Machine learning has become increasingly popular in academic and industrial communities and has been widely implemented in various online applications due to its powerful ability to analyze and use data. Among all the machine learning models, decision tree models stand out due to their great interpretability and simplicity, and have been implemented in cloud computing services for various purposes. Despite its great success, the integrity issue of online decision tree prediction is a growing concern. The correctness and consistency of decision tree predictions in cloud computing systems need more security guarantees since verifying the correctness of the model prediction remains challenging. Meanwhile, blockchain has a promising prospect in two-party machine learning services as the immutable and traceable characteristics satisfy the verifiable settings in machine learning services. In this paper, we initiate the study of decision tree prediction services on blockchain systems and propose VDT, a Verifiable Decision Tree prediction scheme for decision tree prediction. Specifically, by leveraging the Merkle tree and hash function, the scheme allows the service provider to generate a verification proof to convince the client that the output of the decision tree prediction is correctly computed on a particular data sample. It is further extended to an update method for a verifiable decision tree to modify the decision tree model efficiently. We prove the security of the proposed VDT schemes and evaluate their performance using real datasets. Experimental evaluations show that our scheme requires less than one second to produce verifiable proof.
Federated Learning (FL) has emerged as a privacy-preserving distributed Machine Learning paradigm, which collaboratively trains a shared global model across a number of end devices (clients) without exposing their raw data. However, FL typically assumes that all clients are benign and trust the coordinating central server, which is unrealistic for many real-world scenarios. In practice, clients can harm the FL process by sharing poisonous model updates while the server could malfunction or misbehave. Moreover, the deployment of FL for real-world applications is hindered by the high communication overhead between the server and clients that are often at the network edge with limited bandwidth. To address these key challenges, we propose a lightweight Blockchain-Empowered secure and efficient Federated Learning (BEFL) system. BEFL is built by integrating a communication-efficient and mutual-information guarded training scheme, a cost-effective Verifiable Random Function (VRF)-based consensus mechanism, and Inter-Planetary File System (IPFS)-enabled scalable blockchain architecture. Extensive simulation experiments using two benchmark FL datasets demonstrate that BEFL is resistant against byzantine clients launching data poisoning and model poisoning attacks, fault-tolerant against colluded malicious blockchain nodes, scalable to a large number of blockchain nodes, and communication-efficient at the network edge.
Secure data deletion enables data owners to have full control over the erasure of their data stored on local or cloud data centers, and it is essential for preventing data leakage, especially in cloud storage. However, traditional data deletion methods based on unlinking, overwriting, and cryptographic key management are either ineffective in cloud storage or rely on impractical assumptions. In this paper, we introduce SevDel, a secure and verifiable data deletion scheme that utilizes zero-knowledge proofs to achieve verification of the encryption of outsourced data without retrieving the ciphertexts. Meanwhile, the deletion of encryption keys is guaranteed based on Intel SGX. SevDel implements secure interfaces for performing data encryption and decryption in secure cloud storage. It also utilizes smart contracts to enforce the operations of the cloud service provider, ensuring compliance with service level agreements with data owners and imposing penalties on the service provider for disclosing cloud data on its servers. Evaluation using real-world workloads demonstrates that SevDel efficiently achieves data deletion verification and maintains high bandwidth savings.
Training contemporary AI models requires investment in procuring learning data and computing resources, making the models intellectual property of the owners. Popular model watermarking solutions rely on key input triggers for detection; the keys have to be kept private to prevent discovery, forging, and removal of the hidden signatures. We present ZKROWNN, the first automated end-to-end framework utilizing Zero-Knowledge Proofs (ZKP) that enable an entity to validate their ownership of a model, while preserving the privacy of the watermarks. ZKROWNN permits a third party client to verify model ownership in less than a second, requiring as little as a few KBs of communication.
Jens Hunhevicz, David F. Bucher, Ranjith K. Soman, Meliha Honic · 6 authors
Long-term access to lifecycle data is key to a successful transition towards a circular built environment. However, the underlying technology often remains centralized and risks becoming inaccessible over time. In this paper, we investigate whether decentralized access methods using Web3, i.e. blockchain and decentralized data storage protocols, can help to mitigate this limitation. We implement Web3 data access mechanisms for a material passport with both a role-based and a token-based smart contract. Initial results suggest that Web3 offers a promising approach to data access over the lifecycle of a built asset - but only with careful design choices.
Orestis Alpos, Ignacio Amores-Sesar, Christian Cachin, Michelle Yeo
Traditional blockchains grant the miner of a block full control not only over which transactions but also their order. This constitutes a major flaw discovered with the introduction of decentralized finance and allows miners to perform MEV attacks. In this paper, we address the issue of sandwich attacks by providing a construction that takes as input a blockchain protocol and outputs a new blockchain protocol with the same security but in which sandwich attacks are not profitable. Furthermore, our protocol is fully decentralized with no trusted third parties or heavy cryptography primitives and carries a linear increase in latency and minimum computation overhead.
Laasya Bangalore, Mohammad Hossein Faghihi Sereshgi, Carmit Hazay, Muthuramakrishnan Venkitasubramaniam
In this work, we introduce a lightweight secure aggregation protocol that guarantees liveness (i.e., guaranteed output delivery), robust against faulty inputs and security against malicious clients. First, we improve upon prior works in the “star”-like topology network with a central coordinating (also output) party, Bonawitz et al. (ACM CCS 2017) and Bell et al. (ACM CCS 2020), which are not robust against faulty inputs. Recent works, RoFL (Burkhalter et al.) and (concurrent work) ACORN (Bell et al.) show how to rely on zero-knowledge proofs to address such attacks at expense of significantly high computation costs. We also compare our protocol against the PRIO system by Gibbs and Boneh (USENIX 2017) which achieves the same task in an incomparable security model. We benchmark our protocol with implementation and demonstrate its concrete efficiency. Our solution scales to 1000s of clients, requires only a constant number of rounds, outperforms prior work in computational cost, and has competitive communication cost.
Muhammed F. Esgin, Oğuzhan Ersoy, Veronika Kuchta, Julian Loss · 8 authors
In this work, we study the blockchain leader election problem. The purpose of such protocols is to elect a leader who decides on the next block to be appended to the blockchain, for each block proposal round. Solutions to this problem are vital for the security of blockchain systems. We introduce an efficient blockchain leader election method with security based solely on standard assumptions for cryptographic hash functions (rather than public-key cryptographic assumptions) and that does not involve a racing condition as in Proof-of-Work based approaches. Thanks to the former feature, our solution provides the highest confidence in security, even in the post-quantum era. A particularly scalable application of our solution is in the Proof-of-Stake setting, and we investigate our solution in the Algorand blockchain system. We believe our leader election approach can be easily adapted to a range of other blockchain settings.
Shared code in blockchains, known as smart contracts , stands to replace important parts of our digital governance and financial infrastructure. The permissionless execution of smart contracts is tightly coupled to cryptocurrencies and Proof-of-Work blockchains. As a result, smart contracts inherit the environmental impact of Proof-of-Work blockchains, such as its energy consumption, carbon footprint, and electronic waste. The four concepts of relaxed consistency, strong identities, probabilistic consensus, and the use of liabilities instead of assets may change the status quo. This work explores the integration of these concepts to decouple smart contracts from Proof-of-Work blockchains. By means of a local-first approach, which may expose users to inconsistent ephemeral contract states, the architecture of smart contracts can be transformed to become green. Because such contract states may be dropped, we base the interactions between users on liabilities. We propose a novel paradigm for smart contract architectures, named Green Smart Contracts, that is based on a local-first approach. Furthermore, we present and implement a prototype solution for this paradigm. We validate the need for a mechanism to resolve consistency violations by replaying the contract calls of a real smart contract. Our simulation shows that violations occur more often (13% of contract invocations) when using liabilities than when using a traditional blockchain (3% of contract invocations). However, we additionally validate that they can be avoided using a consensus mechanism, and our experiments show that a publish-subscribe messaging pattern uses the fewest messages to do so, though it may not be applicable for use cases that disallow the inherent imbalance in the messaging between peers. Our carbon emission estimation shows that a Green Smart Contract approach lowers carbon emissions by 52.31% when compared with the messaging behavior of a typical peer-to-peer blockchain with 1000 nodes.
The exponential growth in connected devices with Internet-of-Things (IoT) and next-generation wireless networks requires more advanced and dynamic spectrum access mechanisms. Blockchain-based approaches to Dynamic Spectrum Access (DSA) seem efficient and robust due to their inherited characteristics such as decentralization, immutability, and transparency. However, conventional consensus mechanisms used in blockchain networks are expensive to be used due to the cost, processing, and energy constraints. Moreover, addressing spectrum violations (i.e., unauthorized access to the spectrum) is not well-discussed in most blockchain-based DSA systems in the literature. In this work, we propose a newly tailored energy-efficient consensus mechanism called “Distributed-Proof-of-Sense (DPoS)” that is specially designed to enable DSA and detect spectrum violations. The proposed consensus algorithm motivates blockchain miners to perform spectrum sensing, which leads to the collection of a full spectrum of sensing data. An elliptic curve cryptography-based zero-knowledge proof is used as the core of the proposed mechanism. We use MATLAB simulations to analyze the performance of the consensus mechanism and implement several consensus algorithms in a microprocessor to highlight the benefits of adopting the proposed system.
In the era of deep learning, federated learning (FL) presents a promising approach that allows multi-institutional data owners, or clients, to collaboratively train machine learning models without compromising data privacy. However, most existing FL approaches rely on a centralized server for global model aggregation, leading to a single point of failure. This makes the system vulnerable to malicious attacks when dealing with dishonest clients. In this work, we address this problem by proposing a secure and reliable FL system based on blockchain and distributed ledger technology. Our system incorporates a peer-to-peer voting mechanism and a reward-and-slash mechanism, which are powered by on-chain smart contracts, to detect and deter malicious behaviors. Both theoretical and empirical analyses are presented to demonstrate the effectiveness of the proposed approach, showing that our framework is robust against malicious client-side behaviors.
We propose a middleware solution designed to facilitate seamless integration of privacy using zero-knowledge proofs within various multi-chain protocols, encompassing domains such as DeFi, gaming, social networks, DAOs, e-commerce, and the metaverse. Our design achieves two divergent goals. zkFi aims to preserve consumer privacy while achieving regulation compliance through zero-knowledge proofs. These ends are simultaneously achievable. zkFi protocol is designed to function as a plug-and-play solution, offering developers the flexibility to handle transactional assets while abstracting away the complexities associated with zero-knowledge proofs. Notably, specific expertise in zero-knowledge proofs (ZKP) is optional, attributed to zkFi's modular approach and software development kit (SDK) availability.
Maurantonio Caprolu, Elmahdi Bentafat, Spiridon Bakiras, Roberto Di Pietro
In this paper we propose UBIC, a novel blockchain-less architecture that preserves the main advantages of classic cryptocurrencies while avoiding their pitfalls. The proposed construction is general-that is, UBIC can be adopted at par with any other cryptocurrency-though UBIC also satisfies the requirements to support state-sponsored financial services, like Universal Basic Income and Central Bank Digital Currency. Indeed, UBIC stands for Universal Basic Income Coin, to highlight one of its most straightforward use-cases. One of the key features of UBIC is that every user participating in the protocol gets fair and equal access to the rewards, regardless of the available resources, e.g., computational power or financial stake. Moreover, by leveraging standard cryptographic techniques, such as homomorphic encryption and verifiable random functions, UBIC ensures full user privacy and trust in the network, while enjoying a highly scalable architecture. Our experimental results confirm the feasibility of the proposed architecture and demonstrate that UBIC is very efficient in terms of transaction verification time. To the best of our knowledge, this is the first blockchain-less cryptocurrency proposal. Other than being interesting on its own, and being particularly fit to support UBI and Central Bank Digital Currency, the architectural solutions and the technical choices discussed in this contribution have the potential to generate high impact and further research in the field.
Open access
Blockchain Technology Applications and Security
Cryptography and Data Security
Advanced Steganography and Watermarking Techniques
Aggelos Kiayias, Cristopher Moore, Saad Quader, Alexander Russell
We describe and analyze a simple protocol for$n$parties that implements a randomness beacon: a sequence of high entropy values, continuously emitted at regular intervals, with sub-linear communication per value. The algorithm can tolerate a$(1-\epsilon)/2$fraction of the$n$players to be controlled by an adaptive adversary that may deviate arbitrarily from the protocol. The randomness mechanism relies on verifiable random functions (VRF), modeled as random functions, and effectively stretches an initial$\lambda$-bit seed to an arbitrarily long public sequence so that (i) with overwhelming probability in k-the security parameter-each beacon value has high min-entropy conditioned on the full history of the algorithm, and (ii) the total work and communication required per value is$O(k)$cryptographic operations. The protocol can be directly applied to provide a qualitative improvement in the security of several proof-of-stake blockchain algorithms, rendering them safe from “grinding” attacks.
Open access
Blockchain Technology Applications and Security
Cryptography and Data Security
Advanced Steganography and Watermarking Techniques
One of the most important features of blockchain protocols is decentralization, as their main contribution is that they formulate a distributed ledger that will be maintained and extended without the need of a trusted party. Bitcoin has been criticized for its tendency to centralization, as very few pools control the majority of the hashing power. Pass et al. proposed FruitChain [PODC 17] and claimed that this blockchain protocol mitigates the formation of pools by reducing the variance of the rewards in the same way as mining pools, but in a fully decentralized fashion. Many follow up papers consider that the problem of centralization in Proof-of- Work (PoW) blockchain systems can be solved via lower rewards' variance, and that in FruitChain the formation of pools is unnecessary. Contrary to the common perception, in this work, we prove that lower variance of the rewards does not eliminate the tendency of the PoW blockchain protocols to centralization; miners have also other incentives to create large pools, and specifically to share the cost of creating the instance they need to solve the PoW puzzle. We abstract the procedures of FruitChain as oracles and assign to each of them a cost. Then, we provide a formal definition of a pool in a blockchain system, and by utilizing the notion of equilibrium with virtual payoffs (EVP) [AFT 21], we prove that there is a completely centralized EVP, where all the parties form a single pool controlled by one party called the pool leader. The pool leader is responsible for creating the instance used for the PoW procedure. To the best of our knowledge, this is the first work that examines the construction of mining pools in the FruitChain system.
The maturation of wireless connectivity, blockchain (distributed ledger technologies), and intelligent systems has fostered a comprehensive ecosystem for the Internet of Things (IoT). However, the growing volume of data generated by IoT devices creates substantial pressure on blockchain storage and computation capabilities, impeding the further development of the IoT ecosystem. Decentralizing data storage across multiple chains and utilizing cross-chain technology for data exchange eliminates the need for expensive centralized infrastructure, lowers data transfer costs, and improves accessibility. Hence, the issue of computational and storage pressure in blockchain can be improved. Nonetheless, the data of IoT devices are constantly updating, and ensuring consistency for dynamic data across heterogeneous chains remains a significant challenge. To address the aforementioned challenge, we propose a blockchain-based distributed and lightweight data consistency verification model (BDCA), which leverages a batch verification dynamic Merkle hash tree (BV-MHT) and an advanced gamma multi-signature scheme (AGMS) to enable consistent verification of dynamic data while ensuring secure and private data transmission. The AGMS scheme is reliable and robust based on security analysis while the dependability and consistency of BDCA are verified through inductive reasoning. Experimental results indicate that BDCA outperforms CPVPA and Fortress in communication and computation overhead for data preprocessing and auditing in a similar condition, and the AGMS scheme exhibits superior performance when compared to other widely adopted multi-signature schemes such as Cosi, BLS, and RSA. Furthermore, BDCA provides up to 99% data consistency guarantees, demonstrating its practicality.
Abner F. B. Costa, Henrique Hepp, Murilo V. G. da Silva, Leandro M. Zatesko
The Hidden Subgroup Problem (HSP) generalises many problems that are candidates to be NP-intermediate. It was shown that the decision version of HSP belongs to the zero-knowledge complexity class HVPZK and that, if the size of the group is known, it also belongs to NISZK. We show that whenever we can sample uniformly at random elements of the group and of a set, with the same size of the group, that contains the image of the function that hides the subgroup, the problem is in NIPZK1 (i.e. NIPZK with perfect completeness). As a second contribution, we show that NIPZK1 has a complete promise problem that is a restricted version of a complete promise problem for the NIPZK class.
Aditya Pribadi Kalapaaking, Ibrahim Khalil, Mohammed Atiquzzaman
The Internet of Things (IoT) is revolutionizing numerous industrial applications by employing smart devices in manufacturing and industrial processes. Industries based on IoT generate extensive data, typically analyzed using various machine learning (ML) models. Federated learning (FL) is an emerging, privacy-preserving ML method where clients train models locally and develop a global model based on the aggregation of local models, without sharing the local data set with a third party. However, FL methods struggle to achieve trustworthiness and incorporate accountable ML principles. Blockchain technologies are being developed across different industries to enhance trust and security. This article proposes a blockchain-enabled, verifiable model for securing FL within IoT systems. Our proposed framework combines a trusted execution platform (TEE) to secure each client’s local model training process, and multisignature-powered global model verification to ensure ML model verifiability. We conducted several experiments with different data sets to assess our proposed framework. The experiments demonstrated the high efficiency and scalability of the proposed framework.
Land registry system denotes to the system that records the particulars of land ownership rights by government bodies. The deposited record can be used as the proof on right and avoid any sort of scam. The aim of this work is to use decentralized system to increase the consistency of land registration and storage of property records based on ownership hierarchy. The system architecture is proposed and implemented here supported with dashboard for land contact owner, land inspector and users. Land inspectors dash board contains various operations like verification of user, land and transfer of property from one user to another user. Similarly, user dashboard contains entry of user details for registration, add land details, land gallery, send request to buy and received request for sale. Here, a consensus algorithm is employed to make nodes in a network like users, land registrar to reach a common agreement about the present state of the distributed ledger. Proof of Stake (PoS) consensus algorithm is utilized to authorize the blocks. The validators will confirm blocks by keeping a bet on them if they notice a block that can be added to the chain. SHA256 is a cryptographic hashing algorithm used which converts an input of arbitrary length into a fixed-size output and is utilized to generate addresses of blocks created when transaction happens. The system is working well as intended with respect to various operations.
Anton Wahrstätter, Matthew D. Solomon, Ben DiFrancesco, Vitalik Buterin · 5 authors
Stealth addresses represent an approach to enhancing privacy within public and distributed blockchains, such as Ethereum and Bitcoin. Stealth address protocols employ a distinct, randomly generated address for the recipient, thereby concealing interactions between entities. In this study, we introduce BaseSAP, an autonomous base-layer protocol for embedding stealth addresses within the application layer of programmable blockchains. BaseSAP expands upon previous research to develop a modular protocol for executing unlinkable transactions on public blockchains. BaseSAP allows for the development of additional stealth address layers using different cryptographic algorithms on top of the primary implementation, capitalizing on its modularity. To demonstrate the effectiveness of our proposed protocol, we present simulations of an advanced Secp256k1-based dual-key stealth address protocol. This protocol is developed on top of BaseSAP and deployed on the Ethereum test network as the first prototype implementation. Furthermore, we provide cost analyses and underscore potential security ramifications and attack vectors that could affect the privacy of stealth addresses. Our study highlights the flexibility of the BaseSAP protocol and provides insights into the broader implications of stealth address technology in the realm of blockchain privacy.
Isaac David, Liyi Zhou, Kaihua Qin, Dawn Song · 6 authors
We investigate the feasibility of employing large language models (LLMs) for conducting the security audit of smart contracts, a traditionally time-consuming and costly process. Our research focuses on the optimization of prompt engineering for enhanced security analysis, and we evaluate the performance and accuracy of LLMs using a benchmark dataset comprising 52 Decentralized Finance (DeFi) smart contracts that have previously been compromised. Our findings reveal that, when applied to vulnerable contracts, both GPT-4 and Claude models correctly identify the vulnerability type in 40% of the cases. However, these models also demonstrate a high false positive rate, necessitating continued involvement from manual auditors. The LLMs tested outperform a random model by 20% in terms of F1-score. To ensure the integrity of our study, we conduct mutation testing on five newly developed and ostensibly secure smart contracts, into which we manually insert two and 15 vulnerabilities each. This testing yielded a remarkable best-case 78.7% true positive rate for the GPT-4-32k model. We tested both, asking the models to perform a binary classification on whether a contract is vulnerable, and a non-binary prompt. We also examined the influence of model temperature variations and context length on the LLM's performance. Despite the potential for many further enhancements, this work lays the groundwork for a more efficient and economical approach to smart contract security audits.
Nguyễn Văn Nghị, Lại Thị Thu Vân, Hà Như Tuấn, Lê Minh Hiếu · 5 authors
Zero-Knowledge Proof (ZKP) - bằng chứng không lộ tri thức là một dạng kỹ thuật mật mã được công bố đầu tiên từ thập niên 90 của thế kỷ trước. Tuy nhiên, trong vòng 10 năm trở lại đây thì ZKP mới được ứng dụng phổ biến trong thực tế như: công nghệ Blockchain, hệ thống xác thực và kết hợp vào các thuật toán mật mã khác. Các lược đồ ZKP đang sử dụng này thì đa phần có cơ sở toán học trên trường hữu hạn có chi phí triển khai lớn và tốc độ chậm. Trong bài báo này, chúng tôi đề xuất một lược đồ ZKP kiểu Schnorr với cơ sở toán học dựa trên đường cong Elliptic. Mục tiêu giải pháp ZKP đề xuất trên Elliptic này có độ an toàn cao và hiệu năng tốt hơn so với lược đồ ZKP kiểu Schnorr trên trường hữu hạn, đồng thời có thêm một số cải tiến tốt hơn về mặt bảo mật so với các phiên ZKP kiểu Schnorr đã công bố khác trên đường cong Elliptic. Các kết quả này được lập luận dựa trên phương pháp nghiêncứu cơ sở lý thuyết toán học của các công trình đã công bố và thực nghiệm bằng ngôn ngữ lập trình python. Qua đó kết luận rằng đây là lược đồ ZKP rất có tiềm năng áp dụng vào thực tế trong các hệ thống xác thực và trong công nghệ Blockchain.
A commitment scheme is a cryptographic tool that allows one to commit to a hidden value, with the option to open it later at requested places without revealing the secret itself. Commitment schemes have important applications in zero-knowledge proofs and secure multi-party computation, just to name a few. This survey introduces a few multivariate polynomial commitment schemes that are built from a variety of mathematical structures. We study how Orion is constructed using hash functions; Dory, Bulletproofs, and Vampire using the inner-product argument; Signatures of Correct Computation using polynomial factoring; DARK and Dew using groups of unknown order; and Orion+ using a CP-SNARK. For each protocol, we prove its completeness and state its security assumptions.
Lattice-based cryptography is one of the most promising candidates for designing post-quantum cryptographic algorithms that resist emerging quantum computing attacks. The recent NIST PQC standardization process is nearing its completion, with practical lattice-based algorithms for basic cryptographic functionalities (namely digital signature and public-key encryption) selected for standardization in the near future. However, practical lattice-based solutions for more advanced privacy-preserving protocols, in particular, Zero-Knowledge Proofs (ZKPs), have only emerged recently and are an active area of research. We discuss some recent developments in design and analysis of practical lattice-based post-quantum ZKPs and their applications. In particular, we review some challenges that arise in designing ZKPs in the lattice setting and some recent progress on efficient lattice-based Schnorr-like proofs for important relations, such as binary/range proofs, one-out-of-many proofs and rounding proofs [1, 2, 4]. We discuss applications and optimization of such proof systems as building blocks for practical advanced cryptographic protocols such as ring signatures and balance proofs for privacy-preserving cryptocurrency payment protocols [2, 3]. We also discuss our recent work on succinct designated-verifier ZKPs (DV-ZKSNARKS) for verifying correctness of general delegated computations [5].