Some of the well-known signature techniques like Winternitz and Lamport are not considered to be very appropriate for the usage of hashing or smart contracts in Blockchains security because of their size O(n2), which is prominently too high. Although in Blockchain, the security concern is on the top priority because of its distributed P2P design still, the security enhancement is required to sign and verify the documents forwarded to the peers, especially in Hyperledger Fabric. Here, this paper presents a new signature technique “Block-Hash” to enhance Blockchain security by using it in smart contracts as well as hashing with size 3Xn bits (n=256, generally for SHA-256 Hashing) and which can score 112 bits security. The proposed signature can be used appropriately for signing a smart contract by the endorser or committer node. Also, it can be used with a hash algorithm in forming a Merkle tree. Apart from the description and implementation of Block-Hash Signature, this paper has covered the analysis of its security and correctness measures with a table for result comparison.
Marco Di Francesco, Lodovica Marchesi, Raffaele Porcu
Trading data sets is not easy. The owner of valuable data, once they are sold the first time, cannot be sure that they will not be copied and resold. On the other hand, the buyer, cannot be sure that the seller will not sell the same data to a competitor. The advent of blockchain technology, or DLT, can mitigate, or event solve these issues, because it can certify the data ownership, and act as a broker between seller and buyer. In this paper we present Kryptosafe, a system developed following sound software engineering practices, aimed to manage the trade of data sets taking advantage of the unique features of immutability and trustfulness of Ethereum blockchain, and of IPFS distributed DBMS. Kryptosafe allows data sellers to sell a whole encrypted data set or to show potential buyers a subset of it, allowing full access only after the sale is finalized. Using ERC721 and ERC1155 tokens, it also manages one-time sales, when the data set ownership is simply transferred to the buyer, or multiple sales of the same data set to different buyers.
We proposed a new construction for contract wallets, smart contract applications that allow users to control their crypto assets. Users can manipulate their crypto assets by simply sending emails with no need to manage keys. These emails are verified using zero-knowledge proof (ZKP) along with their attached digital signatures that the sender domain server (SDS) generates according to DomainKeys Identified Mail. Unless the SDS forges the emails, the crypto assets remain secure in the proposed system. Moreover, the existing SDSs can be used as is by outsourcing additional work to a third party that is not necessarily trusted. The system supports various functions to manipulate crypto assets. We produced a tool for variable-regex mapping (VRM) that enables developers to build a new function without ZKP skills. For example, using the tool, we built a demo application where users can exchange crypto assets via Uniswap only with emails. The published version of this paper is available at https://doi.org/10.1109/ICBC56567.2023.10174932.
While the Internet of things brings convenience to people's lives, it will also bring people hidden worries about data security. As an important barrier to protect data security, identity authentication is widely used in the Internet of things. However, it is necessary to protect users' identity privacy while authenticating their identity. Anonymous authentication technology is often used to solve the contradiction between legitimacy and privacy in the authentication process. The existing anonymous authentication scheme has many problems in practical application such as the inability to achieve complete anonymity, the high computational complexity of the algorithm, and the corruption of the central authority. Aiming at the privacy of authentication, we propose Zero-Cerd, a self-blindable anonymous authentication system based on blockchain and dynamic accumulator. The self-blinding properties of the credential enable the users themselves to generate a new validly pseudonymous credential. With the help of zero-knowledge proof technology, users can prove the validity of their credentials without disclosing any information. Security analysis shows that our scheme has achieved the expected security objectives. Compared with the existing schemes, our scheme has the advantages of complete anonymity and high efficiency, and is more suitable for IoT applications with privacy protection requirements.
Many protocols in distributed computing rely on a source of randomness, usually called a random beacon, both for their applicability and security. This is especially true for proof-of-stake blockchain protocols in which the next miner or set of miners have to be chosen randomly and each party's likelihood to be selected is in proportion to their stake in the cryptocurrency. Current random beacons used in proof-of-stake protocols, such as Ouroboros and Algorand, have two fundamental limitations: Either (i)~they rely on pseudorandomness, e.g.~assuming that the output of a hash function is uniform, which is a widely-used but unproven assumption, or (ii)~they generate their randomness using a distributed protocol in which several participants are required to submit random numbers which are then used in the generation of a final random result. However, in this case, there is no guarantee that the numbers provided by the parties are uniformly random and there is no incentive for the parties to honestly generate uniform randomness. Most random beacons have both limitations. In this thesis, we provide a protocol for distributed generation of randomness. Our protocol does not rely on pseudorandomness at all. Similar to some of the previous approaches, it uses random inputs by different participants to generate a final random result. However, the crucial difference is that we provide a game-theoretic guarantee showing that it is in everyone's best interest to submit uniform random numbers. Hence, our approach is the first to incentivize honest behavior instead of just assuming it. Moreover, the approach is trustless and generates unbiased random numbers. It is also tamper-proof and no party can change the output or affect its distribution. Finally, it is designed with modularity in mind and can be easily plugged into existing distributed protocols such as proof-of-stake blockchains.
Ethereum is a popular blockchain that facilitates the creation of decentralized applications (dApps) and enables digital transactions to be executed without the need for a central authority. However, as in traditional markets, information asymmetry and market inefficiencies are used to the detriment of ordinary users via trading strategies that exploit “Miner Extractable Value” (MEV). We propose two extensions of Ethereum, one for proof of work (PoW), and one for proof of stake (PoS), that eliminate most forms of MEV by randomizing the execution order of transactions and hiding the content of transactions until their inclusion in a block. We simulate attack scenarios for both settings and provide detailed security properties and proofs.
To prevent DoS attacks, Ethereum assigns a fixed gas cost to every atomic operation in the EVM and the party who creates a transaction has to pay for its overall gas usage. While the gas model is successful in preventing DoS attacks, it causes significant costs in transaction fees. For example, in June-September 2022, the average daily gas usage of Ethereum was almost four million dollars. We propose a solution to minimize these fees by moving most of the execution of a contract off-chain and storing only the bare minimum on-chain. We then trigger an on-chain execution only if there is a disagreement between the parties to the contract, which is in turn only possible if at least one party is acting dishonestly. In such cases, our approach can identify and penalize the dishonest party by making them pay not only for the gas usage of their own function calls, but also calls made by other parties. Thus, it is game-theoretically irrational to behave dishonestly in this protocol. If all parties are rational, the total gas usage goes down significantly. Notably, our approach does not require a sidechain and works directly on the main Ethereum blockchain. We also provide extensive experiments over real-world Ethereum smart contracts, demonstrating that our protocol reduces their gas usage by 40.09%.
Nowadays, data between hospitals are usually not interoperable, which brings great inconvenience to medical data sharing and patients’ medical treatment. In addition, patients do not want their medical data to be leaked during the sharing process. Researchers have employed blockchain to build data-sharing systems to address these issues. However, current systems do not restrict the power of participants, nor do they prevent visitors from sharing the obtained data to unauthorized parties. To address these issues, we propose a private data-sharing system with symmetric encryption for the medical industry that implements power restriction and access control, and prevents the leakage of private data. To be specific, firstly, symmetric encryption algorithm is utilized to encrypt medical data to protect the privacy of data owner. Secondly, our proposed system is built on a new blockchain framework, in which only visitors with permission can access the medical data. Thirdly, we employ chameleon signature to prevent visitors from sharing data with other parties without permission. Finally, we make the power of participants in the system revocable to prevent them from abusing their power. Our proposed system has been proven to be secure through security analysis and can protect the privacy of patients. In addition, the experimental results show that our system has excellent performance in terms of time overhead compared to other systems.
As digital payments become increasingly ubiquitous, concerns over data privacy and transaction security have intensified, prompting the need for privacy-preserving payment architectures. This study explores the design, implementation, and evaluation of payment systems that ensure confidentiality, integrity, and anonymity without compromising transactional efficiency or regulatory compliance. It examines key technologies such as homomorphic encryption, secure multiparty computation, zero-knowledge proofs, and blockchain-based mechanisms that enable secure payment verification and data sharing with minimal exposure of sensitive user information. Furthermore, it highlights privacy-enhancing frameworks integrated into mobile wallets, digital identity systems, and decentralized finance (DeFi) platforms. Through comparative analysis of centralized and decentralized payment models, the paper identifies trade-offs between scalability, transparency, and privacy assurance. The findings underscore that hybrid architectures—combining cryptographic privacy layers with compliance-enabling audit trails—represent the most viable approach for future financial ecosystems. Ultimately, privacy-preserving payment architectures not only safeguard user trust but also support regulatory adaptability and sustainable innovation in the evolving landscape of digital finance.
Smart contracts self-executing code deployed on blockchain platforms have revolutionized the way digital agreements are formed and executed. Despite their decentralized nature and deterministic logic, vulnerabilities in code and execution environments can compromise their security. Cryptography is pivotal in safeguarding the integrity, authenticity, and confidentiality of smart contract operations. This paper explores cryptographic techniques that enhance smart contract trustworthiness, including digital signatures, zero-knowledge proofs, and verifiable computation. We assess how these methods reinforce security, compare frameworks across criteria like scalability and auditability, and present best practices for secure smart contract development
Cristina Vilchez Moya, Juan Ramón Bermejo Higuera, Juan Ramón Bermejo Higuera, Javier Bermejo Higuera · 6 authors
The problem of digital identity acquires more relevance every day in the eyes of a society that spends more and more time connected to the Internet. It has evolved throughout its history to reach a decentralized model known as Self-Sovereign Identity (SSI), which finds its natural tools in the blockchain technology and Zero-Knowledge Proofs (ZKPs). ZKPs, in this context, allow users to prove that their credentials are legitimate without revealing more information than is strictly necessary, and constitute one of the most promising areas of applied cryptography. In this work, an application is developed for the study of Zero-Knowledge Proof methods and, specifically, in their application for authentication in public-private key encryption systems. It focuses on the study of three ZKP protocols (Feige-Fiat-Shamir, Guillou-Quisquater, and Schnorr, which rely on the problems of large number factorizations and discrete logarithms for security) in the practical use-case where a prover wants to demonstrate knowledge of a private key for a public key without revealing the key itself. The application allows the user to modify the necessary parameters in each method to achieve a better understanding of their role in their safety and efficiency. Several types of attacks are carried out against the above-mentioned protocols to analyze their degree of security and what recommendations can be made to improve it.
John Domingue, Allan Third, María-Esther Vidal, Philipp D. Rohde · 7 authors
Knowledge Graphs have become a foundation for sharing data on the web and building intelligent services across many sectors and also within some of the most successful corporations in the world. The over centralisation of data on the web, however, has been raised as a concern by a number of prominent researchers in the field. For example, at the beginning of 2022 a €2.7B civil lawsuit was launched against Meta on the basis that it has abused its market dominance to impose unfair terms and conditions on UK users in order to exploit their personal data. Data centralisation can lead to a number of problems including: lock-in/siloing effects, lack of user control over their personal data, limited incentives and opportunities for interoperability and openness, and the resulting detrimental effects on privacy and innovation. A number of diverse approaches and technologies exist for decentralising data, such as federated querying and distributed ledgers. The main question is, though, what does decentralisation really mean for web data and Knowledge Graphs? What are the main issues and tradeoffs involved? These questions and others are addressed in this workshop.
Blockchain protocols typically aspire to run in the permissionless setting, in which nodes are owned and operated by a large number of diverse and unknown entities, with each node free to start or stop running the protocol at any time. This setting is more challenging than the traditional permissioned setting, in which the set of nodes that will be running the protocol is fixed and known at the time of protocol deployment. The goal of this paper is to provide a framework for reasoning about the rich design space of blockchain protocols and their capabilities and limitations in the permissionless setting. We propose a hierarchy of settings with different "degrees of permissionlessness", specified by the amount of knowledge that a protocol has about the current participants: These are the fully permissionless, dynamically available and quasi-permissionless settings. The paper also proves several results illustrating the utility of our analysis framework for reasoning about blockchain protocols in these settings. For example: (1) In the fully permissionless setting, even with synchronous communication and with severe restrictions on the total size of the Byzantine players, every deterministic protocol for Byzantine agreement has a non-terminating execution. (2) In the dynamically available and partially synchronous setting, no protocol can solve the Byzantine agreement problem with high probability, even if there are no Byzantine players at all. (3) In the quasi-permissionless and partially synchronous setting, by contrast, assuming a bound on the total size of the Byzantine players, there is a deterministic protocol solving state machine replication. (4) In the quasi-permissionless and synchronous setting, every proof-of-stake state machine replication protocol that uses only time-malleable cryptographic primitives is vulnerable to long-range attacks.
Abstract Blockchain and Decentralized Applications (DApps) are increasingly important for creating trust and transparency in data storage and computation. However, on-chain transactions are often costly and slow. To overcome this challenge, off-chain nodes can be used to store and compute data. Unfortunately, this introduces the risk of untrusted nodes. To address this, authenticated data structures have been proposed, however, this ignores the compute of data from the raw data. We tackle this challenge by introducing zk-Oracle, which provides an efficient and trusted compute and storage off-chain. There is a challenge in using zero-knowledge proofs (zk-proof for short), which is the large proof generation time. We aim to overcome it with novel designs in zk-Oracle. zk-Oracle builds on zk-proofs technologies to achieve two goals. First, the computation of data structures from raw data and the corresponding proof generation is improved in terms of performance. Second, the verification on-chain is inexpensive and fast. Our experiments show that we can speed up zk-proof generation by up to $$550 \times $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>550</mml:mn> <mml:mo>×</mml:mo> </mml:mrow> </mml:math> faster than the baseline method.
Recent years have witnessed explosive growth in blockchain smart contract applications. As smart contracts become increasingly popular and carry trillion dollars worth of digital assets, they become more of an appealing target for attackers, who have exploited vulnerabilities in smart contracts to cause catastrophic economic losses. Notwithstanding a proliferation of work that has been developed to detect an impressive list of vulnerabilities, the bad randomness vulnerability is overlooked by many existing tools. In this paper, we make the first attempt to provide a systematic analysis of random numbers in Ethereum smart contracts, by investigating the principles behind pseudo-random number generation and organizing them into a taxonomy. We also lucubrate various attacks against bad random numbers and group them into four categories. Furthermore, we present RNVulDet - a tool that incorporates taint analysis techniques to automatically identify bad randomness vulnerabilities and detect corresponding attack transactions. To extensively verify the effectiveness of RNVulDet, we construct three new datasets: i) 34 well-known contracts that are reported to possess bad randomness vulnerabilities, ii) 214 popular contracts that have been rigorously audited before launch and are regarded as free of bad randomness vulnerabilities, and iii) a dataset consisting of 47,668 smart contracts and 49,951 suspicious transactions. We compare RNVulDet with three state-of-the-art smart contract vulnerability detectors, and our tool significantly outperforms them. Meanwhile, RNVulDet spends 2.98s per contract on average, in most cases orders-of-magnitude faster than other tools. RNVulDet successfully reveals 44,264 attack transactions. Our implementation and datasets are released, hoping to inspire others.
Xin Liu, Xiaomeng Liu, Naixue Xiong, Dan Luo · 6 authors
With the rapid development of cloud computing and other modern technologies, collaborative computing between data is increasing, and privacy protection and secure multi-party computation are also attracting more attention. The emergence of cloud computing provides new options for data holders to perform complex computing problems and to store images; however, data privacy issues cannot be ignored. If a graphic is encrypted and stored in the cloud, the cloud server will perform confidential similar matching when the user searches. At present, most research on searchable encryption is focused on text search, with few schemes researched on how to finish the graphic search. To solve this problem, this paper proposes a secure search protocol based on graph shape under the semi-honest model. Using the cut-choose method and zero-knowledge proof, further designs of the anti-malicious attack graphic similarity judgment system (AAJS) based on the Paillier encryption algorithm, can achieve the secure search and matching of the graph while resisting malicious adversary attacks. The proposed protocol’s security is proved by the real/ideal model paradigm. This paper conducts performance analysis and experimental simulation on the existing scheme and the experiments demonstrate that the system achieves high execution efficiency.
In this paper, we propose a physical protocol to verify the first nonzero term of a sequence using a deck of cards. The protocol lets a prover show the value of the first nonzero term of a given sequence to a verifier without revealing which term it is. Our protocol uses $Θ(1)$ shuffles, which is asymptotically lower than that of an existing protocol of Fukusawa and Manabe which uses $Θ(n)$ shuffles, where $n$ is the length of the sequence. We also apply our protocol to construct zero-knowledge proof protocols for three well-known logic puzzles: ABC End View, Goishi Hiroi, and Toichika. These protocols enables a prover to physically show that he/she know solutions of the puzzles without revealing them.
Abstract Fair exchange is a challenging problem for two mutually distrusting players. It is widely known that fair exchange is impossible without a trusted third party (TTP). However, relying on a single TTP can cause a single-point failure. An intuitive idea is to adopt multiple TTPs to distribute trust. This paper constructs a two-party optimistic fair exchange (OFE) protocol using decentralized ciphertext-policy attribute-based encryption (CP-ABE), achieving decentralized TTPs. This is achievable because decentralized CP-ABE ciphertext supports a nested access control policy. A nested access control policy fits perfectly in a fair exchange protocol which contains multiple roles (i.e. players and TTPs). Further, we apply non-interactive zero knowledge proofs to prove the well-formedness of ciphertexts, so as to enforce players to follow the protocol specification honestly. Consequently, we construct an OFE protocol in which each player’s operations are publicly verifiable without revealing secret information. Also, we obtain decentralized TTPs with optimism (i.e. the TTPs are involved only when arbitration is required), autonomy (i.e. the TTPs do not need to interact with each other), statelessness (i.e. the TTPs do not need to store data for the exchange protocol) and verifiability (i.e. the TTPs are publicly verifiable). Compared with previous work, our protocol assumes only a public communication channel and each party’s operations are publicly verifiable. Besides, it achieves a favorable $O(n)$ verification complexity in the normal case, where $n$ is the number of TTPs. Finally, we present a proof-of-concept implementation to demonstrate the feasibility.
Smart contracts are small programs on the blockchain that often handle valuable assets. Vulnerabilities in smart contracts can be costly, as time has shown over and over again. Countermeasures are high in demand and include best practice recommendations as well as tools supporting development, program verification, and post-deployment analysis. Many tools focus on detecting the absence or presence of a subset of the known vulnerabilities, delivering results of varying quality. Most comparative tool evaluations resort to selecting a handful of tools and testing them against each other. In the best case, the evaluation is based on a smallish ground truth. For Ethereum, there are commendable efforts by several author groups to manually classify contracts. However, a comprehensive ground truth is still lacking. In this work, we construct a ground truth based on publicly available benchmark sets for Ethereum smart contracts with manually checked ground truth data. We develop a method to unify these sets. Additionally, we devise strategies for matching entries that pertain to the same contract, such that we can determine overlaps and disagreements between the sets and consolidate the disagreements. Finally, we assess the quality of the included ground truth sets. Our work reduces inconsistencies, redundancies, and incompleteness while increasing the number of data points and heterogeneity.
Izdehar M. Aldyaflah, Wenbing Zhao, Himanshu Upadhyay, Leonel Lagos
In this paper, we present a secure datastore based on an Ethereum smart contract. Our research is guided by three research questions. First, we will explore to what extend a smart-contract-based datastore should resemble a traditional database system. Second, we will investigate how to store the data in a smart-contract-based datastore for maximum flexibility while minimizing the gas consumption. Third, we seek answers regarding whether or not a smart-contract-based datastore should incorporate complex processing such as data encryption and data analytic algorithms. The proposed smart-contract-based datastore aims to strike a good balance between several constraints: (1) smart contracts are publicly visible, which may create a confidentiality concern for the data stored in the datastore; (2) unlike traditional database systems, the Ethereum smart contract programming language (i.e., Solidity) offers very limited data structures for data management; (3) all operations that mutate the blockchain state would incur financial costs and the developers for smart contracts must make sure sufficient gas is provisioned for every smart contract call, and ideally, the gas consumption should be minimized. Our investigation shows that although it is essential for a smart-contract-based datastore to offer some basic data query functionality, it is impractical to offer query flexibility that resembles that of a traditional database system. Furthermore, we propose that data should be structured as tag-value pairs, where the tag serves as a non-unique key that describes the nature of the value. We also conclude that complex processing should not be allowed in the smart contract due to the financial burden and security concerns. The tag-based secure datastore designed this way also defines its applicative perimeter, i.e., only applications that align with our strategy would find the proposed datastore a good fit. Those that would rather incur higher financial cost for more data query flexibility and/or less user burden on data pre- and post-processing would find the proposed database too restrictive.
Aditya Pribadi Kalapaaking, Ibrahim Khalil, Xun Yi
Due to the rising awareness of privacy and security in machine learning applications, federated learning (FL) has received widespread attention and applied to several areas, e.g., intelligence healthcare systems, IoT-based industries, and smart cities. FL enables clients to train a global model collaboratively without accessing their local training data. However, the current FL schemes are vulnerable to adversarial attacks. Its architecture makes detecting and defending against malicious model updates difficult. In addition, most recent studies to detect FL from malicious updates while maintaining the model's privacy have not been sufficiently explored. This paper proposed blockchain-based federated learning with SMPC model verification against poisoning attacks for healthcare systems. First, we check the machine learning model from the FL participants through an encrypted inference process and remove the compromised model. Once the participants' local models have been verified, the models are sent to the blockchain node to be securely aggregated. We conducted several experiments with different medical datasets to evaluate our proposed framework.
Abstract With the rapid development of cloud computing technology, how to achieve secure access to cloud data has become a current research hotspot. Attribute-based encryption technology provides the feasibility to achieve the above goal. However, most of the existing solutions have high computational and trust costs. Furthermore, the fairness of access authorization and the security of data search can be difficult to guarantee. To address these issues, we propose a novel access control scheme based on blockchain and attribute-based searchable encryption in cloud environment. The proposed scheme achieves fine-grained access control with low computation consumption by implementing proxy encryption and decryption, while supporting policy hiding and attribute revocation. The encrypted file is stored in the IPFS and the metadata ciphertext is stored on the blockchain, which ensures data integrity and confidentiality. Simultaneously, the scheme enables the secure search of ciphertext keyword in an open and transparent blockchain environment. Additionally, an audit contract is designed to constrain user access behavior to dynamically manage access authorization. Security analysis proves that our scheme is resistant to chosen-plaintext attacks and keyword-guessing attacks. Theoretical analysis and experimental results show that our scheme has high computational and storage efficiency, which is more advantageous than other schemes.
Smart contracts are crucial elements of decentralized technologies, but they face significant obstacles to trustworthiness due to security bugs and trapdoors. To address the core issue, we propose a technology that enables programmers to focus on design-level properties rather than specific low-level attack patterns. Our proposed technology, called Theorem-Carrying-Transaction (TCT), combines the benefits of runtime checking and symbolic proof. Under the TCT protocol, every transaction must carry a theorem that proves its adherence to the safety properties in the invoked contracts, and the blockchain checks the proof before executing the transaction. The unique design of TCT ensures that the theorems are provable and checkable in an efficient manner. We believe that TCT holds a great promise for enabling provably secure smart contracts in the future. As such, we call for collaboration toward this vision.
Sharding scales throughput by splitting blockchain nodes into parallel groups. However, different shards' independent and random scheduling for cross-shard transactions results in numerous conflicts and aborts, since cross-shard transactions from different shards may access the same account. A deterministic ordering can eliminate conflicts by determining a global order for transactions before processing, as proved in the database field. Unfortunately, due to the intertwining of the Byzantine environment and information isolation among shards, there is no trusted party able to predetermine such an order for cross-shard transactions. To tackle this challenge, this paper proposes Prophet, a conflict-free sharding blockchain based on Byzantine-tolerant deterministic ordering. It first depends on untrusted self-organizing coalitions of nodes from different shards to pre-execute cross-shard transactions for prerequisite information about ordering. It then determines a trusted global order based on stateless ordering and post-verification for pre-executed results, through shard cooperation. Following the order, the shards thus orderly execute and commit transactions without conflicts. Prophet orchestrates the pre-execution, ordering, and execution processes in the sharding consensus for minimal overhead. We rigorously prove the determinism and serializability of transactions under the Byzantine and sharded environment. An evaluation of our prototype shows that Prophet improves the throughput by $3.11\times$ and achieves nearly no aborts on 1 million Ethereum transactions compared with state-of-the-art sharding.