Victor Youdom Kemmoe, W. H. Stone, Jeehyeong Kim, Daeyoung Kim · 5 authors
Smart contracts, as an added functionality to blockchain, have received increased attention recently. They are executable programs whose instance and state are stored in blockchain. Hence, smart contracts and blockchain enable a trustable, trackable, and irreversible protocol without the need for trusted third parties which generally constitute a single point of failure. If a user creates and distributes a smart contract, others will be able to interact with it while the underlying blockchain ensures a trustable execution. In this paper, we aim to introduce state-of-the-art technologies of the smart contract protocol. We firstly introduce the history of blockchain and smart contracts followed by their step-by-step operations. Then, we introduce the survey results which are classified into four categories based on their purposes: cryptography, access management, social application, and smart contract structure. By presenting the most recent knowledge, this paper will contribute to the advances and proliferation of smart contracts.
We report our experience in the formal verification of the deposit smart contract, whose correctness is critical for the security of Ethereum 2.0, a new Proof-of-Stake protocol for the Ethereum blockchain. The deposit contract implements an incremental Merkle tree algorithm whose correctness is highly nontrivial, and had not been proved before. We have verified the correctness of the compiled bytecode of the deposit contract to avoid the need to trust the underlying compiler. We found several critical issues of the deposit contract during the verification process, some of which were due to subtle hidden bugs of the compiler.
Blockchain is a technology used with the series of users in peer-to-peer transactions to utilize the usability properties of the immutable data records. The distributed nature of this technology has given the wide acceptance to its range of applications in various sectors. Seeing the prospect of this new technology, we have chosen the field of human resource management as these data needs to be privacy preserving and confidential along with significant research value. Distributed ledger approach is a novel idea in this field of work specifically for the application of human resource records management. We have used a privacy preserving framework that provides a transparent system for human resource record management. Wallets are generated with organization id and outputting with public-private key pair along with privacy parameter mapping with hash. Keys are used to provide confidentiality, integrity and authentication. Smart contract uses distributed but converged decision with privacy level classification. Performance of the proposed work has been measured based on time, memory consumptions, failure point identification and read-write latencies. The analysis of the results confirms the efficiency of the system.
Hamda Al Breiki, Muhammad Habib ur Rehman, Khaled Salah, Davor Svetinović
The essence of blockchain smart contracts lies in the execution of business logic code in a decentralized architecture in which the execution outcomes are trusted and agreed upon by all the executing nodes. Despite the decentralized and trustless architectures of the blockchain systems, smart contracts on their own cannot access data from the external world. Instead, smart contracts interact with off-chain external data sources, called oracles, whose primary job is to collect and provide data feeds and input to smart contracts. However, there is always risk of oracles providing corrupt, malicious, or inaccurate data. In this paper, we analyze and present the notion of trust in the oracles used in blockchain ecosystems. We analyze and compare trust-enabling features of the leading blockchain oracle approaches, techniques, and platforms. Moreover, we discuss open research challenges that should be addressed to ensure secure and trustworthy blockchain oracles.
Blockchain and other Distributed Ledger Technologies (DLTs) have evolved significantly in the last years and their use has been suggested for numerous applications due to their ability to provide transparency, redundancy and accountability. In the case of blockchain, such characteristics are provided through public-key cryptography and hash functions. However, the fast progress of quantum computing has opened the possibility of performing attacks based on Grover's and Shor's algorithms in the near future. Such algorithms threaten both public-key cryptography and hash functions, forcing to redesign blockchains to make use of cryptosystems that withstand quantum attacks, thus creating which are known as post-quantum, quantum-proof, quantum-safe or quantum-resistant cryptosystems. For such a purpose, this article first studies current state of the art on post-quantum cryptosystems and how they can be applied to blockchains and DLTs. Moreover, the most relevant post-quantum blockchain systems are studied, as well as their main challenges. Furthermore, extensive comparisons are provided on the characteristics and performance of the most promising post-quantum public-key encryption and digital signature schemes for blockchains. Thus, this article seeks to provide a broad view and useful guidelines on post-quantum blockchain security to future blockchain researchers and developers.
Blockchain technologies are becoming more popular in securing the sensitive data such as government holding citizens’ s wealth, health and personal information. A blockchain is a shared encrypted data of records, consisting of a ledger of transactions. As the data stored in blockchain is tamper proof, it is proposed to implement new Aadhar enrolments with P2P Blockchains and migrate the existing centralized Aadhar personnel’s personal data from the conventional RDBMS / Big data system repositories to distributed ledger technologies by creating private blockchains. In this paper, we will discuss how to provide security for Aadhar card enrolment data using blockchain architectures. A blockchain-based Aadhaar would help UIDAI in truly complying with the data protection and privacy stipulations outlined in the Right to Privacy Act judgment
A deletable blockchain has been proposed recently to change the immutability of the traditional blockchain. However, the users' identities and transaction contents are all public in the scheme, and the public data may reveal the users' privacy. In order to protect the privacy of the users, we propose a privacy-protected deletable blockchain based on the proof-of-space consensus mechanism, which does not rely on complex cryptographic tools or any trusted party. In order to satisfy full transparency and accountability in an anonymous environment, we use a traceable ring signature or a Pedersen commitment scheme to disclose the users' real identities or the real transaction contents respectively according to different deletion reasons. During the deletion process, we propose a linkable multi-signature scheme, which allows multiple users to generate a valid signature by using their one-time addresses as pseudonyms to protect their identity privacy. Moreover, the proposed multi-signature scheme can link two sub-signatures if they are generated by the same malicious user. Finally, we simulate the generation and deletion process of a block under the proof-of-space consensus mechanism and give the time of generating and deleting a block. The experimental results prove the efficiency and feasibility of our proposed scheme.
Cloud computing is an information technology that enables different users to access a shared pool of configurable system resources and different services without physically acquiring them. Most industries nowadays such as banking, healthcare and education are migrating to the cloud due to its efficiency of services especially when it comes to data security and integrity. Cloud platforms encounter numerous challenges such as Data deduplication, Data Transmission, Data Integrity, VM Security, Data Availability, Bandwidth usage… etc. In this paper we have adopted the Blockchain technology - which is a relatively new technology - that emerged for the first time as the cryptocurrency Bitcoin and proved its efficiency in securing data and assuring data integrity. It is mostly a distributed public ledger that holds transactions data in case of Bitcoin. In our work blockchains are adopted in a different way than its regular use in bitcoin. Three of the major challenges in Cloud Computing and Cloud services are Data Deduplication, Storage and Bandwidth usage are discussed in this paper.
Nowadays, with rapid advancements of vehicular telematics and communication techniques, proliferation of vehicular ad hoc networks (VANETs) have been witnessed, which facilitates the construction of promising intelligent transportation system (ITS). Due to inherent wireless communicating features in open environment, secure transmission among numerous VANET entities remains crucial issues. Currently, lots of research efforts have been made, while most of which tend to allocate the universal group key to the verified devices for both vehicle-to-vehicle (V2V) and vehicle-to-RSU (V2R) communications. However, in heterogeneous VANET environment with large numbers of devices in same vehicular group, complicated and variable topologies lead to continuous key updating in every moment, causing interference to regular V2R data exchange, which is not reliable and efficient for resource-constrained VANET environment. Moreover, group membership recording and detecting mechanisms are necessary for real time vehicle revocation and participation, which has not been further studied so far. In this paper, we address the above issues by proposing a secure authentication and key management scheme. In our design, novel VANET system model with edge computing infrastructure is adopted so as to offer adequate computing and storing capacity compared to traditional VANET structure. Note that our certificateless authentication scheme applies the independent session key for each vehicle for interference avoidance. Furthermore, consortium blockchain is employed for V2V group key construction. Real time group membership arrangement with efficient group key updating is accordingly provided. Formal security proofs are presented, demonstrating that the proposed scheme can achieve desired security properties. Performance analysis is conducted as well, proving that the proposed scheme is efficient compared with the state-of-the-arts.
The blockchain data structure maintained via the longest-chain rule—popularized by Bitcoin—is a powerful algorithmic tool for consensus algorithms. Such algorithms achieve consistency for blocks in the chain as a function of their depth from the end of the chain. While the analysis of Bitcoin guarantees consistency with error 2−k for blocks of depth O(k), the state-of-the-art of proof-of-stake (PoS) blockchains suffers from a quadratic dependence on k: these protocols, exemplified by Ouroboros (Crypto 2017), Ouroboros Praos (Eurocrypt 2018) and Sleepy Consensus (Asiacrypt 2017), can only establish that depth Θ(k2) is sufficient. Whether this quadratic gap is an intrinsic limitation of PoS—due to issues such as the nothing-at-stake problem—has been an urgent open question, as deployed PoS blockchains further rely on consistency for protocol correctnes. We give an axiomatic theory of blockchain dynamics that permits rigorous reasoning about the longest-chain rule and achieve, in broad generality, Θ(k) dependence on depth in order to achieve consistency error 2−k In particular, for the first time we show that PoS protocols can match proof-of-work protocols for linear consistency. We analyze the associated stochastic process, give a recursive relation for the critical functionals of this process, and derive tail bounds in both i.i.d. and martingale settings via associated generating functions.
Guntur Dharma Putra, Volkan Dedeoglu, Salil S. Kanhere, Raja Jurdak
Heterogeneous and dynamic IoT environments require a lightweight, scalable, and trustworthy access control system for protection from unauthorized access and for automated detection of compromised nodes. Recent proposals in IoT access control systems have incorporated blockchain to overcome inherent issues in conventional access control schemes. However, the dynamic interaction of IoT networks remains uncaptured. Here, we develop a blockchain based Trust and Reputation System (TRS) for IoT access control, which progressively evaluates and calculates the trust and reputation score of each participating node to achieve a self-adaptive and trustworthy access control system. Trust and reputation are explicitly incorporated in the attribute-based access control policy, so that different nodes can be assigned to different access right levels, resulting in dynamic access control policies. We implement our proposed architecture in a private Ethereum blockchain comprised of a Docker container network. We benchmark our solution using various performance metrics to highlight its applicability for IoT contexts.
In fifth-generation (5G) networks and beyond, communication latency and network bandwidth will be no longer be bottlenecks to mobile users. Thus, almost every mobile device can participate in distributed learning. That is, the availability issue of distributed learning can be eliminated. However, model safety will become a challenge. This is because the distributed learning system is prone to suffering from byzantine attacks during the stages of updating model parameters and aggregating gradients among multiple learning participants. Therefore, to provide the byzantine-resilience for distributed learning in the 5G era, this article proposes a secure computing framework based on the sharding technique of blockchain, namely PiRATE. To prove the feasibility of the proposed PiRATE, we implemented a prototype. A case study shows how the proposed PiRATE contributes to distributed learning. Finally, we also envision some open issues and challenges based on the proposed byzantine- resilient learning framework.
This paper proposes SilentDelivery, a secure, scalable and cost-efficient protocol for implementing timed information delivery service in a decentralized blockchain network. SilentDelivery employs a novel combination of threshold secret sharing and decentralized smart contracts. The protocol maintains shares of the decryption key of the private information of an information sender using a group of mailmen recruited in a blockchain network before the specified future time-frame and restores the information to the information recipient at the required time-frame. To tackle the key challenges that limit the security and scalability of the protocol, SilentDelivery incorporates two novel countermeasure strategies. The first strategy, namely silent recruitment, enables a mailman to get recruited by a sender silently without the knowledge of any third party. The second strategy, namely dual-mode execution, makes the protocol run in a lightweight mode by default, where the cost of running smart contracts is significantly reduced. We rigorously analyze the security of SilentDelivery and implement the protocol over the Ethereum official test network. The results demonstrate that SilentDelivery is more secure and scalable compared to the state of the art and reduces the cost of running smart contracts by 85%.
Abstract Background With the advent of precision medicine, pharmacogenomics data is becoming increasingly critical to patient care. These data describe the relationship between a particular variant in the genome and the response to a drug by the patient. As utilizing this kind of data becomes more integral to medical treatment decisions, appropriate storage and sharing of this data will be critical. A potential way of securely storing and sharing pharmacogenomics data is a smart contract with the Ethereum blockchain. This is an open-source blockchain platform for decentralized applications. A transaction-based, state machine, the “world” of Ethereum maintains user accounts and storage in a network state. Immutable pieces of code called “smart contracts” may be deployed to the Ethereum network and run on the Ethereum Virtual Machine when called by a user or other contract. The 2019 iDASH (Integrating Data for Analysis, Anonymization, and Sharing) competition for Secure Genome Analysis challenged participants to develop time- and space-efficient smart contracts to log and query gene-drug relationship data on the Ethereum blockchain. Methods We designed a smart contract to store and query pharmacogenomics data (gene-drug interaction data) in Ethereum using an index-based, multi-mapping approach allowing for time and space efficient storage and query. Our solution to the IDASH competition ranked in the top three at a workshop held in Bloomington, IN in October 2019. Although our solution performed well in the challenge, we wanted to improve its scalability and query efficiency. To that end, we developed an alternate “fastQuery” solution that stores pooled rather than raw data, allowing for significantly improved query time for 0-AND queries, and constant query time for 1- and 2-AND queries. Results We tested the performance of both of our solutions in Truffle (v5.0.31) using datasets ranging from 100 to 1000 entries, and inserting data at 25, 50, 100, and 200 observations at a time. On a private, proof-of-authority test network, our challenge solution requires approximately 70 seconds, 500 MB of memory, and 80 MB of disk space to insert 1000 entries (200 at a time); and 400 ms and 5 MB of memory to query a two-AND query from 1000 entries. This solution exhibits constant memory for insertion and querying, and linear query time. Our alternate fastQuery solution requires approximately 60 seconds, 500 MB of memory, and 80 MB of disk space to insert 1000 entries (200 at a time); and 83 ms and 5 MB of memory to query a two-AND query from 1000 entries. This solution exhibits constant memory for insertion and querying, linear query time for 0-AND queries, and constant query time for 1- and 2-AND queries in a database of up to 1000 entries. Conclusion In this study we showed that pharmacogenomics data can be stored and queried efficiently on the Ethereum blockchain. Our approach has the potential to be useful for a wide range of datasets in biomedical research; while we focused on gene-drug interaction data, our solution designs could be used to store a range of clinical trial data. Moreover, our solutions could be adapted to store and query data in any field where high-integrity data storage and efficient access is required.
Benjamin S. Glicksberg, Shohei Burns, Robert Currie, A. Clark Griffin · 8 authors
BACKGROUND: Efficiently sharing health data produced during standard care could dramatically accelerate progress in cancer treatments, but various barriers make this difficult. Not sharing these data to ensure patient privacy is at the cost of little to no learning from real-world data produced during cancer care. Furthermore, recent research has demonstrated a willingness of patients with cancer to share their treatment experiences to fuel research, despite potential risks to privacy. OBJECTIVE: The objective of this study was to design, pilot, and release a decentralized, scalable, efficient, economical, and secure strategy for the dissemination of deidentified clinical and genomic data with a focus on late-stage cancer. METHODS: We created and piloted a blockchain-authenticated system to enable secure sharing of deidentified patient data derived from standard of care imaging, genomic testing, and electronic health records (EHRs), called the Cancer Gene Trust (CGT). We prospectively consented and collected data for a pilot cohort (N=18), which we uploaded to the CGT. EHR data were extracted from both a hospital cancer registry and a common data model (CDM) format to identify optimal data extraction and dissemination practices. Specifically, we scored and compared the level of completeness between two EHR data extraction formats against the gold standard source documentation for patients with available data (n=17). RESULTS: Although the total completeness scores were greater for the registry reports than those for the CDM, this difference was not statistically significant. We did find that some specific data fields, such as histology site, were better captured using the registry reports, which can be used to improve the continually adapting CDM. In terms of the overall pilot study, we found that CGT enables rapid integration of real-world data of patients with cancer in a more clinically useful time frame. We also developed an open-source Web application to allow users to seamlessly search, browse, explore, and download CGT data. CONCLUSIONS: Our pilot demonstrates the willingness of patients with cancer to participate in data sharing and how blockchain-enabled structures can maintain relationships between individual data elements while preserving patient privacy, empowering findings by third-party researchers and clinicians. We demonstrate the feasibility of CGT as a framework to share health data trapped in silos to further cancer research. Further studies to optimize data representation, stream, and integrity are required.
A blockchain is a Distributed Ledger Technology that has been defined as a “distributed, shared, encrypted database that serves as an irreversible and incorruptible repository of information. Blockchain can be defined as a peer-to-peer distributed ledger that is cryptographically secure, append-only, immutable and updatable only via consensus or agreement among peers. In blockchain platforms, each transaction in the public ledger is verified by consensus of the majority of the system participants in a transparent and secure way. The consensus algorithm refers to the process of attaining an unified agreement on the state of the network in a decentralized way and to facilitate the verification and validation of information being added to the blockchain. This paper aims at providing a comparison between most of the recent consensus algorithms regarding the scalability of the algorithm; the type of blockchain, node identity, the performance of the algorithm (in terms of throughput & latency) and Adversial Tolerance and to deliver a solid basis for discussions about current statistics. In this research, we also presented a new category of the Blockchain consensus algorithms, which consist of three groups as follows; the proof based on Hardware, the proof based on stake, and the proof based on voting.
Credential fraud is a widespread practice that undermines investment and confidence in higher education systems and bears significant economic and social costs. Legacy credential verification systems are typically time-consuming, costly, and bureaucratic, and struggle against certain classes of credential fraud. In this paper, we propose a comprehensive blockchain-based credential verification solution, Cerberus, which is considerably more efficient, easy and intuitive to use, and effectively mitigates widespread manifestations of credential fraud. Cerberus also improves significantly upon other blockchain-based solutions in the research literature: it adheres closely to the existing credential verification ecosystem, it addresses a threat model informed by real-world fraud scenarios. Moreover, Cerberus uses on-chain smart contracts for credential revocation, and it does not entail students or employers to manage digital identities or cryptographic credentials to use the system. We prototype our solution and describe our attempt to design an online verification service with a rich feature set, including data privacy, transcript verification, and selective disclosure of data. We hope this effort contributes positively to towards alleviating the problem of fake credentials.
With the digitization of traditional medical records, medical institutions encounter difficult problems, such as electronic health record storage and sharing. Patients and doctors spend considerable time querying the required data when accessing electronic health records, but the obtained data are not necessarily correct, and access is sometimes restricted. On this basis, this study proposes a medical data sharing scheme based on permissioned blockchains, which use ciphertext-based attribute encryption to ensure data confidentiality and access control of medical data. Under premise of ensuring patient identity privacy, a polynomial equation is used to achieve an arbitrary connection of keywords, and then blockchain technology is combined. In addition, the proposed scheme has keyword-indistinguishability against adaptive chosen keyword attacks under the random oracle model. Analysis shows that the scheme has high retrieval efficiency.
For the modern world where data is becoming one of the most valuable assets,\nrobust data privacy policies rooted in the fundamental infrastructure of\nnetworks and applications are becoming an even bigger necessity to secure\nsensitive user data. In due course with the ever-evolving nature of newer\nstatistical techniques infringing user privacy, machine learning models with\nalgorithms built with respect for user privacy can offer a dynamically adaptive\nsolution to preserve user privacy against the exponentially increasing\nmultidimensional relationships that datasets create. Using these privacy aware\nML Models at the core of a Federated Learning Ecosystem can enable the entire\nnetwork to learn from data in a decentralized manner. By harnessing the\never-increasing computational power of mobile devices, increasing network\nreliability and IoT devices revolutionizing the smart devices industry, and\ncombining it with a secure and scalable, global learning session backed by a\nblockchain network with the ability to ensure on-device privacy, we allow any\nInternet enabled device to participate and contribute data to a global privacy\npreserving, data sharing network with blockchain technology even allowing the\nnetwork to reward quality work. This network architecture can also be built on\ntop of existing blockchain networks like Ethereum and Hyperledger, this lets\neven small startups build enterprise ready decentralized solutions allowing\nanyone to learn from data across different departments of a company, all the\nway to thousands of devices participating in a global synchronized learning\nnetwork.\n
Participatory sensing is gaining popularity as a method for collecting and sharing information from distributed local environments using sensor-rich mobile devices. There are a number of participatory sensing applications currently in wide use, such as location-based service applications (e.g., Waze navigation). Usually, these participatory applications collect tremendous amounts of sensing data containing personal information, including user identity and current location. Due to the high sensitivity of this information, participatory sensing applications need a privacy-preserving mechanism, such as anonymity, to secure and protect personal user data. However, using anonymous identifiers for sensing sources proves difficult when evaluating sensing data trustworthiness. From this perspective, a successful participatory sensing application must be designed to consider two challenges: (1) user privacy and (2) data trustworthiness. To date, a number of privacy-preserving reputation techniques have been proposed to satisfy both of these issues, but the protocols contain several critical drawbacks or are impractical in terms of implementation. In particular, there is no work that can transparently manage user reputation values while also tracing anonymous identities. In this work, we present a blockchain-based privacy-preserving reputation framework called BPRF to transparently manage user reputation values and provide a transparent tracing process for anonymous identities. The performance evaluation and security analysis show that our solution is both practical and able to satisfy the two requirements for user privacy and data trustworthiness.
Amir Teshome Wonjiga, Sean Peisert, Louis Rilling, Christine Morin
Migrating an application from local compute resources to commercial cloud resources involves giving up full control of the physical infrastructure, as the cloud service provider (CSP) is responsible for managing the physical infrastructure, including its security. The reliance of a tenant on a CSP can create a trust issue around whether the CSP is upholding its end of the bargain. CSPs acknowledge this and provide a guarantee through a Service Level Agreement (SLA). SLAs need to be verified for satisfaction of the defined objectives. To avoid raising the trust issue again, such a verification procedure needs to be unbiased and independently achievable by both tenants and CSPs without one relying on the other party. In this paper, we consider an SLA offered by the provider that guarantees the integrity of tenants' data, and propose to verify the SLA using an integrity checking method based on a distributed ledger. Our proposed method allows both CSPs and tenants to perform integrity checking without one party relying on the other. The method uses a blockchain as a distributed ledger to store evidence of data integrity. Assuming the ledger as a secure, trusted source of information, the evidence can be used to resolve conflicts between providers and tenants. In addition, we present a prototype implementation and an experimental evaluation to show the feasibility of our verification method and to measure the time overhead.
Statistical analysis of health data is an essential task in healthcare. However, existing healthcare systems are incompatible with this critical need due to privacy restrictions. A recently emerged technology called Blockchain has shown great promise for mitigating this incompatibility. In this work, we aim to improve existing secure statistical analysis protocols by leveraging the blockchain technology. We propose a novel method that enables researchers to perform statistical analysis on health data in a privacy-preserving, secure, and precise manner.
Muntadher Sallal, Steve Schneider, Matthew Casey, Constantin Cătălin Drăgan · 9 authors
Online voting in the UK generally takes place without verifiability mechanisms, with providers that are trusted to provide ballot privacy and correctness of the result. However, replacing existing systems with verifiable voting systems with brand new algorithms and code presents a business risk to election providers. We present an approach for incremental change: adding a Selene-based verifiability layer to an existing online voting system. Selene is a verifiable e-voting protocol that publishes votes in plaintext alongside tracking numbers that enable voters to confirm that their votes have been captured correctly by the system. This results in a system where even the election authority running the system cannot change the result in an undetectable way. This gives stronger guarantees on the integrity of the election than were previously present. This gives an end-to-end verifiable system we call Verify My Vote (VMV). In addition, we outline how this approach supports further incremental changes towards the deployment of fully trustworthy online voting systems. The paper also describes the use of distributed ledger technology as a component of VMV to manage the verifiability data in a decentralised way for resilience and trust.
With the wide application of cloud storage, cloud security has become a crucial concern. Related works have addressed security issues such as data confidentiality and integrity, which ensure that the remotely stored data are well maintained by the cloud. However, how to define zero-knowledge proof algorithms for stored data integrity check has not been formally defined and investigated. We believe that it is important that the cloud server is unable to reveal any useful information about the stored data. In this paper, we introduce a novel definition of data privacy for integrity checks, which describes very high security of a zero-knowledge proof. We found that all other existing remote integrity proofs do not capture this feature. We provide a comprehensive study of data privacy and an integrity check algorithm that captures data integrity, confidentiality, privacy, and soundness.