Blockchain Papers

Luis Ibáñez, John Domingue, Pascal Molli

It is our great pleasure to welcome you to the WWW 2018 3rd International Workshop on Linked Data and Distributed Ledgers (LD-DL). We envision the workshop as a forum for researchers and practitioners from Distributed Ledgers and Linked Data to come together to discuss common challenges; propose solutions to shortcomings of existing architectures; and identify synergies for joint initiatives. The ultimate goal is the creation of a Web of Interoperable Ledgers. We received 6 submissions from all around the world. We evaluated them regarding relevance, quality, and novelty, selecting 3 short papers and 1 long paper (66% acceptance rate) --ScienceMiles - Digital currency for researchers--Can Blockchains and Linked Data Advance Taxation? --A distributed database with explicit semantics and chained RDF graphs--When trust saves energy: A Reference Framework for Proof of Trust (PoT) Blockchains. We hope that you will find the tutorial program interesting, providing you with a valuable opportunity to learn and share ideas with other researchers and practitioners from institutions around the world.

Hans-Georg Fill, Felix Haerer

Blockchains permit to store information in a tamper-resistant and irrevocable manner by reverting to distributed computing and cryptographic technologies. The primary purpose is to keep track of the ownership of tangible and intangible assets. In the paper at hand we apply these concepts and technologies to the domain of knowledge management. Based on the explication of knowledge in the form of enterprise models this permits the application of so-called knowledge proofs for a. enabling the transparent monitoring of knowledge evolution, b. tracking the provenance, ownership, and relationships of knowledge in an organization, c. establishing delegation schemes for knowledge management, and d. ensuring the existence of patterns in models via zero-knowledge proofs. To validate the technical feasibility of the approach a first technical implementation is described and applied to a fictitious use case.

Yu Zhuang, Lincoln Sheets, Zon‐Yin Shae, Jeffrey J. P. Tsai · 5 authors

"Blockchain" is a distributed ledger technology originally applied in the financial sector. This technology ensures the integrity of transactions without third-party validation. Its functions of decentralized transaction validation, data provenance, data sharing, and data integration are a good fit for the needs of health information exchange and clinical trials. We investigated the current workflow of Health Information Exchange and clinical trials; conducted design thinking processes with clinicians, trial managers, informaticians, and blockchain professionals; and implemented a private blockchain model to tackle known issues. We used coded Smart Contract regulations to simulate several scenarios in healthcare processes. This proof-of-concept work provides a feasible simulation for potential solutions to monitor clinical trials across different census regions persistently. Various levels of data access privileges have been designed to utilize a suite of customized Smart Contract settings. These settings emulate the workflow protocols for the monitoring entities, trial sponsors, clinical sponsors and participating subjects. Keywords: Blockchain, Smart Contract, Health Information Exchange, Clinical Trial, Persistent Monitoring.

Aravind Ramachandran, Murat Kantarcıoğlu

Blockchain technology has evolved from being an immutable ledger of\ntransactions for cryptocurrencies to a programmable interactive the environment\nfor building distributed reliable applications. Although, blockchain technology\nhas been used to address various challenges, to our knowledge none of the\nprevious work focused on using blockchain to develop a secure and immutable\nscientific data provenance management framework that automatically verifies the\nprovenance records. In this work, we leverage blockchain as a platform to\nfacilitate trustworthy data provenance collection, verification, and\nmanagement. The developed system utilizes smart contracts and open provenance\nmodel (OPM) to record immutable data trails. We show that our proposed\nframework can efficiently and securely capture and validate provenance data,\nand prevent any malicious modification to the captured data as long as the\nmajority of the participants are honest.\n

Cesare Furlanello, Manlio De Domenico, Giuseppe Jurman, Nicole Bussola

Publishing reproducible analyses is a long-standing and widespread challenge for the scientific community, funding bodies and publishers. Although a definitive solution is still elusive, the problem is recognized to affect all disciplines and lead to a critical system inefficiency. Here, we propose a blockchain-based approach to enhance scientific reproducibility, with a focus on life science studies and precision medicine. While the interest of encoding permanently into an immutable ledger all the study key information-including endpoints, data and metadata, protocols, analytical methods and all findings-has been already highlighted, here we apply the blockchain approach to solve the issue of rewarding time and expertise of scientists that commit to verify reproducibility. Our mechanism builds a trustless ecosystem of researchers, funding bodies and publishers cooperating to guarantee digital and permanent access to information and reproducible results. As a natural byproduct, a procedure to quantify scientists' and institutions' reputation for ranking purposes is obtained.

Béla Gipp, Corinna Breitinger, Norman Meuschke, Joeran Beel

Manuscript submission systems are a central fixture in scholarly publishing. However, with existing systems, researchers must trust that their yet unpublished findings will not prematurely be disseminated due to technical weaknesses and that anonymous peer reviewers or committee members will not plagiarize unpublished content. To address this limitation, we present CryptSubmit - a system that automatically creates a decentralized, tamperproof, and publicly verifiable timestamp for each submitted manuscript by utilizing the blockchain of the cryptocurrency Bitcoin. The publicly accessible and tamperproof infrastructure of the blockchain allows researchers to independently verify the validity of the timestamp associated with their manuscript at the time of submission to a conference or journal. Our system supports researchers in protecting their intellectual property even in the face of vulnerable submission platforms or dishonest peer reviewers. Optionally, the system also generates trusted timestamps for the feedback shared by peer reviewers to increase the traceability of ideas. CryptSubmit integrates these features into the open source conference management system OJS. In the future, the method could be integrated at nearly no overhead cost into other manuscript submission systems, such as EasyChair, ConfTool, or Ambra. The introduced method can also improve electronic pre-print services and storage systems for research data.

Sönke Bartling, Benedikt Fecher

<em>Blockchain</em> technology has the capacity to make digital goods immutable, transparent, externally provable, decentralized, and distributed. Besides the initial experiment or data acquisition, all remaining parts of the research cycle could take place within a <em>blockchain system</em>. Attribution, data, data postprocessing, publication, research evaluation, incentivisation, and research fund distribution would thereby become comprehensible, open (at will) and provable to the external world. Currently, scientists must be trusted to provide a true and useful representation of their research results in their final publication; <em>blockchain</em> would make much larger parts of the research cycle open to scientific self-correction. This bears the potential to be a technical solution to the current reproducibility crisis in science, and could ‘reduce waste and make more research results true’.

Enas Al Kawasmi, Edin Arnautović, Davor Svetinović

ABSTRACT This paper presents a system‐of‐systems architecture model for a Decentralized Carbon Emissions Trading Infrastructure (D‐CETI) with focus on privacy and system security goals. The structure and behavior are implemented as a solution to the problem of trading carbon emissions anonymously among the trading agents. Privacy and security of the trading agents and their carbon credits are the main requirements behind the architecture of D‐CETI. The decentralized structure of multiple systems and distributed behavior are the two main features of D‐CETI that distinguish it from the traditional carbon trading schemes and protocols. D‐CETI is based on Bitcoin, a peer‐to‐peer digital currency with no central authority, and Open Transactions, a system that simplifies the use of cryptography in financial transactions. The architecture of D‐CETI is evaluated and compared with the architecture of five other carbon emissions trading platforms.

Rajiv Ranjan, Rajkumar Buyya, Manish Parashar

Welcome to the special issue of Concurrency and Computation: Practice and Experience (CCPE) journal. This special issue compiles a number of excellent technical contributions that significantly advance the state-of-the-art in autonomic cloud computing. Cloud computing 1, 2 is an emerging utility computing model that allows users to dynamically access, select, and configure a large pool of IT resources (virtual machine templates, storage, and networking elements) and deliver them as ‘computing utilities’ to consumers in a pay-as-you-go manner. Several vendors have emerged in this space including IBM, VMware, Microsoft, Manjrasoft, and Yahoo. This model of computing is quite attractive, especially for small and medium sized enterprises, as it allows them to focus on consuming or offering services on top of cloud infrastructure. At high-level, cloud computing might not seem radically different from the existing paradigms: World Wide Web, grid computing, and cluster computing. However, key differentiators of cloud computing are its technical characteristics such as on-demand resource pooling or rapid elasticity, self-service, almost infinite scalability, end-to-end virtualization support, and robust support of resource usage metering and billing. Additionally, nontechnical differentiators include services that are offered under pay-as-you-go-model, guaranteed Service Level Agreement (SLA), faster time to deployments, lower upfront costs, little or no maintenance overhead, and environment friendliness. Unpredictability is a fact in a distributed computing environment, and the Cloud is no exception. Performance unpredictability 3 in the Cloud is in fact a major issue for many users and it is coined as one of the major obstacles for cloud computing. For instance, researchers (biologists, physicists, finance analysts, etc.) expect guaranteed performance for their experiments, independent of the current workload and state 4 of IT resources of the Cloud, because this is key to repeatability of results. Other examples are small and medium sized enterprises (gaming company, web application providers) that want strict assurance on SLA; for example, an end-user request for a web page or multimedia content has to be served within the agreed time-limit. Hence, it is highly important for Cloud vendors that they have the ability to offer guaranteed SLAs based on performance metrics — such as response time and throughput. Interestingly, vendors seem to base their SLAs on availability of their offering, while completely ignoring response time and throughput. Hence, it is clear that dealing with performance unpredictability is critical to exploiting the full potential of clouds. In this special issue, we have tried to compile some high quality papers that exhaustively deal with some of the aforementioned issues. Next, we briefly describe the technical contributions, which were selected for publication in this special issue. All of the selected papers underwent a rigorous peer-review process. The end-to-end QoS negotiation for SLA establishment for composite services involves compound multiparty negotiations in which the composite service provider concurrently negotiates with multiple candidates for each atomic service, selecting the one that best satisfies the atomic service QoS preferences while ensuring that the end-to-end QoS requirements are also fulfilled. It is necessary to derive the atomic utility boundaries from the global utility boundary to be able to negotiate with potential candidates. Additionally, there has to be a mechanism for updating these boundaries in subsequent negotiation rounds based upon the individual negotiation outcomes. To counter these complexities, in paper 5 titled ‘Establishing Composite SLAs through Concurrent QoS Negotiation with Surplus Redistribution’, Richter et al. propose an algorithm for the decomposition of global utility boundary into atomic service utility boundaries, and the surplus redistribution from successful negotiation outcomes among the remaining negotiations. The proposed mechanism is a practical approach to efficiently coordinate concurrent service negotiations within complex workflows, enabling the iterative and interactive adjustment of the negotiation boundaries for each atomic service in a composition based on the performance of other atomic negotiations. They demonstrate the feasibility of our approach by evaluating it with some popular negotiation strategies using the Specialised Property Search Scenario. Many scientific workflows are data intensive where large volumes of intermediate data are generated during their execution. Some valuable intermediate data need to be stored for sharing or reuse. Traditionally, they are selectively stored according to the system storage capacity determined manually. As doing science in the Cloud has become popular nowadays, more intermediate data can be stored in scientific cloud workflows based on a pay-for-use model. In the paper in 6 titled ‘A data dependency based strategy for intermediate data storage in scientific cloud workflow systems’, Yuan et al. build an intermediate data dependency graph (IDG) from the data provenance in scientific workflows. With the IDG, deleted intermediate data can be regenerated, and as such they develop a novel intermediate data storage strategy that can reduce the cost of scientific cloud workflow systems by automatically storing appropriate intermediate data sets with one Cloud service provider. The strategy has significant research merits, that is, it achieves a cost-effective trade-off of computation cost and storage cost and is not strongly impacted by the forecasting inaccuracy of data sets’ usages. Meanwhile, the strategy also takes the users’ tolerance of data accessing delay into consideration. Authors utilize Amazon's cost model and apply the strategy to general random and specific astrophysics pulsar searching scientific workflows for evaluation. The results show that our strategy can reduce the overall cost of scientific cloud workflow execution significantly. Recall that, one of the biggest premises of cloud computing is the flexibility of delivering IT resources and virtual appliances as an utility such as phone, electricity, gas, and water services. It enables users to have access to computing infrastructure, platform, and software as services over the Internet. To be competitive, however, Cloud providers need to be able to adapt to the dynamic loads from users, not only optimizing the local usage and costs but also engaging into agreements with other clouds to complement local capacity. The infrastructure in which competing clouds are able to cooperate to maximize their benefits is called a Federated Cloud. Just as clouds enable users to cope with unexpected demand loads, a Federated Cloud will enable individual clouds to cope with unforeseen variations of demand. The definition of the mechanism to ensure mutual benefits for the individual clouds composing the federation, however, is one of its main challenges. Gomes et al. in their paper 7 ‘Pure exchange markets for resource sharing in federated clouds’ propose and investigate the application of market-oriented mechanisms based on the General Equilibrium Theory of Microeconomics to coordinate the sharing of resources between the clouds in a Federated Cloud. Several research institutions and universities own computational capacity that is not effectively utilized, thereby providing an opportunity for such institutions to use such capacity to offer Cloud services (to both internal and external users). However, the unreliability and unpredictability of these resources mean that their use in the context of an SLA is high risk, leading to a reduction in reputation and economic penalties in case of SLA violation. To overcome these challenges, in the paper 8 titled ‘Towards autonomic management for Cloud services based upon volunteered resources’, Caton and Rana propose a methodology that addresses the issues of unreliability and unpredictability such that Cloud software services could be hosted upon volunteered resources. To enable the harnessing of these resources, they rely on autonomic fault management techniques that allow such systems to independently adapt to the resources they use based upon their perception of individual resource reliability. Using the proposed approach they were able to scale out the backend infrastructure of the Cloud service elastically (minimum 30 s per worker), opportunistically, and autonomically. To summarize, the authors address two key questions in their paper: Can a campus volunteer infrastructure be used in Cloud provisioning? and What measures are necessary to ensure reliability at the resource level? To improve the hosting and delivery of applications through cloud-based IT resources, Champrasert et al. in the paper 9 titled ‘Exploring self-optimization and self-stabilization properties in bio-inspired autonomic cloud computing’, describe architecture to build self-optimizable and self-stabilizable applications. The design of the proposed architecture, SymbioticSphere, is inspired by key biological principles such as decentralization, evolution, and symbiosis. In SymbioticSphere, each cloud application consists of application services and middleware platforms. Each service and platform is designed as a biological entity, and implements biological behaviors such as energy exchange, migration, reproduction, and death. Each service/platform possesses behavior policies, as genes, each of which defines when and how to invoke a particular behavior. SymbioticSphere allows services and platforms to autonomously adapt to dynamic network conditions by optimizing their behavior policies with a multi-objective genetic algorithm. Moreover, SymbioticSphere allows services and platforms to autonomously seek stable adaptation decisions as equilibria (or symbiosis) between them with a game theoretic algorithm. This symbiosis augments evolutionary optimization to expedite the adaptation of agents and platforms. It also contributes to stable performance that contains a very limited amount of fluctuations. Simulation results demonstrate that agents and platforms successfully attain self-optimization and self-stabilization properties in their adaptation processes. We hope that the readers will find the articles of this special issue to be informative and useful.

Nikhil Swamy, Juan Chen, Cédric Fournet, Pierre-Yves Strub · 6 authors

Abstract Distributed applications are difficult to program reliably and securely. Dependently typed functional languages promise to prevent broad classes of errors and vulnerabilities, and to enable program verification to proceed side-by-side with development. However, as recursion, effects, and rich libraries are added, using types to reason about programs, specifications, and proofs becomes challenging. We present F*, a full-fledged design and implementation of a new dependently typed language for secure distributed programming. Our language provides arbitrary recursion while maintaining a logically consistent core; it enables modular reasoning about state and other effects using affine types; and it supports proofs of refinement properties using a mixture of cryptographic evidence and logical proof terms. The key mechanism is a new kind system that tracks several sub-languages within F* and controls their interaction. F* subsumes two previous languages, F7 and Fine. We prove type soundness (with proofs mechanized in Coq) and logical consistency for F*. We have implemented a compiler that translates F* to .NET bytecode, based on a prototype for Fine. F* provides access to libraries for concurrency, networking, cryptography, and interoperability with C#, F#, and the other .NET languages. The compiler produces verifiable binaries with 60% code size overhead for proofs and types, as much as a 45x improvement over the Fine compiler, while still enabling efficient bytecode verification. We have programmed and verified nearly 50,000 lines of F* including new schemes for multi-party sessions; a zero-knowledge privacy-preserving payment protocol; a provenance-aware curated database; a suite of web-browser extensions verified for authorization properties; a cloud-hosted multi-tier web application with a verified reference monitor; the core F* typechecker itself; and programs translated to F* from other languages such as F7 and JavaScript.

Chen Su, Tiejian Luo, Wei Liu, Jinliang Song · 5 authors

In an e-Science environment, large-scale distributed resources in autonomous domains are aggregated by unified collaborative platforms to support scientific research across organizational boundaries. In order to enhance the scalability of access management, an integrated approach for decentralizing the task from resource owners to administrators on the platform is needed. We propose an extensible access management framework to meet this requirement by supporting an administrative delegation policy. This feature allows administrators on the platform to make new policies based on the original policies made by resources owners. An access protocol that merges SAML and XACML is also included in the framework. It defines how distributed parties operate with each other to make decentralized authorization decisions.