Nida Khan, Abdelkader Lahmadi, Zsófia Kräussl, Radu State
Blockchain has emerged as a novel solution addressing a plethora of industrial issues in domains spanning from financial to educational. However, several challenges restrict the widespread adoption of the technology and data privacy, with throughput and scalability issues, ranks amongst the foremost. In this paper, we introduce a novel privacy management plane which integrates differential privacy to query existing relational databases through the blockchain as well as spearheads the use of blockchain for local differential privacy. The distinguishing feature in the latter is that the privacy management plane gives the data owners the right to perturb their data with the desired privacy budget, while in the former it gives the right to the data curator to change the privacy budget dynamically while answering queries through the blockchain. The paper also includes experimental evaluation of the developed privacy management plane and integrates management operations in it through another smart contract. The paper addresses the issue of GDPR and it's implications in the context of blockchain data, while highlighting the compliance of the proposed implementation.
Dara Tith, Joong-Sun Lee, H. Suzuki, W. M. A. B. Wijesundara · 7 authors
OBJECTIVES: Currently, patients' consent is essential to use their medical records for various purposes; however, most people give their consent using paper forms and have no control over it. Healthcare organizations also have difficulties in dealing with patient consent. The objective of this research is to develop a system for patients to manage their consent flexibly and for healthcare organizations to obtain patient consent efficiently for a variety of purposes. METHODS: We introduce a new e-consent model, which uses a purpose-based access control scheme; it is implemented by a blockchain system using Hyperledger Fabric. All metadata of patient records, consents, and data access are written immutably on the blockchain and shared among participant organizations. We also created a blockchain chaincode that performs business logic managing patient consent. RESULTS: We developed a prototype and checked business logics with the chaincode by validating doctors' data access with purpose-based consent of patients stored in the blockchain. The results demonstrate that our system provides a fine-grained way of handling medical staff 's access requests with diverse intended purposes for accessing data. In addition, patients can create, update, and withdraw their consents in the blockchain. CONCLUSIONS: Our consent model is a solution for consent management both for patients and healthcare organizations. Our system, as a blockchain-based solution that provides high reliability and availability with transparency and traceability, is expected to be used not only for patient data sharing in hospitals, but also for data donation for biobank research purposes.
Although blockchain, the supporting technology of Bitcoin and various cryptocurrencies, has offered a potentially effective framework for numerous applications, it still suffers from the adverse affects of the impossibility triangle. Performance, security, and decentralization of blockchains normally do not scale simultaneously with the number of participants in the network. The recent introduction of error correcting codes in sharded blockchain by Li et al. partially settles this trilemma, boosting throughput without compromising security and decentralization. In this paper, we improve the coded sharding scheme in three ways. First, we propose a novel 2-Dimensional Sharding strategy, which inherently supports cross-shard transactions, alleviating the need for complicated inter-shard communication protocols. Second, we employ distributed storage techniques in the propagation of blocks, improving latency under restricted bandwidth. Finally, we incorporate polynomial cryptographic primitives of low degree, which brings coded blockchain techniques into the realm of feasible real-world parameters.
The problem of fair exchange consists of interchanging goods between two parties that do not trust each other. Despite known impossibility results, recent works leverage the block-chain and zero-knowledge proofs to implement zero-knowledge contingent payment (zkCP) systems that make fair exchange of digital goods possible. Implementing these systems in a secure and efficient way is a big challenge, as evidenced by several unsuccessful attempts from the literature. Campanelli et al. (ACM CCS 2017) discovered a vulnerability on an existing zkCP proposal based on SNARKs (succinct non-interactive arguments of knowledge) and suggested several repairs. Fuchsbauer (ACM CCS 2019) found a flaw in the mentioned countermeasures. In particular, he showed that witness-indistinguishability (WI) is not sufficient for the zkCP schemes proposed by Campanelli et al. to be secure. In this work, we observe that a slightly stronger notion of WI, that we coin trapdoor subversion WI (tS-WI), rules out Fuchsbauer's attack. We formally define security properties for CP systems and show that, under tS-WI, Campanelli et al.'s proposal indeed satisfies these properties. Additionally, we explore alternative approaches to implement ZK (other than SNARKs) and develop a prototype, using it to demonstrate their potential. Our new ideas result in a protocol to sell ECDSA signatures with contingent payment that can be executed in less than $150$ milliseconds over a LAN network.
This paper follows the line of works that design concretely efficient transparent sublinear zero-knowledge Interactive Oracle Proofs (IOP). Arguments obtained via this paradigm have the advantages of not relying on public-key cryptography, not requiring a trusted setup, and resistance to known quantum attacks. In the realm of transparent systems, Ligero and Aurora stand out with incomparable advantages where the former has a fast prover algorithm somewhat succinct proofs and the latter has somewhat fast prover and succinct proofs. In this work, we introduce Ligero++ that combines the best features of both approaches to achieve the best of both worlds. We implement our protocol and benchmark the results.
Zero-Knowledge (ZK) proofs (ZKP) are foundational in cryptography. Most recent ZK research focuses on non-interactive proofs (NIZK) of small statements, useful in blockchain scenarios. Another line, and our focus, instead targets proofs of large statements that are useful, e.g., in proving properties of programs in ZK. We specify a zero-knowledge processor that executes arbitrary programs written in a simple instruction set, and proves in ZK the correctness of the execution. Such an approach is well-suited for constructing ZK proofs of large statements as it efficiently supports complex programming constructs, such as loops and RAM access. Critically, we propose several novel ZK improvements that make our approach concretely efficient: (1) an efficient arithmetic representation with conversions to/from Boolean, (2) an efficient read-only memory that uses $2łog n$ OTs per access, and (3) an efficient read-write memory, øurram, which uses $\frac1 2 łog^2 n$ OTs per access. øurram beats linear scan for RAM of size $>3$ elements! Prior ZK systems used generic ORAM costing orders of magnitude more. We cast our system as a garbling scheme that can be plugged into the ZK protocol of [Jawurek et al, CCS'13]. Put together, our system is concretely efficient: for a processor instantiated with $512$KB of main memory, each processor cycle costs $24$KB of communication. We implemented our approach in \textttC++. On a 1Gbps LAN our implementation realizes a $2.1$KHz processor.
Karl Wüst, Siniša Matetić, Silvan Egli, Kari Kostiainen · 5 authors
Smart contracts are programmable, decentralized and transparent financial applications. Because smart contract platforms typically support Turing-complete programming languages, such systems are often said to enable arbitrary applications. However, the current permissionless smart contract systems impose heavy restrictions on the types of computations that can be implemented. For example, the globally-replicated and sequential execution model of Ethereum requires low gas limits that make many computations infeasible.
Jiaheng Zhang, Zhiyong Fang, Yupeng Zhang, Dawn Song
Machine learning has become increasingly prominent and is widely used in various applications in practice. Despite its great success, the integrity of machine learning predictions and accuracy is a rising concern. The reproducibility of machine learning models that are claimed to achieve high accuracy remains challenging, and the correctness and consistency of machine learning predictions in real products lack any security guarantees. In this paper, we initiate the study of zero knowledge machine learning and propose protocols for zero knowledge decision tree predictions and accuracy tests. The protocols allow the owner of a decision tree model to convince others that the model computes a prediction on a data sample, or achieves a certain accuracy on a public dataset, without leaking any information about the model itself. We develop approaches to efficiently turn decision tree predictions and accuracy into statements of zero knowledge proofs. We implement our protocols and demonstrate their efficiency in practice. For a decision tree model with 23 levels and 1,029 nodes, it only takes 250 seconds to generate a zero knowledge proof proving that the model achieves high accuracy on a dataset of 5,000 samples and 54 attributes, and the proof size is around 287 kilobytes.
5G communications proposed significant improvements over 4G in terms of efficiency and security. Among these novelties, the 5G Network Slicing seems to have a prominent role: deploy multiple virtual network slices, each providing a different service with different needs and features. Like this, a Slice Operator (SO) ruling a specific slice may want to offer a service for users meeting some requirements. It is of paramount importance to provide a robust authentication protocol, able to ensure that users meet the requirements, but providing at the same time a privacy-by-design architecture. This makes even more sense having a growing density of Internet of Things (IoT) devices exchanging private information over the network. In this paper, we improve the 5G network slicing authentication using a Self-Sovereign Identity (SSI) scheme: granting users full control over their data. We introduce an approach to allow a user to prove his right to access a specific service without leaking any information about him. Such an approach is SANS, a protocol that provides non-linkable protection for any issued information, preventing an SO or an eavesdropper from tracking users' activity and relating it with their real identities. Furthermore, our protocol is scalable and can be taken as a framework for improving related technologies in similar scenarios, like authentication in the 5G Radio Access Network (RAN) or other wireless networks and services. Such features can be achieved using cryptographic primitives called Zero-Knowledge Proofs (ZKP). Upon implementing our solution using a state-of-the-art ZKP library and performing several experiments, we provide benchmarks demonstrating that our approach is affordable in speed and memory consumption.
Stanisław Barański, Julian Szymański, Andrzej Sobecki, David Gil · 5 authors
In this paper, we propose a privacy-preserving i-voting system based on the public Stellar Blockchain network. We argue that the proposed system satisfies all requirements stated for a robust i-voting system including transparency, verifiability, and voter anonymity. The practical architecture of the system abstracts a voter from blockchain technology used underneath. To keep user privacy, we propose a privacy-first protocol that protects voter anonymity. Additionally, high throughput and low transaction fees allow handling large scale voting at low costs. As a result we built an open-source, cheap, and secure system for i-voting that uses public blockchain, where everyone can participate and verify the election process without the need to trust a central authority. The main contribution to the field is a method based on a blind signature used to construct reliable voting protocol. The proposed method fulfills all requirements defined for i-voting systems, which is challenging to achieve altogether.
Guendalina Capece, Nathan Levialdi Ghiron, Francesco Pasquale
University certificates can have a significant impact on people’s lives: they can help people get the job they want or allow companies to decide whether a candidate for a job has the appropriate skills. Despite their important social role, current systems for certifying academic achievements are slow, complicated, expensive, and vulnerable to forgery. In the education field, the Blockcerts project, an open source project launched by MIT and Learning Machine in 2016, seems to have the potential to become a new standard for issuing certificates using the Blockchain technology as a platform. It enables students to quickly and easily get a verifiable, tamper-proof version of their diploma. Additionally, the infrastructure provides permanence, convenience, and a level of security appropriate to the importance of the record, guaranteeing the legitimacy of the diploma. The University of Rome “Tor Vergata” started a pilot program in 2018 adopting the Blockcerts framework to issue digital diplomas. In this paper, we describe the whole process from a technical perspective and analyze the impact that a broad adoption of the Blockcerts standard might have, as compared to the current way of issuing diplomas at the University of “Tor Vergata”. Our aim is that our work might contribute to building momentum for the application of the Blockchain technology to digital certificates and stimulate further discussion with other institutions to fully exploit the potential of the technology.
Anders Dalskov, Daniele Lain, Enis Ulqinaku, Kari Kostiainen · 5 authors
Encrypted cloud storage services are steadily increasing in popularity, with many commercial solutions currently available. In such solutions, the cloud storage is trusted for data availability, but not for confidentiality. Additionally, the user's device is considered secure, and the user is expected to behave correctly. We argue that such assumptions are not met in reality: e.g., users routinely forget passwords and fail to make backups, and users' devices get stolen or become infected with malware. Therefore, we consider a more extensive threat model, where users' devices are susceptible to attacks and common human errors are possible. Given this model, we analyze 10 popular commercial services and show that none of them provides good confidentiality and data availability. Motivated by the lack of adequate solutions in the market, we design a novel scheme called Two-Factor Encryption (2FE) that draws inspiration from two-factor authentication and turns file encryption and decryption into an interactive process where two user devices, like a laptop and a smartphone, must interact. 2FE provides strong confidentiality and availability guarantees, as it withstands compromised cloud storage, one stolen or compromised user device at a time, and various human errors. 2FE achieves this by leveraging secret sharing with additional techniques such as oblivious pseudorandom functions and zero-knowledge proofs. We evaluate 2FE experimentally and show that its performance overhead is small. Finally, we explain how our approach can be adapted to other related use cases such as cryptocurrency wallets.
The on-demand mobility market, including ridesharing, is becoming increasingly important with e-hailing fares growing at a rate of approximately 130% per annum since 2013. By increasing utilization of existing vehicles and empty seats, ridesharing can provide many benefits including reduced traffic congestion and environmental impact from vehicle usage and production. However, the safety of riders and drivers has become of paramount concern and a method for privacy-preserving identity verification between untrusted parties is essential for protecting users. To this end, we propose a novel privacy-preserving identity verification system, extending zero-knowledge proof (ZKP) and blockchain for use in ridesharing applications. We design a permissioned blockchain network to perform the ZKP verification of a driver's identity, which also acts as an immutable ledger to store ride logs and ZKP records. For the ZKP module, we design a protocol to facilitate user verification without requiring the exchange of any private information. We prototype the proposed system on the Hyperledger Fabric platform, with the Hyperledger Ursa cryptography library, and conduct extensive experimentation. To measure the prototype's performance, we utilize the Hyperledger Caliper benchmark tool to perform extensive analysis and the results show that our system is suitable for use in real-world ridesharing applications.
Blockchain technology supports building transparent and decentralized systems in which the executed transactions can be easily traceable. Suppose one such system is intended to manage and process personal data. In that case, complementary mechanisms are required that make it possible for the system to comply, for instance, with data protection regulations. This work studies the integration of off-chain capabilities in blockchain-based solutions. In particular, we have focused on mechanisms that support safely moving data or computational operations outside the core blockchain network. We have carried out a thorough analysis of the European data protection regulation and discussed the weaknesses and strengths regarding the security and privacy requirements established by that regulation of solutions built using traditional blockchain technology.As a direct consequence of this study, we have conceived, and present in this paper, a system architecture for the design of privacy-aware solutions that use that kind of technology and put forward a systematic approach for performing a security and privacy threat analysis of one such solution. We illustrate the use of the proposed methodological tools, presenting and discussing the high-level design and security and privacy assessment of a system that provides services to handle, store, and validate digital academic certificates.
Edoardo Puggioni, Arash Shaghaghi, Robin Doss, Salil S. Kanhere
Internet of Things (IoT) devices are being deployed in huge numbers around the world, and often present serious vulnerabilities. Accordingly, delivering regular software updates is critical to secure IoT devices. Manufactures face two predominant challenges in providing software updates to IoT devices: 1) scalability of the current client-server model and 2) integrity of the distributed updates - exacerbated due to the devices' computing power and lightweight cryptographic primitives. Motivated by these limitations, we propose CrowdPatching, a blockchain-based decentralized protocol, allowing manufacturers to delegate the delivery of software updates to self-interested distributors in exchange for cryptocurrency. Manufacturers announce updates by deploying a smart contract (SC), which in turn will issue cryptocurrency payments to any distributor who provides an unforgeable proof-of-delivery. The latter is provided by IoT devices authorizing the SC to issue payment to a distributor when the required conditions are met. These conditions include the requirement for a distributor to generate a zero-knowledge proof, generated with a novel proving system called zk-SNARKs. Compared with related work, CrowdPatching protocol offers three main advantages. First, the number of distributors can scale indefinitely by enabling the addition of new distributors at any time after the initial distribution by manufacturers (i.e., redistribution among the distributor network). The latter is not possible in existing protocols and is not account for. Secondly, we leverage the recent common integration of gateway or Hub in IoT deployments in our protocol to make CrowdPatching feasible even for the more constraint IoT devices. Thirdly, the trustworthiness of distributors is considered in our protocol, rewarding the honest distributors' engagements. We provide both informal and formal security analysis of CrowdPatching using Tamarin Prover.
Edoardo Puggioni, Arash Shaghaghi, Robin Doss, Salil S. Kanhere
We propose CrowdPatching, a blockchain-based decentralized protocol, allowing\nInternet of Things (IoT) manufacturers to delegate the delivery of software\nupdates to self-interested distributors in exchange for cryptocurrency.\nManufacturers announce updates by deploying a smart contract (SC), which in\nturn will issue cryptocurrency payments to any distributor who provides an\nunforgeable proof-of-delivery. The latter is provided by IoT devices\nauthorizing the SC to issue payment to a distributor when the required\nconditions are met. These conditions include the requirement for a distributor\nto generate a zero-knowledge proof, generated with a novel proving system\ncalled zk-SNARKs. Compared with related work, CrowdPatching protocol offers\nthree main advantages. First, the number of distributors can scale indefinitely\nby enabling the addition of new distributors at any time after the initial\ndistribution by manufacturers (i.e., redistribution among the distributor\nnetwork). The latter is not possible in existing protocols and is not account\nfor. Secondly, we leverage the recent common integration of gateway or Hub in\nIoT deployments in our protocol to make CrowdPatching feasible even for the\nmore constraint IoT devices. Thirdly, the trustworthiness of distributors is\nconsidered in our protocol, rewarding the honest distributors' engagements. We\nprovide both informal and formal security analysis of CrowdPatching using\nTamarin Prover.\n
In current healthcare systems, electronic medical records (EMRs) are always located in different hospitals and controlled by a centralized cloud provider. However, it leads to single point of failure as patients being the real owner lose track of their private and sensitive EMRs. Hence, this article aims to build an access control framework based on smart contract, which is built on the top of distributed ledger (blockchain), to secure the sharing of EMRs among different entities involved in the smart healthcare system. For this, we propose four forms of smart contracts for user verification, access authorization, misbehavior detection, and access revocation, respectively. In this framework, considering the block size of ledger and huge amount of patient data, the EMRs are stored in cloud after being encrypted through the cryptographic functions of elliptic curve cryptography (ECC) and Edwards-curve digital signature algorithm (EdDSA), while their corresponding hashes are packed into blockchain. The performance evaluation based on a private Ethereum system is used to verify the efficiency of proposed access control framework in the real-time smart healthcare system.
Federated learning(FL) is a rapidly growing field and many centralized and decentralized FL frameworks have been proposed. However, it is of great challenge for current FL frameworks to improve communication performance and maintain the security and robustness under malicious node attacks. In this paper, we propose Galaxy Federated Learning Framework(GFL), a decentralized FL framework based on blockchain. GFL introduces the consistent hashing algorithm to improve communication performance and proposes a novel ring decentralized FL algorithm(RDFL) to improve decentralized FL performance and bandwidth utilization. In addition, GFL introduces InterPlanetary File System(IPFS) and blockchain to further improve communication efficiency and FL security. Our experiments show that GFL improves communication performance and decentralized FL performance under the data poisoning of malicious nodes and non-independent and identically distributed(Non-IID) datasets.
Dan Boneh, Saba Eskandarian, Lucjan Hanzlik, Nicola Greco
In a Single Secret Leader Election (SSLE), a group of participants aim to randomly choose exactly one leader from the group with the restriction that the identity of the leader will be known to the chosen leader and nobody else. At a later time, the elected leader should be able to publicly reveal her identity and prove that she has won the election. The election process itself should work properly even if many registered users are passive and do not send any messages. Among the many applications of SSLEs, their potential for enabling more efficient proof-of-stake based cryptocurrencies have recently received increased attention.
One of the current challenges in cryptographic research is the development of advanced cryptographic primitives ensuring a high level of confidence. In this thesis, we focus on their design, while proving their security under well-studied algorithmic assumptions.My work grounds itself on the linearity of homomorphic encryption, which allows to perform linear operations on encrypted data. Precisely, I built upon the linearly homomorphic encryption scheme introduced by Castagnos and Laguillaumie at CT-RSA'15. Their scheme possesses the unusual property of having a prime order plaintext space, whose size can essentially be tailored to ones' needs. Aiming at a modular approach, I designed from their work technical tools (projective hash functions, zero-knowledge proofs of knowledge) which provide a rich framework lending itself to many applications.This framework first allowed me to build functional encryption schemes; this highly expressive primitive allows a fine grained access to the information contained in e.g., an encrypted database. Then, in a different vein, but from these same tools, I designed threshold digital signatures, allowing a secret key to be shared among multiple users, so that the latter must collaborate in order to produce valid signatures. Such signatures can be used, among other applications, to secure crypto-currency wallets. Significant efficiency gains, namely in terms of bandwidth, result from the instantiation of these constructions from class groups. This work is at the forefront of the revival these mathematical objects have seen in cryptography over the last few years.
Permissionless blockchain systems, such as Bitcoin, rely on users using their computational power to solve a puzzle in order to achieve a consensus. To incentivise users in maintaining the system, newly minted coins are assigned to the user who solves this puzzle. A hardware race that has hence ensued among the users, has had a detrimental impact on the environment, with enormous energy consumption and increased global carbon footprint. On the other hand, proof of stake systems incentivise coin hoarding as players maximise their utility by holding their stakes. As a result, existing cryptocurrencies do not mimic the day-to-day usability of a fiat currency, but are rather regarded as crypto-assets or investment vectors. In this work we initiate the study of minting mechanisms in cryptocurrencies as a primitive on its own right, and as a solution to prevent coin hoarding we propose a novel minting mechanism based on waiting-time first-price auctions. Our main technical tool is a protocol to run an auction over any blockchain. Moreover, our protocol is the first to securely implement an auction without requiring a semi-trusted party, i.e., where every miner in the network is a potential bidder. Our approach is generically applicable and we show that it is incentive-compatible with the underlying blockchain, i.e., the best strategy for a player is to behave honestly. Our proof-of-concept implementation shows that our system is efficient and scales to tens of thousands of bidders.
The pervasive adoption of Internet-connected digital services has led to a growing concern in the personal data privacy of their customers. On the other hand, machine learning (ML) techniques have been widely adopted by digital service providers to improve operational productivity and customer satisfaction. ML inevitably accesses and processes users' personal data, which could potentially breach the relevant privacy protection regulations if not performed carefully. The situation is exacerbated by the cloud-based implementation of digital services when user data are captured and stored in distributed locations, hence aggregation of the user data for ML could be a serious breach of privacy regulations. In this backdrop, Federated Learning (FL) is an emerging area that allows ML on distributed data without the data leaving their stored location. However, depending on the nature of the digital services, data captured at different locations may carry different significance to the business operation, hence a weighted aggregation will be highly desirable for enhancing the quality of the FL-learned model. Furthermore, to prevent leakage of user data from the aggregated gradients, cryptographic mechanisms are needed to allow secure aggregation of FL. In this paper, we propose a privacy-enhanced FL scheme for supporting secure weighted aggregation. Besides, by devising a verification protocol based on Zero-Knowledge Proof (ZKP), the proposed scheme is capable of guarding against fraudulent messages from FL participants. Experimental results show that our scheme is practical and secure. Compared to existing FL approaches, our scheme achieves secure weighted aggregation with an additional security guarantee against fraudulent messages with an affordable 1.2 times runtime overheads and 1.3 times communication costs.
Large commercial buildings are complex cyber-physical systems containing expensive and critical equipment that ensure the safety and comfort of their numerous occupants. Yet occupant and visitor access to spaces and equipment within these buildings are still managed through unsystematic, inefficient, and human-intensive processes. As a standard practice, long-term building occupants are given access privileges to rooms and equipment based on their organisational roles, while visitors have to be escorted by their hosts. This approach is conservative and inflexible. In this paper, we describe a methodology that can flexibly and securely manage building access privileges for long-term occupants and short-term visitors alike, taking into account the risk associated with accessing each space within the building. Our methodology relies on blockchain smart contracts to describe, grant, audit, and revoke fine-grained permissions for building occupants and visitors, in a decentralised fashion. The smart contracts are specified through a process that leverages the information compiled from Brick and BOT models of the building. We illustrate the proposed method through a typical application scenario in the context of a real office building and argue that it can greatly reduce the administration overhead, while, at the same time, providing fine-grained, auditable access control.CCS Concepts: Security and privacy; Security services; Computer systems organisation; Embedded and cyber-physical systems; Sensors and actuators
An important feature of Proof-of-Work (PoW) blockchains is full dynamic availability, allowing miners to go online and offline while requiring only 50% of the online miners to be honest. Existing Proof-of-stake (PoS), Proof-of-Space and related protocols are able to achieve this property only partially, either putting the additional assumption that adversary nodes to be online from the beginning and no new adversary nodes come online afterwards, or use additional trust assumptions for newly joining nodes.We propose a new PoS protocol PoSAT which can provably achieve dynamic availability fully without any additional assumptions. The protocol is based on the longest chain and uses a Verifiable Delay Function for the block proposal lottery to provide an arrow of time. The security analysis of the protocol draws on the recently proposed technique of Nakamoto blocks as well as the theory of branching random walks. An additional feature of PoSAT is the complete unpredictability of who will get to propose a block next, even by the winner itself. This unpredictability is at the same level of PoW protocols, and is stronger than that of existing PoS protocols using Verifiable Random Functions.