Runtime Verification (RV) of smart contracts ensures the absence of exploitations within a transaction during execution. It is a crucial security aspect that is often omitted due to its high onchain overhead. The lack of RV in public blockchains allowed attackers to compromise vulnerable contracts and cause significant monetary losses. Existing runtime protection solutions fail to address the onchain overhead limitation, which may hinder their deployment and undermine their effectiveness. To address this problem, we propose SRP (Smart contract Runtime Protection), an efficient framework that integrates an off-chain mechanism with on-chain contract execution to minimize the burden of RV. Our hybrid architecture aims to protect deployed smart contracts from real-time attacks while maintaining blockchain scalability. We first present SRP from a design perspective proposing a protocol customized for off-chain RV interoperability. Then, we evaluate our approach empirically and demonstrate the applicability of SRP using a proof-of-concept implementation on a local Ethereum network. We further generalize our evaluation results using a queue-theoretic approach. We present a discrete-time queuing network model of SRP and the block creation process. The model is then used to conduct an extensive data-driven parametric evaluation of SRP compared to onchain-only RV. Our empirical, experimental, and quantitative results indicate the feasibility and efficiency of our approach, where SRP outperforms the onchain-only mechanism in terms of service time and throughput, for increasing workloads. Lastly, we introduce a game-theoretic incentive mechanism enhancing the robustness and security of SRP. We analyze the security of SRP and demonstrate that the presence of at least one honest validator serves as a deterrent to RV forging attacks.
Decentralized Autonomous Organizations (DAOs) have emerged as pioneers of decentralized innovation, utilizing smart contracts and blockchain technology to operate autonomously. However, their progress is impeded by persistent security vulnerabilities. In response, we introduce a groundbreaking security solution: Decentralized Autonomous Verification (DAVe). DAVe integrates blockchain-based consensus mechanisms with advanced cryptographic techniques to establish a resilient security framework tailored to the specific requirements of DAOs. Through DAVe implementation, DAOs can effectively mitigate smart contract vulnerabilities, amplify transparency, and cultivate trust among participants. This solution represents a pivotal advancement in fortifying the future of decentralized governance, safeguarding the integrity of DAO operations amidst the ever-evolving landscape of cyber threats.
Hulin Yang, Mingzhe Li, Jin Zhang, Alia Asheralieva · 6 authors
The advent of Ethereum 2.0 has introduced significant changes, particularly the shift to Proof-of-Stake consensus. This change presents new opportunities and challenges for arbitrage. Amidst these changes, we introduce BriDe Arbitrager, a novel tool designed for Ethereum 2.0 that leverages Bribery-driven attacks to Delay block production and increase arbitrage gains. The main idea is to allow malicious proposers to delay block production by bribing validators/proposers, thereby gaining more time to identify arbitrage opportunities. Through analysing the bribery process, we design an adaptive bribery strategy. Additionally, we propose a Delayed Transaction Ordering Algorithm to leverage the delayed time to amplify arbitrage profits for malicious proposers. To ensure fairness and automate the bribery process, we design and implement a bribery smart contract and a bribery client. As a result, BriDe Arbitrager enables adversaries controlling a limited (< 1/4) fraction of the voting powers to delay block production via bribery and arbitrage more profit. Extensive experimental results based on Ethereum historical transactions demonstrate that BriDe Arbitrager yields an average of 8.66 ETH (16,442.23 USD) daily profits. Furthermore, our approach does not trigger any slashing mechanisms and remains effective even under Proposer Builder Separation and other potential mechanisms will be adopted by Ethereum.
Sagar Dev Achar, P Thejaswini, Sukumar Nandi, Sunit Kumar Nandi
The global paradigm shift toward edge computing has led to a growing demand for efficient integrity verification. Hash functions are one-way algorithms which act as a zero-knowledge proof of a datum’s contents. However, it is infeasible to compute hashes on devices with limited processing power and memory. Hence, we propose four novel LiteHash functions which are architecturally similar to SHA-512 yet simpler. By using various approximation techniques, our implementations reduce the computational costs of digesting a message into a hash. On validating our proposed designs using the NIST PRNG Test Suite, we observe SHA-512 equivalent cryptographic security while satisfying all desired hash function property requirements. We observe a minimum of 9.41% reduction in area, 20.47% reduction in power, and 22.05% increase in throughput. Our designs offer a throughput of up to 2 Gbps while reducing area and power by a maximum of 16.86% and 32.48%, respectively. LiteHash functions also support the computation of the entire SHA-2 family of hash functions (SHA-224/256/384/512) with minor architectural modifications.
Physical Unclonable Functions (PUFs) and Hardware Security
Blockchain adoption has surged with the rise of Decentralized Finance (DeFi) applications. However, the significant value of digital assets managed by DeFi protocols makes them prime targets for attacks. Current smart contract vulnerability detection tools struggle with DeFi protocols due to deep logical bugs arising from complex financial interactions between multiple smart contracts. These tools primarily analyze individual contracts and resort to brute-force methods for DeFi protocols crossing numerous smart contracts, leading to inefficiency. We introduce Foray, a highly effective attack synthesis framework against deep logical bugs in DeFi protocols. Foray proposes a novel attack sketch generation and completion framework. Specifically, instead of treating DeFis as regular programs, we design a domain-specific language (DSL) to lift the low-level smart contracts into their high-level financial operations. Based on our DSL, we first compile a given DeFi protocol into a token flow graph, our graphical representation of DeFi protocols. Then, we design an efficient sketch generation method to synthesize attack sketches for a certain attack goal (e.g., price manipulation, arbitrage, etc.). This algorithm strategically identifies candidate sketches by finding reachable paths in TFG, which is much more efficient than random enumeration. For each candidate sketch written in our DSL, Foray designs a domain-specific symbolic compilation to compile it into SMT constraints. Our compilation simplifies the constraints by removing redundant smart contract semantics. It maintains the usability of symbolic compilation, yet scales to problems orders of magnitude larger. Finally, the candidates are completed via existing solvers and are transformed into concrete attacks via direct syntax transformation.
Fischlin's transform (CRYPTO 2005) is an alternative to the Fiat-Shamir transform that enables straight-line extraction when proving knowledge. In this work we focus on the problem of using the Fischlin transform to construct UC-secure zero-knowledge from Sigma protocols, since UC security – that guarantees security under general concurrent composition – requires straight-line (non-rewinding) simulators. We provide a slightly simplified transform that is much easier to understand, and present algorithmic and implementation optimizations that significantly improve the running time. It appears that the main obstacles to the use of Fischlin in practice is its computational cost and implementation complexity (with multiple parameters that need to be chosen). We provide clear guidelines and a simple methodology for choosing parameters, and show that with our optimizations the running-time is far lower than expected. For just one example, on a 2023 MacBook, the cost of proving the knowledge of discrete log with Fischlin is only 0.41ms (on a single core). This is 15 times slower than plain Fiat-Shamir on the same machine, which is a significant multiple but objectively not significant in many applications. We also extend the transform so that it can be applied to batch proofs, and show how this can be much more efficient than individually proving each statement. We hope that this paper will both encourage and help practitioners implement the Fischlin transform where relevant.
This study builds on our previous systematic literature review (SLR) that assessed the applications and performance of zk-SNARK, zk-STARK, and Bulletproof non-interactive zero-knowledge proof (NIZKP) protocols. To address the identified research gaps, we designed and implemented a benchmark comparing these three protocols using a dynamic minimized multiplicative complexity (MiMC) hash application. We evaluated performance across four general-purpose programming libraries and two programming languages. Our results show that zk-SNARK produced the smallest proofs, while zk-STARK generated the largest. In terms of proof generation and verification times, zk-STARK was the fastest, and Bulletproof was the slowest. Interestingly, zk-SNARK proofs verified marginally faster than zk-STARK, contrary to other findings. These insights enhance our understanding of the functionality, security, and performance of NIZKP protocols, providing valuable guidance for selecting the most suitable protocol for specific applications.
Function-as-a-Service providers manage security devices that are shared among multiple tenants. It is undesirable to give them access to cleartext HTTP requests to perform tasks such as traffic inspection. The recent Zero-Knowledge Middlebox (ZKMB) can be used to enforce network policies on TLS traffic without revealing any information on the content to the policy verifier. In this paper, we describe a ZKMB implementation and a policy designed to check whether the HTTPS function invocations by the clients follow a legitimate pattern. We also present and compare two strategies to distribute allowed patterns, introducing a Moving-Target Defense approach for the function URI randomization, which shows a good tradeoff between detection effectiveness and confidentiality. Performance assessment in our prototype implementation shows that the ZK algorithms are not yet suitable for real-time execution, but current research interest in this technology is expected to narrow this gap.
Ethereum is the first and largest blockchain that supports smart contracts. To enhance scalability and security, one major planned change of Ethereum 2.0 (Eth2) is to upgrade the smart contract interpreter from Ethereum Virtual Machine (EVM) to WebAssembly (WASM). In the meanwhile, many other popular blockchains have adopted WASM. Since Ethereum hosts millions of smart contracts, it is highly desirable to automatically migrate EVM smart contracts to WASM code to foster the prosperity of the blockchain ecosystem, while inheriting the historical transactions from Ethereum. Unfortunately, it is non-trivial to achieve this purpose due to the challenges in converting the EVM bytecode of smart contracts to WASM bytecode and adapting the generated WASM bytecode to the underlying blockchain environment. In particular, none of the existing tools are adequate for this task because they fail to achieve accurate translation and compatibility with the blockchain environment. In this paper, we propose a novel solution and use Eth2 as the target blockchain to demonstrate its feasibility and performance because Eth2 is highly attractive to both industry and academia. Specifically, we develop EVMBT, a novel EVM2WASM bytecode translation framework that not only ensures the fidelity of translation but also supports plugins to improve smart contracts. Extensive experiments demonstrate that EVMBT can successfully translate real-world smart contracts with high fidelity and low gas overhead.
Solana gained considerable attention as one of the most popular blockchain platforms for deploying decentralized applications. Compared to Ethereum, however, we observe a lack of research on how Solana smart contract developers handle security, what challenges they encounter, and how this affects the overall security of the ecosystem. To address this, we conducted the first comprehensive study on the Solana platform consisting of a 90-minute Solana smart contract code review task with 35 participants followed by interviews with a subset of seven participants. Our study shows, quite alarmingly, that none of the participants could detect all important security vulnerabilities in a code review task and that 83% of the participants are likely to release vulnerable smart contracts. Our study also sheds light on the root causes of developers' challenges with Solana smart contract development, suggesting the need for better security guidance and resources. In spite of these challenges, our automated analysis on currently deployed Solana smart contracts surprisingly suggests that the prevalence of vulnerabilities - especially those pointed out as the most challenging in our developer study - is below 0.3%. We explore the causes of this counter-intuitive resilience and show that frameworks, such as Anchor, are aiding Solana developers in deploying secure contracts.
Wenbing Zhao, Izdehar M. Aldyaflah, Zhaohua Zheng, Xiong Luo
We propose a novel blockchain-based academic degree verification system. The system relies on a smart contract deployed on the Ethereum blockchain platform. The system protects the privacy of the students who have been verified without the need of encryption, and hence, avoid the complexity of security key management and the potential disaster if the keys are stolen or revealed. The amount of degree data is also designed to be minimum for proper verification. All operations on the critical path of the system are automated without any human intervention. However, the system does assume that the organization would stand behind the proposed system to ensure the system's integrity. The system is open to anyone who wishes to verify the degree of a student. To prevent spamming and to support the long-term sustainability of the system, a small fee is charged for each verification request. A portion of the fees collected is immediately credited to the participating schools. To facilitate automated school enrollment into the system, any school may request to enroll by placing a significant amount of stake in ETH. The stake can be refunded when the school decides to leave the system. However, if the school is blacklisted due to misbehavior, the stake is confiscated. This design strongly discourages adversaries from abusing the system. The performance of the system is fully characterized with regard to the gas consumption of key operations in various use cases. We demonstrate that the system is conducive for long-term sustainability.
The rapid advancement of technology, alongside state-of-the-art techniques is at an all-time high. However, this unprecedented growth of technological prowess also brings forth potential threats, as oftentimes the security encompassing these technologies is imperfect. Particularly within the automobile industry, the recent strides in technology have brought about increased complexity. A notable flaw lies in the CAN-FD protocol, which lacks robust security measures, making it vulnerable to data theft, injection, replay, and flood data attacks. With the rising complexity of in-vehicular networks and the widespread adoption of CAN-FD, the imperative to safeguard the protocol has never been more crucial. This paper aims to provide a comprehensive review of the existing in-vehicle communication protocol, CAN-FD. It explores existing security approaches designed to fortify CAN-FD, demonstrating multiple multi-layer solutions that leverage modern techniques including Physical Unclonable Function (PUF), Elliptical Curve Cryptography (ECC), Ethereum Blockchain, and Smart contracts. The paper highlights existing multi-layer security measures that offer minimal overhead, optimal performance, and robust security. Moreover, it identifies areas where these security measures fall short and discusses ongoing research along with suggestions for implementing software and hardware-level modifications. These proposed changes aim to streamline complexity, reduce overhead while ensuring forward compatibility. In essence, the methods outlined in this study are poised to excel in real-world applications, offering robust protection for the evolving landscape of in-vehicular communication systems.
Enzo Nicourt, Benjamin Kushigian, Chandrakana Nandi, Ylìès Falcone
This paper presents a successful industrial case study on the application of mutation testing to evaluate and improve test suites for smart contracts. ERCx is a comprehensive, hand-written test suite and framework for smart contract testing, created by Runtime Verification. Despite its thoroughness, hand-written tests can miss edge cases. To address this, we employed mutation testing, which introduces small, syntactic changes, known as mutants, to the program. Mutants that go undetected by the test suite highlight its potential weaknesses, and by presenting them as testing goals, mutation testing helps developers iteratively improve their test suites. In this study, we used mutation testing to expand the ERCx test suite with five new test cases, including one potential vulnerability identified as critical by the ERCx developers. We also developed a test redundancy metric by analyzing pairwise correlation of test data on mutants; we used this redundancy metric to minimize the test suite by removing redundant tests. Finally, we ran both the full and minimized test suites on 106 real-world, faulty ERC-20 contracts to compare the suites' effectiveness and efficiency. Our findings reveal that although the minimized test suite has systematically lower running times compared to the full suite, it still detected faults in 105 of the 106 real-world tokens, retaining nearly all of the full suite's fault-detection capability.
Jan Lauinger, Serhat Bezmez, Jens Ernstberger, Sebastian Steinhorst
Latest identity systems rely on public blockchains to enhance user autonomy and reduce tracking from conventional identity providers. At the same time, identity systems integrate novel technologies such as zero-knowledge proofs (ZKPs) to improve data privacy and data compliance. We show that a naive verification of ZKPs at smart contracts enables replay attacks: Attackers can replay ZKPs at arbitrary times without having access to the private inputs that are required for the computation of the ZKP. To solve this problem, we construct a transaction sequence which verifies time-bound and replay-resistant ZKPs at smart contracts. Our construction introduces an additional but constant fee of 0.14${\$}$ per verification of a ZKP on the public blockchain Ethereum. With our new construction, we propose Portal, a novel identity system for decentralized single sign-on.
We present a simple approach to mitigate transaction-ordering dependent Maximum-Extractable-Value (MEV) opportunities in Ethereum. The approach is built on top of Proposer-Builder-Separation, restricts the freedom to order transactions within a block arbitrarily, and relies primarily on a non-malleable signature scheme and separation of responsibilities. In addition, we generalize the proposed approach to show that the property of unpredictable transaction arrangement can be transferred also to other blockchain systems. We discuss the gain in MEV mitigation, important limitations, and open issues.
This paper explores securing Non-Fungible Tokens (NFTs) within Ethereum's Decentralized Applications (DApps), crucial in the evolving blockchain landscape. NFTs represent a paradigm shift in digital asset ownership, but their innovation introduces security challenges. We navigate Ethereum-based NFT ecosystems, highlighting vulnerabilities like smart contract exploits and authentication issues. Emphasizing the need for proactive measures, we advocate for robust smart contract design, cryptographic protocols, decentralized identity management, and user education. Our objective is to empower the Ethereum community with a comprehensive roadmap for fortifying NFT transaction security, ensuring the integrity of digital ownership in the decentralized landscape. By addressing these challenges, we aim to contribute valuable insights to the discourse on securing blockchain innovations, fostering a safer environment for NFTs within Ethereum's DApps.
Blockchain is a distributed ledger technology that can provide trustworthy data services and robust support for secure data sharing. However, it faces the challenge of data privacy leakage during application, greatly limiting its scope and application areas. With the increasing volume of on-chain data, ensuring privacy protection during the blockchain data query process has become one of the key concerns for researchers. To address this issue, this paper proposes a framework called Trusted Execution Environment-based Blockchain Query Framework (TEEBQF). This framework loads blockchain query transactions based on smart contracts into a trusted execution environment, authenticates the trusted execution environment with relevant cryptographic techniques, and protects the confidentiality of query content, thereby achieving privacy protection during the data query process. Finally, the effectiveness of this framework is analyzed through performance evaluation, confirming its ability to provide robust support for privacy protection during blockchain data queries while achieving efficient and available queries, thus contributing to secure data sharing in blockchain environments.
This work focuses on utilising Physically Unclonable Functions (PUFs) for device authentication, exploiting a device's unique manufacturing-induced hardware variations. Traditional PUF-based authentication methods often rely on trusted third parties for validation or necessitate that Verifiers maintain large databases. Existing approaches that aim to reduce storage demands by reutilizing information typically address only networklevel threats, leading to doubts about the necessity of PUFs, or they focus exclusively on adversaries aiming at non-volatile memory. This paper introduces a classification guideline that delineates the scenarios in which PUFs are necessary or advantageous. Additionally, we present a novel PUF-based authentication scheme that incorporates challenge concealment to safeguard against comprehensive invasive physical attacks. This method offers perfect hiding, an enhanced level of security compared to previous models that permitted the reusing of PUF challenges. Through this approach, we aim to provide a more secure yet efficient framework for PUF-based authentication, addressing the limitations of current methodologies and extending the protection against a broader spectrum of adversaries.
Physical Unclonable Functions (PUFs) and Hardware Security
As a leading approach to improving the scalability of Ethereum, Rollup projects (e.g., Arbitrum) have proliferated in recent years, leading to an increased demand for cross-Rollup solutions. Unfortunately, existing cross-Rollup solutions are either slow and expensive or unsuitable for complex cross-Rollup interaction. We present ROLLUPNET, the first state channel that synchronously executes cross-Rollup contracts to support complex cross-Rollup applications while providing both security and efficiency guarantees. To prevent parties from misbehaving, we design an Ethereum-based dispute resolution to ensure the consistency of state between different Rollups. The results show that the ROLLUPNET is practical for Ethereum Rollups.
Miguel Isabel, Clara Rodríguez-Núñez, Albert Rubio
The application of Zero-Knowledge (ZK) proofs is rapidly growing in the industry and has become a key element to enable privacy and enhance scalability in public distributed ledgers. In most practical ZK systems, the statement to be proven is expressed by means of a set of polynomial equations in a prime field that describe an arithmetic circuit. Describing general statements using this kind of constraints is a complex and error-prone task. This can be partly mitigated by using high-level programming languages, but at the cost of losing control over the added constraints and, as a result, obtaining too large systems for complex statements. In this context, having tools to automatically verify properties of the constraint systems is of paramount importance to guarantee the security of the protocol. However, since non-linear polynomial reasoning over a finite field is needed for checking challenging properties, existing automatic tools either do not scale or cannot detect non-trivial bugs. In this paper, we present a new scalable modular technique based on the application of transformation and deduction rules that have proven to be very effective in verifying properties over the signals of a circuit given as a set of polynomial equations in a large prime field. Our technique has been implemented in a tool called CIVER and applied to verify safety properties for circuits implemented in circom, which is one of the most popular languages for defining ZK protocols. We have been able to analyze large industrial circuits and detect subtle vulnerabilities in circuits designed by expert programmers.
The rise of decentralized finance (DeFi), Web 3.0, and other blockchain-based applications has led to an increased demand for on-chain data analysis across multiple blockchains. Conducting advanced queries, such as data aggregation and correlation analysis, is essential for gaining valuable insights in this context. However, multi-chain queries pose several challenges for the querying system, including compatibility with existing blockchains, supporting diverse query types, and ensuring the integrity of query results. To tackle these challenges, we propose a novel paradigm called verifiable virtual filesystem (V2FS). V2FS extends the POSIX I/O interface, shifting the focus from verifying computation to verifying data. This innovative approach empowers query clients to leverage an off-the-shelf database engine to evaluate queries using verifiable data retrieved from an indexing service provider (ISP). Our solution ensures strong integrity guarantees and can be smoothly integrated with existing database engines to support various query types. To achieve blockchain compatibility, we utilize the DCert framework to certify blocks from different blockchains, making our system applicable to various blockchain systems. Furthermore, we propose cache-based algorithms and a bloom filter-integrated algorithm to optimize query performance and minimize network communication costs. Security analysis and empirical study validate the effectiveness and efficiency of the proposed system.
Decentralized finance (DeFi) protocols are crypto projects developed on the blockchain to manage digital assets. Attacks on DeFi have been frequent and have resulted in losses exceeding \$77 billion. However, detection methods for malicious DeFi events are still lacking. In this paper, we propose DeFiTail, the first framework that utilizes deep learning to detect access control and flash loan exploits that may occur on DeFi. Since the DeFi protocol events involve invocations with multi-account transactions, which requires execution path unification with different contracts. Moreover, to mitigate the impact of mistakes in Control Flow Graph (CFG) connections, we validate the data path by employing the symbolic execution stack. Furthermore, we feed the data paths through our model to achieve the inspection of DeFi protocols. Experimental results indicate that DeFiTail achieves the highest accuracy, with 98.39% in access control and 97.43% in flash loan exploits. DeFiTail also demonstrates an enhanced capability to detect malicious contracts, identifying 86.67% accuracy from the CVE dataset.
In the world of decentralized finance and smart contracts, the Ethereum blockchain stands as a pillar of innovation. However, with innovation comes the responsibility to fortify the systems against potential vulnerabilities. Reentrancy attacks pose a significant threat, exploiting vulnerabilities in the fabrication of smart contracts. These attacks can have severe consequences, compromising the integrity of transactions and jeopardizing the trust placed in blockchain technology. Many reentrancy solutions like yenta and ReVulDL have been implemented and various detection approaches have been proposed by various researchers. This paper proposed a “Hybrid Locking” mechanism to prevent Ethereum reentrancy which involves the combination of dynamic mutex locks and hierarchical locking which is lacking yet in research. This represents an innovative security enhancement for smart contracts by leveraging the proven concepts from concurrency control; establishing a multi-layered defense against reentrancy attacks, and addressing vulnerabilities that led to financial losses. This compelling solution press security issue in decentralized finance and proposed Hybrid Locking Mechanism shows promise, further empirical validation, and considerations for practical implementation which strengthen its contribution to the field of blockchain using context-aware defense mechanism against reentrancy attacks. The Hybrid Locking Mechanism demonstrated a 24.14% increase in effectiveness in preventing re-entrance compared to the average effectiveness of other approaches.