The rapid rise of blockchains and “Web3” has sparked significant interest in designing and implementing distributed systems for untrusted environments. However, due to their rigid one-size-fits-all design, current systems fail to adapt to dynamic workloads, new hardware setup, and different user intentions. To address this problem, we examine the systems stack in a top-down layered manner, from transaction management, Byzantine fault-tolerant (BFT) consensus to their underlying infrastructure. We propose i) AdaChain, the first learned system that adaptively manages blockchain transactions, ii) BFTBrain, a multi-protocol BFT consensus engine that dynamically adjusts itself using reinforcement learning, and iii) FlexChain, a flexible disaggregated infrastructure tailored for permissioned blockchains. AdaChain addresses the challenge in transaction execution under dynamic workloads. As a system driven by reinforcement learning, AdaChain adaptively selects the optimal transactional architecture for dynamic workloads, maximizing throughput. AdaChain securely switches architectures at runtime when a better option is identified. Experiments show AdaChain quickly converges to optimal setups, significantly outperforming fixed architectures in committed transactions with minimal overhead. BFTBrain is a practical reinforcement learning based BFT consensus that provides significant operational benefits: a plug-and-play system suitable for a broad set of hardware and network configurations, and adjusts effectively in real-time to changing fault scenarios and workloads. BFTBrain’s key innovations include systematic performance modeling to guide protocol selection and decentralized learning resilient to adversarial data pollution. As a result, in addition to providing significant operational benefits, BFTBrain improves throughput over fixed protocols by 18% to 119% under dynamic conditions and outperforms state-of-the-art learning based approaches by 44% to 154%. FlexChain is a novel infrastructure layer for permissioned blockchains that physically disaggregates CPUs, DRAM, and storage devices to process different blockchain workloads efficiently. Disaggregation enables independent scaling of hardware resources, improving utilization and preventing fragmentation. Our evaluation results show that FlexChain can provide independent compute and memory scalability, while incurring at most 12.8% disaggregation overhead. FlexChain achieves almost identical throughput as the state-of-the-art distributed approaches with significantly lower memory and CPU consumption for compute-intensive and memory-intensive workloads respectively.
Smart contracts are computer programs running on blockchains to automate the transaction execution between users. The absence of contract specifications poses a real challenge to the correctness verification of smart contracts. Program invariants are properties that are always preserved throughout the execution, which characterize an important aspect of the program behaviors. In this paper, we propose a novel invariant generation framework, INVCON+, for Solidity smart contracts. INVCON+ extends the existing invariant detector, InvCon, to automatically produce verified contract invariants based on both dynamic inference and static verification. Unlike INVCON+, InvCon only produces likely invariants, which have a high probability to hold, yet are still not verified against the contract code. Particularly, INVCON+ is able to infer more expressive invariants that capture richer semantic relations of contract code. We evaluate INVCON+ on 361 ERC20 and 10 ERC721 real-world contracts, as well as common ERC20 vulnerability benchmarks. The experimental results indicate that INVCON+ efficiently produces high-quality invariant specifications, achieving a recall of 80%, which can be used to secure smart contracts from 17 types of common vulnerabilities.
With the rapid development of blockchain technology over the last decades, cryptocurrencies have become a focal point in both the technological and financial realms. Following the elegant approach to achieving permissionless consensus of Bitcoin, researchers have dedicated efforts to finding alternative solutions that do not rely on energy-intensive Proof-of-Work (PoW). Ethereum, as the second largest cryptocurrency, has recently transitioned its consensus protocol from PoW to a more energy-efficient approach using Proof-of-Stake (PoS). This construction, named Gasper, has a composite feature that aims to retain the benefit of both open blockchain as well as fast confirmation. However, the security of Gasper is not sufficiently proven and it is still unclear whether Gasper actually achieved its goal. To understand the potential vulnerabilities of Ethereum in the real-world internet, we take a closer look at the working mechanism of Ethereum 2.0 and identify three potential vulnerabilities of Gasper's accountable safety property. Firstly, we illustrate a scenario where a coin can be double-spent while executing the Gasper protocol under a partially synchronous network, and no accountability is established before or after this safety breach. Secondly, we demonstrate a strategy that renders accountability ineffective in a partially synchronous network. Thirdly, we present a method to evade punishment even after a safety breach. Inspired by Gasper, the ebb-and-flow structure mirrors this composite construction by combining a longest-chain style protocol and a BFT protocol in a provably secure manner. However, the construction exhibits limitations in terms of flexibility and liveness in certain scenarios. Thus, we introduce a flexible ebb-and-flow structure that not only preserves dynamic availability but also addresses liveness issues, enhances the corruption resilience of ebb-and-flow protocols, and achieves confirmation diversity.
Samson Kahsay Gebresilassie, Joseph Rafferty, Mamun Abu-Tair, Aftab Ali · 6 authors
The Internet of Things (IoT) is a technology paradigm that has transformed several domains including manufacturing, agriculture, healthcare, power grids, travel, and retail. Despite the enormous advantages that IoT offers to organizations and transforming individuals’ everyday lives in a wide range of domains, it comes with potential cyber risks that can negatively impact, harm, or damage them. Security is the most challenging issue in IoT systems due to insecure devices, inadequate IDMS, lack of data security and privacy, lack of trust, lack of risk analysis on network traffic, various vulnerabilities and attacks, lack of physical security, and many other risk factors. Although several security architectures have been developed, they fail to properly and fully address these IoT security challenges and an urgent demand awaits for a robust IoT security architecture. Thus, this work investigates state-of-the-art solutions and proposes a holistic novel IoT security architecture called SHIELD: Secure Holistic IoT Environment with Ledger-based Defense with core security capabilities of decentralized Identity Management System (IDMS), Network Traffic Monitoring, Analysis, and dataset generation, deep learning-based Intrusion Detection System (IDS), and Distributed Ledger Technology (DLT)-based Trust Management System (TMS). The proposed architecture is qualitatively compared with existing solutions using key features like a single point of failure, risk/attack-aware, trust, real-time traffic behavior monitoring, up-to-date dataset, cross-platform functionality, and availability among others. As a result of this comparison, SHIELD architecture provides a holistic and robust solution with multiple core security features to overcome some of the key security challenges IoT environment.
Abstract Blockchains are decentralized systems that provide trustable execution guarantees through the use of programs called smart contracts. Smart contracts are programs written in domain-specific programming languages running on blockchains that govern how tokens and cryptocurrency are sent and received. Smart contracts can invoke other smart contracts during the execution of transactions initiated by external users. Once deployed, smart contracts running code cannot be modified, so techniques like runtime verification are very appealing for improving their reliability. Moreover, the conventional model of computation of smart contracts is transactional: once operations commit, their effects are permanent and cannot be undone. Therefore, errors in smart contracts may lead to millionaire losses of money. In this paper, we present the concept of future monitors which allows monitors to remain waiting for future transactions to occur before committing or aborting. This is inspired by optimistic rollups, which are modern blockchain implementations that increase efficiency (and reduce cost) by delaying transaction effects. We exploit this delay to propose a model of computation that allows bounded future monitors. We show our monitors correct respect with legacy transactions, how they implement bounded future monitors and how they guarantee progress. We illustrate the use of bounded future monitors by implementing correctly multi-transaction flash loans.
Hamra Afzaal, Nazir Ahmad Zafar, Aqsa Tehseen, Shaheen Kousar · 5 authors
In recent years, Beacon Chain known as the core of Ethereum 2.0, has gained considerable attention since its launch. Many validators have staked billions of Ether in the Proof of Stake (PoS) network. It is a mission critical system and its security and stability rely on the justification and finalization of checkpoints. These are essential elements of the Casper FFG consensus algorithm utilized by the Beacon Chain. This process is critical for establishing a trustworthy foundation and finalizing proposed blocks by confirming agreed upon checkpoints. Hence, ensuring the correctness of checkpoints in the Beacon Chain has significant importance because any bug in it can cause serious implications. To address this challenge, we employ formal methods, a popular mathematical approach used for verifying the correctness of such critical systems. In this work, we have done formal verification of the processes of Beacon Chain state initialization, justification and finalization of checkpoints using the Process Analysis Toolkit (PAT) model checker. The adoption of model checking through the PAT model checker presents a novel contribution of our work, as this approach is not previously utilized in the formal verification of Beacon Chain. The presented work is specified through the Communicating Sequential Programs, formal specification language, and the properties are described through Linear Temporal Logic. The PAT model checker takes the specified formal model and properties as input to assess whether the properties are satisfied. The properties are analyzed with respect to the verification time, visited states, total transitions, and memory used. Through this research, we aim to increase confidence in the correctness and reliability of the Beacon Chain.
Pradeep Gupta, Nusrat Nigar, Roma Paswan, Rajat Kumar Singh · 5 authors
The advent of non-fungible tokens (NFTs) has revolutionized the digital landscape, providing creators and brands with unprecedented avenues to engage their communities and explore innovative monetization methods. Beyond their origins in digital art and collectibles, NFTs have catalyzed diverse applications, reshaping the way digital assets are perceived and utilized. One such innovation is the concept of NFT-gated websites, which has gained substantial momentum. These platforms facilitate community engagement by granting exclusive access to content and experiences, all while generating new revenue streams. NFT-gated websites operate by mandating users to connect their crypto wallets and prove ownership of specific NFTs or crypto tokens, thereby creating a unique layer of restricted access. This novel approach empowers creators and brands to nurture exclusive communities and deliver distinct experiences to their audience. In the rapidly evolving Web3 ecosystem, this transformative technology stands poised to redefine digital interactions, enabling creators and brands to thrive in this new era.
This paper presents a trustworthy architecture for Web3 service that establishes self-sovereign services. This architecture leverages decentralized identifiers (DID) and resource access control based on user trust scores and policies. By transitioning from centrally managed ID to DID, it will be possible to move towards ID management that does not rely on service providers. Trust scores are calculated by analyzing the social network generated from the history of past transactions between users stored in the blockchain. The degree of trust is quantified using measures of centrality and similarity. Centrality is measured by the number of user achievements and the extent of their connections. Similarity is calculated by estimating the communities they belong to using node embedding. These trust scores are clustered to generate policy based on role-based access control (RBAC). The authorization function is programmatically realized based on user credibility by comparing the results of the distribution of accessible resources by policy. In addition, a Web3 service broker acts as an intermediary between multiple service providers and users to provide optimal services through smart contracts. A Web3 service broker programmatically select services without intermediary agencies. A trustworthy architecture for Web3 service is shown as a case study of a home delivery service. In this scenario, Web3 service brokers offer optimal services for private companies and small and medium-sized businesses. This paper is an extended version of ”A Web3 Service Architecture with Self-Sovereign Identity” presented at iDECON/MS2023.
Marisol García‐Valls, Alejandro M. Chirivella-Ciruelos
The lack of sufficient guarantee about the authenticity of running smart contracts is a major entry barrier to blockchain networks. By authenticity,we refer to the smart contract ownership or provenance; this implies perfect matching between a published source-code and the corresponding running version of a given smart contract. Block verifiers are services that check the provenance authenticity of the logic contained in blockchain networks. Nevertheless, as a block verifier is an external verification service, it consumes time to use it; and the derived overhead may not comply with temporal requirements of time-sensitive domains like cyber-physical systems. Such systems require that the temporal cost of using external services is assessed prior to the final system deployment. To the best of our knowledge, there are no previous contributions on the determination of the temporal cost of the smart-contract provenance verification process. This paper presents the design and implementation of a middleware that assesses the temporal overhead of accessing the verification services; the middleware is hosted in the global ledger and runs the verification services over large sets of smart contracts. Our contribution is validated by providing an implementation on a real blockchain network, employing actual smart contract verifier logic, and analysing the temporal behavior of the overall system operations to comply with the time-sensitive requirements of cyber-physical systems.
The unstoppably increasing number of the Internet of Things (IoT), autonomous agents, and massive distributed web ecosystems have made data acquisition a complicated, risk-prone, and a very sensitive process. Regulation Web data collection is a fixed pipeline that is strictly regulated by established rules and legal limits, and reactive policy audits to operate in traditional forms of governance. Nevertheless, the contemporary digital ecosystem requires a decentralized system of governance that could identify unpredictable streams of data, the shifting web framework, loosely distributed computing individuals, and shifting conditions of regulation. This paper will present Governance-of-Things (GoT), an emerging conceptual and architectural design that will address these issues and show how to smoothly integrate ethical intelligence, regulatory and laws compliance, semantic awareness, and integrity assurance within autonomous systems of web data acquisition. GoT suggests a view where governance follows a first-class computation i.e. embedded, adaptive, intelligent and context-aware. In contrast to traditional approaches of governing IoT, GoT regards any acquisition agent as ethics-regulated, compliance-aware, and self-regulating. Agents do not simply pull information, they negotiate access rights, authenticate provenance, reason about risk, and implement multi-jurisdictional policies all by themselves. The framework combines dynamic enforcement of policies, federated governance, semantic classification pipelines, AI-enhanced agent frameworks built on Java and distributed analytics to create an ecosystem, producing an automated acquisition that is compatible with responsible, transparent, and audit-friendly behaviours. Fairness, legality, transparency, explainability and accountability are the principles of ethical autonomy which are expounded in the paper. GoT has the aspect of federated ethical rule orchestration where the governance layers among organizations in various stakeholders share without necessarily providing the raw information. The system incorporates automation using structural integrity that guarantees cryptographic validation and review trails that are not tampered with. The given adaptive monitoring model promotes the constant policy updating, data flows redirection and the detection of threats. Furthermore, GoT involves semantic intelligence so that data classification, contextual labeling, entity recognition, and domain mapping take place before storing or processing data- therein avoiding compliance violation at its early phases. GoT architecturally has a multi-layer stack that is organized and includes Perception Layer, Autonomous Agent Layer, Governance Core, Distributed Analytics Layer, and Compliance Ledger Layer. The primitives of computational governance are embedded in each layer, making it highly modular and allowing run-time updates of rules and cooperating across agents. Java frameworks boosted with AI facilitate interoperability with legacy enterprise systems and with current base systems. Using experimental simulation, it was found that GoT enhances compliance accuracy, governance throughput, policy adaptation latency and decision explainability on varying scenarios of acquisitions. This article is in the pre-2021 academic style, has extensive literature review, methodological description, architectural schematics, theoretical framework, and profound results discussion. It ends by establishing GoT as an innovative paradigm which is able to influence the future of web data governance, autonomous systems, and distributed analytics
Rafael Belchior, Dimo Dimov, Zahary Karadjov, Jonas Pfannschmidt · 6 authors
The field of blockchain interoperability plays a pivotal role in blockchain adoption. Despite these advances, a notorious problem persists: the high number and success rate of attacks on blockchain bridges. We propose Harmonia, a framework for building robust, secure, efficient, and decentralized cross-chain applications. A main component of Harmonia is DendrETH, a decentralized and efficient zero-knowledge proof-based light client. DendrETH mitigates security problems by lowering the attack surface by relying on the properties of zero-knowledge proofs. The DendrETH instance of this paper is an improvement of Ethereum’s light client sync protocol that fixes critical security flaws. This light client protocol is implemented as a smart contract, allowing blockchains to read the state of the source blockchain in a trust-minimized way. Harmonia and DendrETH support several cross-chain use cases, such as secure cross-blockchain bridges (asset transfers) and smart contract migrations (data transfers), without a trusted operator. We implemented Harmonia in 9K lines of code. Our implementation is compatible with the Ethereum Virtual Machine (EVM) based chains and some non-EVM chains. Our experimental evaluation shows that Harmonia can generate light client updates with reasonable latency, costs (a dozen to a few thousand US dollars per year), and minimal storage requirements (around 4.5 MB per year). We also carried out experiments to evaluate the security of DendrETH. We provide an open-source implementation and reproducible environment for researchers and practitioners to replicate our results.
Sundas Munir, Mirza Sanam Iqbal Baig, Mah Noor, Syeda Hina Murad
Smart contracts, running on blockchains, enable transparent interactions without intermediaries. However, program-related bugs and flaws in translating business logic into code can introduce vulnerabilities, making them attractive targets for malicious users. For instance, using input from untrusted users in critical operations without proper validation may lead to exploitable functionalities. We refer to this vulnerability as Missing Input Validation (MIV). This paper focuses on the issues caused by MIV (aka MIV-related issues) in Solidity smart contracts executing on the Ethereum blockchain. In particular, we conduct a case study emphasizing how MIV-related issues can lead to unexpected behavior in smart contracts, rendering them vulnerable to malicious manipulation. We also implement an information flow analysis-based analyzer, MIV-Checker, to statically detect instances of MIV in Solidity smart contracts. We evaluated MIV-Checker against a state-of-the-art smart contract analysis tool, Securify, using 3399 distinct contracts collected from the Ethereum blockchain. Securify identified only three contracts, whereas MIV-Checker detected 86 contracts as potentially susceptible to MIV. Our manual assessment confirms that MIV-Checker outperforms Securify by detecting more true MIV cases and reducing execution time. This case study helps determine that many recently used contracts on Ethereum may still be potentially vulnerable to MIV. Additionally, we position user-provided input as a non-deterministic factor in Ethereum contract execution and discuss future research avenues for mitigating issues arising from such factors.
This paper extends the previous paper [6] by implementing two blockchain simulators of Solidity-style smart contracts – a simple and a complex one, using the interactive theorem prover Agda. In the previous article [6], we built a simple and complex abstract model of Solidity-style smart contracts in Agda. These models had many features, such as calling different smart contracts, supporting the ability to call different smart contracts, and providing simple and complex instructions. Because of the use of coalgebras for representing smart contracts they supported loops and conditionals, using the support of those features for coalgebraic programs in Agda. The complex model supported gas costs and pure functions, similar to the Solidity language.
Abu Taher Md Shifat, Md. Ahsan Habib, Shahid Hasan, Avishek Roy
Distributed Ledger Technologies (DLT), notably blockchain, have advanced significantly, finding applications in various domains, including education, for enhanced transparency and accountability. The utilization of hash functions and public-key cryptography (e.g., ECDSA and RSA) in blockchain ensures these attributes. However, the rapid progress in quantum computing has unveiled vulnerabilities in classical public-key cryptography, necessitating a reassessment of blockchain architecture for quantum resistance. This article explores diverse blockchain architectures in education, evaluating their susceptibility to quantum attacks. It introduces QEdu, a consortium blockchain framework securing educational credentials using quantum-safe Elgamal-Like public-key cryptography based on matrices over grouping. Comparative analysis with existing works underscores the efficacy of the proposed framework.
Kai Ma, Jintao Huang, Ningyu He, Zhuo Wang · 5 authors
Non-fungible tokens (NFTs) drive the prosperity of the Web3 ecosystem. By November 2023, the total market value of NFT projects reached approximately 16 billion USD. Accompanying the success of NFTs are various security issues, i.e., attacks and scams are prevalent in the ecosystem. While NFTs have attracted significant attentions from both industry and academia, there is a lack of understanding of kinds of NFT security issues. The discovery, in-depth analysis, and systematic categorization of these security issues are of significant importance for the prosperous development of the NFT ecosystem. To fill the gap, we performed a systematic literature review related to NFT security, and we have identified 142 incidents from 213 security reports and 18 academic papers until October 1st, 2023. Through manual analysis of the compiled security incidents, we have classified them into 12 major categories. Then we explored potential solutions and mitigation strategies. Drawing from these analyses, we established the first NFT security reference frame. Except, we extracted the characteristics of NFT security issues, i.e., the prevalence, severity, and intractability. We have indicated the gap between industry and academy for NFT security, and provide further research directions for the community. This paper, as the first SoK of NFT security, has systematically explored the security issues within the NFT ecosystem, shedding light on their root causes, real-world attacks, and potential ways to address them. Our findings will contribute to the future research of NFT security.
Soosan Naderi Mighan, Jelena Mišić, Vojislav B. Mišić, Xiaolin Chang
In this paper, we analyze the performance of Ethereum data distribution network using a probabilistic model which allows accurate modeling of data propagation. We then apply the model to analyze the performance of data propagation in Ethereum when using geth protocol under block withholding attack, Eclipse attack, and block slowdown attack. We also propose countermeasures for the block withholding attack and Eclipse attack.
If tokenized assets are to be a reality in the future decentralized Web3 then transaction keys need to be distributed and under the control of the asset-owners. This requires a careful design of wallet systems based on trusted hardware. A core feature needed for wallet systems is the attestation of the state of the transaction keys in the wallet without disclosure of the keys. This feature is relevant for relying parties such as insurance providers who need to perform risk assessment based on the security quality of the environment inside the wallet system that is protecting the transaction keys. In the longer term, all key-bearing devices that participate in a decentralized tokenized asset network will need to be hardened using trusted hardware, with attestation capabilities for detecting and countering cyberattacks.
Michael Eckel, Dominik Roy George, Björn Grohmann, Christoph Krauß
Trusted Platform Modules (TPMs) are used for remote attestation to ensure the authenticity and integrity of software running on a computer system. However, measuring software executed as containers or virtual machines can be challenging as it is measured concurrently, resulting in a jumbled measurement log that is difficult to disentangle. Moreover, disclosing the entire measurement log in traditional binary remote attestation raises privacy and intellectual property concerns. To address these issues, we propose a remote attestation method with constrained disclosure, allowing for selective disclosure of entries in the measurement log using a non-interactive zero-knowledge (NIZK) proof with Schnorr signatures. Our approach is evaluated for security and privacy and proven to be correct, sound, and satisfies the properties of a NIZK proof. Formal verification of our solution with ProVerif also supports our claims. Furthermore, the performance evaluation of our proof-of-concept implementation shows that our contribution is feasible, and the overhead introduced is negligible.
Kunsong Zhao, Zihao Li, Jianfeng Li, He Ye · 6 authors
Smart contracts play an increasingly important role in Ethereum platform. It provides various functions implementing numerous services, whose bytecode runs on Ethereum Virtual Machine. To use services by invoking corresponding functions, the callers need to know the function signatures. Moreover, such signatures provide crucial information for many downstream applications, e.g., identifying smart contracts, fuzzing, detecting vulnerabilities, etc. However, it is challenging to infer function signatures from the bytecode due to a lack of type information. Existing work solving this problem depended heavily on limited databases or hard-coded heuristic patterns. However, these approaches are hard to be adapted to semantic differences in distinct languages and various compiler versions when developing smart contracts. In this paper, we propose a novel framework DeepInfer that first leverages deep learning techniques to automatically infer function signatures and returns. The novelties of DeepInfer are: 1) DeepInfer lifts the bytecode into the Intermediate Representation (IR) to preserve code semantics; 2) DeepInfer extracts the type-related knowledge (e.g., critical data flows, constant values, and control flow graphs) from the IR to recover function signatures and returns. We conduct experiments on Solidity and Vyper smart contracts and the results show that DeepInfer performs faster and more accurate than existing tools, while being immune to changes in different languages and various compiler versions.