generalize our attack in a nontrivial way to the higher-degree variant of the Legendre PRF and we point out a large class of weak keys for this construction. Lastly, we provide the first security analysis of two additional generalizations of the Legendre PRF originally proposed by Damgård in the PRG setting, namely the Jacobi PRF and the power residue PRF.