If the cloud is just someone else's computer, securing forensic evidence in case of a breach can be tricky. A blockchain-based distributed ledger could contribute to solve this problem, provided the required forensic information finds its way onto the blockchain. In this paper we sketch how blockchain technology and smart contracts apply to various processing models and their respective forensic challenges, and highlight how an accountability-based approach will be instrumental to the overall acceptability of the solution.
Rafael Ansey, James Kempf, Oleg Berzin, Xi Chen · 5 authors
Decentralized Identifiers (DIDs) are a new class of cryptographically secure identifier that does not require a centralized trust anchor for attesting to the validity of keying material. DIDs are based on distributed ledger (blockchain) technology and allow the entity itself to manage its own identifier, hence the name "self-sovereign" which is often applied to them. In this paper, we describe Gnomon, a system that uses DIDs to securely register 5G IoT devices and install firmware/software into the device. Gnomon is designed to avoid the kind of difficulties that plague current technology, which is largely based on Public Key Infrastructure (PKI) and X.509 public key certificates. After a short introduction, we review current practice and briefly describe DIDs and verifiable credentials, a mechanism based on DIDs to securely assert information about the identified entity. We then describe the architecture of Gnomon and a prototype we built, based on the ION DID scheme, for applying DIDs and verifiable credentials to 5G IoT device registration and software installation.
Omaji Samuel, Nadeem Javaid, Muhammad Awais, Zeeshan Ahmed · 6 authors
The emergence of smart home appliances has generated a high volume of data on smart meters belonging to different customers. However, customers can not share their data in deregulated smart grids due to privacy concern. Although, these data are important for the service provider in order to provide an efficient service. To encourage the customers' participation, this paper proposes an access control mechanism by fairly compensating customers for their participation in data sharing via blockchain using the concept of differential privacy. We addressed the computational issues of existing ethereum blockchain by proposing a proof of authority consensus protocol through the Pagerank mechanism in order to derive the reputation scores. Experimental results show the efficiency of the proposed model to minimize privacy risk, and maximize aggregator's profit. In addition, gas consumption, as well as the cost of the computational resources, is reduced.
The General Data Protection Regulation (GDPR) gives control of data to the data owner. It imposes several requirements and obligations on organizations that process and manage personal data of EU citizens. GDPR uses consent as a legal basis for personal data processing. We design a semantic model to represent GDPR consents; our model is explicit, understandable, and reusable. Ensuring that organizations comply with GDPR with respect to user consents is a critical issue. To address such an issue, we propose a Blockchain-based model for compliance verification. Our decentralized model ensures that only parties authorized based on users' consent can access users' data and that all activities are logged in an immutable distributed ledger. Our GDPR privacy protection framework is cast into the XACML reference architecture.
Recent technological evolution enables Artificial Intelligence (AI) model training by users' mobile devices, which accelerates decentralized big data analysis. In particular, Federated Learning (FL) is a key enabler to realize decentralized AI model update without user's privacy disclosure. However, since the behaviour of workers, who are assigned a training task, cannot be monitored, the state-of-the-art methods require a special hardware and/or cryptography to force the workers behave honestly, which hinders the realization. Furthermore, although blockchain-enabled FL has been proposed to give workers reward, any rigorous reward policy design has not been discussed. In this paper, to tackle these issues, we present a novel method using mechanism design, which is an economic approach to realize desired objectives under the situation that participants act rationally. The key idea is to introduce repeated competition for FL so that any rational worker follows the protocol and maximize their profits. With mechanism design, we propose a generic full-fledged protocol design for FL on a public blockchain. We also theoretically clarify incentive compatibility based on contest theory which is an auction-based game theory in economics.
Zero-knowledge schemes have recently become a popular attempt to offer users privacy in an attribute-based credential system. In this article, we do not contest the mathematics of these schemes; we assume it is logically sound. Instead, we draw attention to the trade-off that is made when employing cryptography instead of trusted parties to protect user privacy. We assert that, for these approaches to create the trust required by credential verifiers, they must introduce mechanisms that limit their utility and create significant privacy risk to the user that cuts against data minimization goals. Greater trust must be placed in the shelf life of cryptography to prevent the user from being unwantonly correlated than alternative approaches. Just as we would discourage storing encrypted private data on public blockchains, we discourage this approach here. Lastly, this article introduces the concept of a trusted witness which provides privacy for honest users and solves the privacy-trust problem without the disadvantages of the zero-knowledge approach.
With the arrival of the Internet of Things (IoT) era and the rise of Big Data, cloud computing, and similar technologies, data resources are becoming increasingly valuable. Organizations and users can perform all kinds of processing and analysis on the basis of massive IoT data, thus adding to their value. However, this is based on data-sharing transactions, and most existing work focuses on one aspect of data transactions, such as convenience, privacy protection, and auditing. In this paper, a data-sharing-transaction application based on blockchain technology is proposed, which comprehensively considers various types of performance, provides an efficient consistency mechanism, improves transaction verification, realizes high-performance concurrency, and has tamperproof functions. Experiments were designed to analyze the functions and storage of the proposed system.
Blockchain is at present one of the most disruptive technologies that have the potential to radically change today’s business models. Blockchain is a decentralised database distributed across several systems. Blockchain technology is expected to be used by different sectors, such as finance, government, and healthcare domains. Blockchain is basically a peer-to-peer cryptographic-based mechanism where each peer holds a digital database known as a ledger in some applications. A smart contract is used in the blockchain framework in order to execute some actions when certain predefined conditions in the contract are met. Public blockchain means that everyone can join and contribute to the network. Blockchain holds the total value of daily exchanges. The central bank can examine the enormous information that is stored in the blockchain. Multi-signature provides a way to form contracts without trusting any other party in the blockchain.
With recent adoption of Internet of Things (IoT) technologies and their use in industry, user data privacy concerns remain a major preoccupation of regulation bodies. The European General Data Protection Regulation (GDPR) enables users to control their data and be informed about any devices involved in collecting and processing this data. The overall objective is to enable individuals to have full rights and control over their data assets and to be able to transfer their data without any unmitigated risk. Blockchains provide the benefits of a distributed ledger that can securely manage digital transactions -- where the centralisation of data is eliminated. Blockchains have recently entered as an enabling technology into the IoT market, and used in a variety of different application areas. Blockchains enable the implementation of a more trusted system capable of processing operations between IoT services and sources of data. In smart buildings, for example, Blockchains support the formation of smart contracts as a means to give transactional capabilities to IoT devices, allowing users to keep data ownership and privacy using an immutable dataset. We describe how Blockchain technology can be used to develop an audit trail of data generated in IoT devices, enabling GDPR rules to be verified on such a trail. We describe how to translate a set of such rules into smart contracts to protect personal data in a transparent and automatic way.
We initiate the study of non-interactive zero-knowledge (NIZK) arguments for languages in QMA. Our first main result is the following: if Learning With Errors (LWE) is hard for quantum computers, then any language in QMA has an NIZK argument with preprocessing. The preprocessing in our argument system consists of (i) the generation of a CRS and (ii) a single (instance-independent) quantum message from verifier to prover. The instance-dependent phase of our argument system involves only a single classical message from prover to verifier. Importantly, verification in our protocol is entirely classical, and the verifier needs not have quantum memory; its only quantum actions are in the preprocessing phase. Our second contribution is to extend the notion of a classical proof of knowledge to the quantum setting. We introduce the notions of arguments and proofs of quantum knowledge (AoQK/PoQK), and we show that our non-interactive argument system satisfies the definition of an AoQK. In particular, we explicitly construct an extractor which can recover a quantum witness from any prover which is successful in our protocol. Finally, we show that any language in QMA has an (interactive) proof of quantum knowledge.
Vehicular ad hoc networks (VANET) are also known as intelligent transportation systems. VANET ensures timely and accurate communications between vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) to improve road safety and enhance the efficiency of traffic flow. Due to its open wireless boundary and high mobility, VANET is vulnerable to malicious nodes that could gain access into the network and carry out serious medium access control (MAC) layer threats, such as denial of service (DoS) attacks, data modification attacks, impersonation attacks, Sybil attacks, and replay attacks. This could affect the network security and privacy, causing harm to the information exchange within the network by genuine nodes and increase fatal impacts on the road. Therefore, a novel secure trust-based architecture that utilizes blockchain technology has been proposed to increase security and privacy to mitigate the aforementioned MAC layer attacks. A series of experiment has been conducted using the Veins simulation tool to assess the performance of the proposed solution in the terms of packet delivery ratio (PDR), end-to-end delay, packet loss, transmission overhead, and computational cost.
Lingjun Fan, J. Ramón Gil-GarcÃa, Yi Song, Felippe Cronemberger · 10 authors
Governments have vast data resources related to a wide-variety of policies and programs. Integrating and sharing data across agencies and departments can add value to these data resources and bring about significant changes in public services as well as better government decisions. However, in addition to the lack of standards and an adequate information architecture, the main obstacles to a centralized government data-sharing strategy are security and privacy concerns. Blockchain - a decentralized peer-to-peer distributed ledger technology - provides a new way to develop sharing mechanisms. In addition, blockchain-based systems are difficult to tamper with and are highly traceable. Based on the current problems of a big data center in the city of Ningbo, China, this paper identifies limitations of this approach and explores the potential of some data sharing mechanism based on blockchain technology. Our analysis describes some potential advantages and the feasibility of using distributed data sharing and automated management mechanisms based on blockchain smart contracts. We also explore implementation challenges and provide some practical recommendations.
Distributed ledger technology offers numerous desirable attributes to\napplications in the enterprise context. However, with distributed data and\ndecentralized computation on a shared platform, privacy and confidentiality\nchallenges arise. Any design for an enterprise system needs to carefully cater\nfor use case specific privacy and confidentiality needs. With the goal to\nfacilitate the design of enterprise solutions, this paper aims to provide a\nguide to navigate and aid in decisions around common requirements and\nmechanisms that prevent the leakage of private and confidential information. To\nfurther contextualize key concepts, the design guide is then applied to three\nenterprise DLT protocols: Hyperledger Fabric, Corda, and Quorum.\n
Recently, blockchain has received much attention from the mobility-centric Internet of Things (IoT). It is deemed the key to ensuring the built-in integrity of information and security of immutability by design in the peer-to-peer network (P2P) of mobile devices. In a permissioned blockchain, the authority of the system has control over the identities of its users. Such information can allow an ill-intentioned authority to map identities with their spatiotemporal data, which undermines the location privacy of a mobile user. In this paper, we study the location privacy preservation problem in the context of permissioned blockchain-based IoT systems under three conditions. First, the authority of the blockchain holds the public and private key distribution task in the system. Second, there exists a spatiotemporal correlation between consecutive location-based transactions. Third, users communicate with each other through short-range communication technologies such that it constitutes a proof of location (PoL) on their actual locations. We show that, in a permissioned blockchain with an authority and a presence of a PoL, existing approaches cannot be applied using a plug-and-play approach to protect location privacy. In this context, we propose BlockPriv, an obfuscation technique that quantifies, both theoretically and experimentally, the relationship between privacy and utility in order to dynamically protect the privacy of sensitive locations in the permissioned blockchain.
We present a new 4-move special honest-verifier zero-knowledge proof of knowledge system for proving that a vector of Pedersen commitments opens to a so-called "one-hot'' vector (i.e., to a vector from the standard orthonormal basis) from Zpn. The need for such proofs arises in the contexts of symmetric private information retrieval (SPIR), end-to-end verifiable voting (E2E), and privacy-preserving data aggregation and analytics, among others. The key insight underlying the new protocol is a simple observation regarding the paucity of roots of polynomials of bounded degree over a finite field. The new protocol is fast and yields succinct proofs: For vectors of length n, the prover evaluates Θ(Θlgn) group operations plus Θ(n) field operations and sends just Θ(Θlgn) group and field elements, while the verifier evaluates one n-base multiexponentiation plus Θ(łlgn) additional group operations and sends just 2(λ+lgn) bits to obtain a soundness error less than 2-λ. (A 5-move variant of the protocol reduces prover upload to just λlgn bits for the same soundness error.) We have implemented both our new protocol and its closest competitors from the literature; in accordance with our analytic results, experiments confirm that the new protocols handily outperform existing protocols for all but the shortest of vectors (roughly, for vectors with more than 16-32 elements).
Wendy Charles, Natalie Marler, Lauren Long, Sean T. Manion
As clinical research moves toward real-world data capture with increased data sharing, there is a growing need for patient-centered technologies that ensure data authenticity and promote researcher and patient access. Blockchain is one of an emerging set of distributed ledger technologies with the potential to offer both research data transparency and trust, while offering robust security measures. As blockchain-based systems are being developed for clinical research applications, these systems may be required to follow state and federal research regulations, such as ethical protections for human participants and data privacy. Blockchain developers and research organizations alike are struggling to identify and interpret these regulatory requirements. Further, regulatory agencies and policymakers have not yet provided blockchain stakeholders with clear guidelines to achieve compliance. This article provides an introduction to the clinical research and health information privacy regulations in the United States as well as data design standards and electronic signature laws. We also offer recommendations for blockchain developers, researchers, and research organizations for achieving compliant blockchain solutions in clinical research.
Shantanu Pal, Tahiry Rabehaja, Ambrose Hill, Michael Hitchens · 5 authors
With the advancement of the Internet of Things (IoT) in recent years, there is a bigger potential to use online services than ever before. The use of the IoT brings numerous opportunities for both service providers and end users, however, it faces critical questions of security and privacy. Toward this, access control is one of the significant security challenges for the IoT, in particular, considering the characteristics of such IoT systems. To develop a secure access control architecture for the IoT, the propagation of access right delegation is a major issue. Many proposals present access control issues for the IoT but given the specific context of access right delegation, it is still in its infancy. This article presents an approach to address such a delegation issue for the IoT using the blockchain technology. We propose a delegation model that employv the critical issues, e.g., the use of nonunique identities, asynchronous and flexible delegation nature of communication for the IoT without the need of a centralized system. The goal of our primitive is to use attributes for validating the identity of an entity instead of relying on a concrete unique identity of an entity. To provide privacy for the attributes, we propose a dual blockchain architecture that moves the attribute storage and access of the public blockchain and onto a secure private blockchain. To demonstrate the feasibility of our proposed approach, we evaluate the system performances using the Ethereum blockchain network.
Wouter Lueks, Bogdan Kulynych, Jules Fasquelle, Simon Le Bail-Collet · 5 authors
Zero-knowledge proofs are an essential building block in many privacy-preserving systems. However, implementing these proofs is tedious and error-prone. In this paper, we present zksk, a well-documented Python library for defining and computing sigma protocols: the most popular class of zero-knowledge proofs. In zksk, proofs compose: programmers can convert smaller proofs into building blocks that then can be combined into bigger proofs. zksk features a modern Python-based domain-specific language. This makes possible to define proofs without learning a new custom language, and to benefit from the rich Python syntax and ecosystem. The library is available at https://github.com/spring-epfl/zksk
Organized surveillance, especially by governments poses a major challenge to individual privacy, due to the resources governments have at their disposal, and the possibility of overreach. Given the impact of invasive monitoring, in most democratic countries, government surveillance is, in theory, monitored and subject to public oversight to guard against violations. In practice, there is a difficult fine balance between safeguarding individual's privacy rights and not diluting the efficacy of national security investigations, as exemplified by reports on government surveillance programs that have caused public controversy, and have been challenged by civil and privacy rights organizations. Surveillance is generally conducted through a mechanism where federal agencies obtain a warrant from a federal or state judge (e.g., the US FISA court, Supreme Court in Canada) to subpoena a company or service-provider (e.g., Google, Microsoft) for their customers' data. The courts provide annual statistics on the requests (accepted, rejected), while the companies provide annual transparency reports for public auditing. However, in practice, the statistical information provided by the courts and companies is at a very high level, generic, is released after-the-fact, and is inadequate for auditing the operations. Often this is attributed to the lack of scalable mechanisms for reporting and transparent auditing. In this paper, we present SAMPL, a novel auditing framework which leverages cryptographic mechanisms, such as zero knowledge proofs, Pedersen commitments, Merkle trees, and public ledgers to create a scalable mechanism for auditing electronic surveillance processes involving multiple actors. SAMPL is the first framework that can identify the actors (e.g., agencies and companies) that violate the purview of the court orders. We experimentally demonstrate the scalability for SAMPL for handling concurrent monitoring processes without undermining their secrecy and auditability.
Samuel Steffen, Benjamin Bichsel, Mario Gersbach, Noa Melchior · 6 authors
Privacy concerns of smart contracts are a major roadblock preventing their wider adoption. A promising approach to protect private data is hiding it with cryptographic primitives and then enforcing correctness of state updates by Non-Interactive Zero-Knowledge (NIZK) proofs. Unfortunately, NIZK statements are less expressive than smart contracts, forcing developers to keep some functionality in the contract. This results in scattered logic, split across contract code and NIZK statements, with unclear privacy guarantees. To address these problems, we present the zkay language, which introduces privacy types defining owners of private values. zkay contracts are statically type checked to (i) ensure they are realizable using NIZK proofs and (ii) prevent unintended information leaks. Moreover, the logic of zkay contracts is easy to follow by just ignoring privacy types. To enforce zkay contracts, we automatically transform them into contracts equivalent in terms of privacy and functionality, yet executable on public blockchains. We evaluated our approach on a proof-of-concept implementation generating Solidity contracts and implemented 10 interesting example contracts in zkay. Our results indicate that zkay is practical: On-chain cost for executing the transformed contracts is around 1M gas per transaction (~0.50US$) and off-chain cost is moderate.
While fair exchange of goods is known to be impossible without assuming a trusted party, smart contracts in cryptocurrencies forgo such parties by assuming trust in the currency system. They allow a seller to sell a digital good, which the buyer will obtain if and only if she pays. Zero-knowledge contingent payments (zkCP) show that, despite the limited expressiveness of its scripting language, this is even possible in Bitcoin by using zero-knowledge proofs. At CCS'17, Campanelli, Gennaro, Goldfeder and Nizzardo showed that the zkCP protocol was flawed, in that the buyer could obtain information about the good without paying. They proposed countermeasures to repair zkCP and moreover observed that zkCP cannot be used when a service is sold. They introduce the notion of ZK contingent payments for services and give an instantiation based on a witness-indistinguishable (WI) proof system. We show that some of their proposed countermeasures are not sufficient by presenting an attack against their fixed zkCP scheme. We also show that their realization of zkCP for services is insecure, as the buyer could learn the desired information (i.e., whether the service was provided) without paying; in particular, we show that WI of the used proof system is not enough.
Russell W. F. Lai, Viktoria Ronge, Tim Ruffing, Dominique Schröder · 6 authors
Monero is the largest cryptocurrency with built-in cryptographic privacy features. The transactions are authenticated using zero-knowledge spend proofs, which provide a certain level of anonymity by hiding the source accounts from which the funds are sent among a set of other accounts. Due to its similarities to ring signatures, this core cryptographic component is called Ring Confidential Transactions (RingCT). Because of its practical relevance, several works attempt to analyze the security of RingCT. Since RingCT is rather complex, most of them are either informal, miss fundamental functionalities, or introduce undesirable trusted setup assumptions. Regarding efficiency, Monero currently deploys a scheme in which the size of the spend proof is linear in the ring size. This limits the ring size to only a few accounts, which in turn limits the acquired anonymity significantly and facilitates de-anonymization attacks. As a solution to these problems, we present the first rigorous formalization of RingCT as a cryptographic primitive. We then propose a generic construction of RingCT and prove it secure in our formal security model. By instantiating our generic construction with new efficient zero-knowledge proofs, we obtain Omniring, a fully-fledged RingCT scheme in the discrete logarithm setting that provides the highest concrete and asymptotic efficiency as of today. Omniring is the first RingCT scheme which 1) does not require a trusted setup or pairing-friendly elliptic curves, 2) has a proof size logarithmic in the size of the ring, and 3) allows to share the same ring between all source accounts in a transaction, thereby enabling significantly improved privacy level without sacrificing performance. Our zero-knowledge proofs rely on novel enhancements to the Bulletproofs framework (S&P 2018), which we believe are of independent interest.