Roberta Galici, Laura Ordile, Michele Marchesi, Andrea Pinna · 5 authors
We present a novel strategy, based on the Extract, Transform and Load (ETL) process, to collect data from a blockchain, elaborate and make it available for further analysis. The study aims to satisfy the need for increasingly efficient data extraction strategies and effective representation methods for blockchain data. For this reason, we conceived a system to make scalable the process of blockchain data extraction and clustering, and to provide a SQL database which preserves the distinction between transaction and addresses. The proposed system satisfies the need to cluster addresses in entities, and the need to store the extracted data in a conventional database, making possible the data analysis by querying the database. In general, ETL processes allow the automation of the operation of data selection, data collection and data conditioning from a data warehouse, and produce output data in the best format for subsequent processing or for business. We focus on the Bitcoin blockchain transactions, which we organized in a relational database to distinguish between the input section and the output section of each transaction. We describe the implementation of address clustering algorithms specific for the Bitcoin blockchain and the process to collect and transform data and to load them in the database. To balance the input data rate with the elaboration time, we manage blockchain data according to the lambda architecture. To evaluate our process, we first analyzed the performances in terms of scalability, and then we checked its usability by analyzing loaded data. Finally, we present the results of a toy analysis, which provides some findings about blockchain data, focusing on a comparison between the statistics of the last year of transactions, and previous results of historical blockchain data found in the literature. The ETL process we realized to analyze blockchain data is proven to be able to perform a reliable and scalable data acquisition process, whose result makes stored data available for further analysis and business.
Businesses whose work hours, work durations & also more compliance records must be trustworthy and verifiable have great difficulties maintaining more accurate & also safe timekeeping. This article looks at a novel approach for smart contract & also blockchain technology integration protection of timekeeping data. Changing from more conventional, centralized time-tracking systems to a distributed ledger creates a safe framework that logs time inputs as unchangeable transactions, therefore preventing any retroactive changes or more unauthorized additions. While smart contracts provide automation of activities like clock-ins, clock-outs & more compliance alerts, every input is validated & also documented with cryptographic certainty. This guarantees real-time policy compliance and eliminates errors in hand-made monitoring. Clear audit trail, real-time notifications for errors or transgressions, and tamper-evident recordkeeping define the main characteristics of the recommended solution. These elements taken together provide a mechanism wherein auditors, managers, and employees may trust the data free from middlemen's intervention. Extended data integrity, increased organizational trust, greater transparency in payroll and compliance procedures, and fewer incidence of fraud or human error define the projected benefits. From manufacturing to logistics, remote work, healthcare, legal compliance management, the approach is versatile and scalable across numerous sectors. This work integrates trust into the infrastructure via blockchain and smart contract automation therefore establishing a progressive base for future timekeeping systems
BACKGROUND: Health care professionals are required to maintain accurate health records of patients. Furthermore, these records should be shared across different health care organizations for professionals to have a complete review of medical history and avoid missing important information. Nowadays, health care providers use electronic health records (EHRs) as a key to the implementation of these goals and delivery of quality care. However, there are technical and legal hurdles that prevent the adoption of these systems, such as concerns about performance and privacy issues. OBJECTIVE: This study aimed to build and evaluate an experimental blockchain for EHRs, named HealthChain, which overcomes the disadvantages of traditional EHR systems. METHODS: HealthChain is built based on consortium blockchain technology. Specifically, three organizations, namely hospitals, insurance providers, and governmental agencies, form a consortium that operates under a governance model, which enforces the business logic agreed by all participants. Every peer node hosts an instance of the distributed ledger consisting of EHRs and an instance of chaincode regulating the permissions of participants. Designated orderers establish consensus on the order of EHRs and then disseminate blocks to peers. RESULTS: HealthChain achieves functional and nonfunctional requirements. It can store EHRs in a distributed ledger and share them among different participants. Moreover, it demonstrates superior features, such as privacy preservation, security, and high throughput. These are the main reasons why HealthChain is proposed. CONCLUSIONS: Consortium blockchain technology can help to build new EHR systems and solve the problems that prevent the adoption of traditional systems.
Data mesh architecture is revolutionizing the field of data analytics, offering a fresh approach to how organizations manage and utilize data. Traditionally, centralized data warehouses and data lakes have dominated the landscape, but as the volume and complexity of data grow, these systems struggle to keep pace. Data mesh breaks away from the centralized model by promoting a decentralized and domain-oriented approach, where individual teams take ownership of their data. This shift enables organizations to treat data as a product, with each domain team responsible for managing and serving their data assets. The goal is to make data more accessible and usable across the organization while reducing bottlenecks that occur in centralized systems. Implementing data mesh architecture has profound implications for data management. It encourages better data governance, scalability, and flexibility, while fostering innovation and collaboration. However, it also introduces challenges, such as ensuring consistency, standardization, and proper integration across domains. The success of a data mesh strategy depends on a strong cultural shift, requiring both technical infrastructure and organizational alignment to support autonomous teams. Ultimately, data mesh offers the promise of unlocking the full potential of data in large organizations by making it more agile, democratized, and efficient. By embracing this architecture, businesses can better respond to the increasing demands of modern data management and gain a competitive edge in the digital landscape.
Machine learning is promising, but it often needs to process vast amounts of\nsensitive data which raises concerns about privacy. In this white-paper, we\nintroduce Substra, a distributed framework for privacy-preserving, traceable\nand collaborative Machine Learning. Substra gathers data providers and\nalgorithm designers into a network of nodes that can train models on demand but\nunder advanced permission regimes. To guarantee data privacy, Substra\nimplements distributed learning: the data never leave their nodes; only\nalgorithms, predictive models and non-sensitive metadata are exchanged on the\nnetwork. The computations are orchestrated by a Distributed Ledger Technology\nwhich guarantees traceability and authenticity of information without needing\nto trust a third party. Although originally developed for Healthcare\napplications, Substra is not data, algorithm or programming language specific.\nIt supports many types of computation plans including parallel computation plan\ncommonly used in Federated Learning. With appropriate guidelines, it can be\ndeployed for numerous Machine Learning use-cases with data or algorithm\nproviders where trust is limited.\n
The potentiality of Blockchain technology is widespread and applied to diverse fields. Blockchain is a distributed ledger of transactions that store immutable records in chronological order in an append-only mode. Hence, humongous data is stored on the blockchain and will continuously expand over time. Blockchain has been rapidly adopted by many businesses for storing the provenance data because of its salient features like immutability, robustness and tamperproof. Blockchain stores data provenance as transactions that are collected from sources like a centralized cloud or decentralized cloud that helps in identifying cybercrimes. This paper emphasizes on the different approaches of querying the data provenance transactions stored in Ethereum Blockchain based on various search parameters using REST API web services. The approach not only queries based on the first-class data elements like blocks, transactions, account address and contract address but also queries based on the provenance data stored on the Ethereum Blockchain explained with a use case LegalProv.
With data intensive computing helping advance state-of-the-art in varied fields, data provenance and lineage continue to remain formidable challenges in assisting with integrity and reproducibility in research and applications. This is particularly challenging for distributed scenarios, where data may be originating from decentralized sources without any centralized control by a single trusted entity. To date most of the data provenance systems are specific to particular domains, and are often centralized. Distributed ledgers such as blockchains have proved quite popular and effective in addressing trust and consensus without central control. There are a few recent proposals to employ blockchains for data provenance, however, they rely on currency in order to propose transactions using public blockchains.\n\nWe present HyperProv, a general framework for data provenance based on the permissioned blockchain Hyperledger Fabric (HLF), and to the best of our knowledge, the first provenance system that is ported to ARM based devices such as Raspberry Pi (RPi). HyperProv records the operation history and data lineage by tracking checksums, editors, timestamps, data pointers, dependencies, and more. Provenance data is retrieved and stored through a NodeJS client library to simplify interactions with the blockchain. HyperProv has a set of built-in queries using smart contracts that enable lightweight retrieval of large collections of provenance data. We evaluate the throughput, latency and resource consumption of HyperProv on x86-64 desktop machines, as well as RPi, demonstrating the feasibility of using HyperProv on RPi for tamperproof data provenance, useful in particular for Internet of Things use cases.
Apr 20, 2019·MaxEnt 2019 - Proceedings of the 39th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, Garching, Germany, 30 June - 5 July 2019
Randomization is an integral part of well-designed statistical trials, and is also a required procedure in legal systems. Implementation of honest, unbiased, understandable, secure, traceable, auditable and collusion resistant randomization procedures is a mater of great legal, social and political importance. Given the juridical and social importance of randomization, it is important to develop procedures in full compliance with the following desiderata: (a) Statistical soundness and computational efficiency; (b) Procedural, cryptographical and computational security; (c) Complete auditability and traceability; (d) Any attempt by participating parties or coalitions to spuriously influence the procedure should be either unsuccessful or be detected; (e) Open-source programming; (f) Multiple hardware platform and operating system implementation; (g) User friendliness and transparency; (h) Flexibility and adaptability for the needs and requirements of multiple application areas (like, for example, clinical trials, selection of jury or judges in legal proceedings, and draft lotteries). This paper presents a simple and easy to implement randomization protocol that assures, in a formal mathematical setting, full compliance to the aforementioned desiderata for randomization procedures.
Sebastian Lawrenz, Priyanka Sharma, Andreas Rausch
In the digital Economy 'Data is the new oil. In the last decade technology has disrupted every filed imaginable. One such booming technology is Blockchain. A blockchain is essentially a distributed database of records or public ledger of all transactions or digital events that have been executed and shared among participating parties. And once entered, the information is immutable. Ongoing projects and prior work in the fields of big data, data mining and data science has revealed how relevant data can be used to enhance products and services. There are uncountable applications and advantages of relevant data. The most valuable companies of today treat data as a commodity, which they trade and earn revenues.
David Froelicher, Juan Ramón Troncoso-Pastoriza, João M. C. Sousa, Jean‐Pierre Hubaux
Data sharing has become of primary importance in many domains such as\nbig-data analytics, economics and medical research, but remains difficult to\nachieve when the data are sensitive. In fact, sharing personal information\nrequires individuals' unconditional consent or is often simply forbidden for\nprivacy and security reasons. In this paper, we propose Drynx, a decentralized\nsystem for privacy-conscious statistical analysis on distributed datasets.\nDrynx relies on a set of computing nodes to enable the computation of\nstatistics such as standard deviation or extrema, and the training and\nevaluation of machine-learning models on sensitive and distributed data. To\nensure data confidentiality and the privacy of the data providers, Drynx\ncombines interactive protocols, homomorphic encryption, zero-knowledge proofs\nof correctness, and differential privacy. It enables an efficient and\ndecentralized verification of the input data and of all the system's\ncomputations thus provides auditability in a strong adversarial model in which\nno entity has to be individually trusted. Drynx is highly modular, dynamic and\nparallelizable. Our evaluation shows that it enables the training of a logistic\nregression model on a dataset (12 features and 600,000 records) distributed\namong 12 data providers in less than 2 seconds. The computations are\ndistributed among 6 computing nodes, and Drynx enables the verification of the\nquery execution's correctness in less than 22 seconds.\n
This thesis aims to explore the compliance of blockchain technology and the GDPR. The GDPR was implemented for the EU member states in May 2018 with the purpose of harmonizing data protection regulation. However, the regulation is based on the notion that data is stored and processed in a centralized system. This causes an issue when it comes to distributed networks, and in particular with the distributed ledger technology (DLT), the underlying technology of blockchain. For this thesis, a literature review has been conducted to investigate the problems of GDPR compliance for blockchain projects, and what technical solutions exist to make a blockchain solution more GDPR compliant. In addition, interviews have been conducted to investigate the technical and legal perspectives on the current and future situations of regulation and technology. Compatibility problems mainly concern the immutability and transparency of a blockchain and examples of technical solutions that handle those problems can be found in the literature. Nevertheless, none of the discussed solutions are yet to guarantee full GDPR compliance. The technical and legal perspectives share ideas of the main compliance issues. However, differences such as interpretation of technical details can be identified, indicating problems to arise when regulating blockchains in the future. Further interdisciplinary work on guidelines for the GDPR is necessary for blockchain projects to be successful in complying with the regulation as well as to strengthen the technology neutrality of the GDPR.
With the recent trend on blockchain, many users want to know more about the important players of the chain. In this study, we investigate and analyze the Ethereum blockchain network in order to identify the major entities across the transaction network. By leveraging the rich data available through Alethio's platform in the form of RDF triples we learn about the Hubs and Authorities of the Ethereum transaction network. Alethio uses SANSA for effcient reading and processing of such large-scale RDF data (transactions on Ethereum blockchain) in order to perform analytics e.g. finding top accounts, or typical behavior patterns of exchanges' deposit wallets and more.
This paper proposes the use of a blockchainbased structure in order to store evidences in a digital forensics investigation. The traditional chain of evidence is augmented with properties of immutability and traceability, thanks to a cryptographic process. The blockchain is constructed by forensics experts by adding evidences through the process. Since the blockchain is immutable, it can be shared among the different parties involved in a prosecution in order to review the chain of evidence and build their case. Furthermore, the blockchain structure can be applied to other forensics fields, like drugs, firearms, NDA. This blockchain is called a Digital Evidence Inventory (DEI) and is part of a wider framework encompassing a Forensics Confidence Rating (FCR) structure, in order to give experts the ability to rate the level of confidence for each evidence and a Global Digital Timeline (GDT) to order evidence through time. The whole framework is called ‘Aldiana’.
Yunhui Long, Tanmay Gangwani, Haris Mughees, Carl A. Gunter
Privacy preserving multi-party computation has many applications in areas such as medicine and online advertisements. In this work, we propose a framework for distributed, secure machine learning among untrusted individuals. The framework consists of two parts: a two-step training protocol based on homomorphic addition and a zero knowledge proof for data validity. By combining these two techniques, our framework provides privacy of per-user data, prevents against a malicious user contributing corrupted data to the shared pool, enables each user to self-compute the results of the algorithm without relying on external trusted third parties, and requires no private channels between groups of users. We show how different ML algorithms such as Latent Dirichlet Allocation, Naive Bayes, Decision Trees etc. fit our framework for distributed, secure computing.
Associating the health-related records and transactions of patients with their numerous “identities” as they interact with different healthcare providers, payers, pharmacy benefit managers and other entities is an expensive and complex problem. With many years of experience addressing this issue in different healthcare systems and Health Information Exchanges (HIEs), it is apparent that there is now a compelling and relatively straightforward technical solution for this problem. Presented here is a broadly feasible and technically compelling argument for a blockchain-based approach to addressing these issues. At the same time, challenges ahead and potential strategies to address them are discussed. Keywords: Blockchain; Master Patient Index; MPI; Distributed Ledger; Patient Identity; HIE; HealthInformation Exchange
Muhammad Muzammal, Qiang Qu, Bulat Nasrulin, Anders Skovsgaard
A blockchain is a decentralised linked data structure that is characterised by its inherent resistance to data modification, but it is deficient in search queries, primarily due to its inferior data formatting. A distributed database is also a decentralised data structure which features quick query processing and well-designed data formatting but suffers from data reliability. In this demonstration, we showcase a blockchain database application platform developed by integrating the blockchain with the database, i.e. we demonstrate a system that has the decentralised, distributed and audibility features of the blockchain and quick query processing and well-designed data structure of the distributed databases. The system features a tamper-resistant, consistent and cost-effective multi-active database and an effective and reliable data-level disaster recovery backup. The system is demonstrated in practice as a multi-active database along with the data-level disaster recovery backup feature.
This paper offers an overview of the highlights of the NFAIS Conference, Blockchain for Scholarly Publishing, that was held in Alexandria, VA from May 15–16, 2018. The goal of the conference was to take a close look at the initiatives that have emerged as a result of the increasing global acceptance of blockchain technology. This technology, chiefly known as the foundation of Bitcoin and originally introduced as a means of securely managing cryptocurrency, has proven to have practical applications beyond finance. The basic technology is that of a distributed ledger and it is being broadly-adopted by multiple industries, including the scholarly publishing community. The capabilities of this new technology are prompting a direct exchange among stakeholders, as blockchain promises a more structured, decentralized, and immutably secure approach that has the potential to significantly impact researcher workflows - from data collection to peer review to access and published work. The technology inspires passion - there are those who believe that it will ultimately transform our lives while others are completely skeptical. The NFAIS conference provided a look at both sides of the coin (no pun intended).
Subasri Mathiyalahan, Shobana Manivannan, Mahalakshmi Nagasundaram, R. Ezhilarasie
Data integrity of outsourced data is main problem in CSP (cloud service provider). Space overhead and computation complexity are very high issue in recent PDP(Provable Data Possession) verification schemes. To overcome such issues MPDP (Mobile Provable Data Possession) schemes using hash tree data structure and Boneh-Lynn-Snacham short signature scheme have been used over decade. Data dynamics is well supported in MPDP scheme via block less verification, dynamic data operations, stateless verification, and verification out sourcing. But still there are some operations which can be performed much more efficiently in some other way than that of the two methods prescribed above. Operations in particular, data modification operations like insertion and deletion operations is somewhat difficult or in other words time consuming in hash tree data structure. In this paper, we have deployed an improved hash tree structure called MPT (Merkle Patricia Tree) for integrity checking.MPT is combination of MHT (Merkle Hash Tree) and patricia tree where each node consists of key-value pairs. As of now, MPT has been used only in block chain technology for providing authentication of transactions through Ethereum.
The blockchain technology is a new innovation with the potential to disrupt the\nworld as we currently know it, despite several limitations and challenges to overcome.\nOne of these challenges for software producing organizations is selecting the\nright technology for their case. In this research, we haveve identified this selection\nprocess as a multi-criteria decision making problem. Based on this we have created\na Decision Support System which aids developers during the technology selection\nprocess of blockchain platforms. Contemporary solutions to this problem were only\nrather simplistic decision-trees, which struggle with complexity and adaptations.\nThe novelty of this Decision Support System lies in being a feature-based artifact\nwhich incorporates ISO Software Quality Aspects and feature prioritization based\non the MoSCoW-technique. These contemporary generic blockchain features have\nbeen gathered through nine interviews with blockchain experts. Based on prioritized\nfeatures as input, the Decision Support System gives a score for feasible solutions\n(e.g. Ethereum or Hyperledger) as result. This Decision Support System was\nevaluated in three different case-studies for organization creating blockchain-based\nsolutions. In addition to this, the artifact has been validated by a blockchain-domain\nexpert. The main difficulties and obstacles of this whole research were grounded in\nthe immaturity of the blockchain domain as a whole.
Siwan Noh, Youngho Park, Chur Sur, Sang Uk Shin · 5 authors
privacy. An exposure of personal medical records causes damage to the finance, etc. Sometimes, it could put patient's life in danger. To achieve secure data sharing between institutions, many studies use cloud storage to store medical records. However, many studies suppose that cloud service providers were trustworthy. These systems required a key establishment with the cloud service providers and all the access logs are governed by cloud service providers. Patients should ask cloud service providers to check these access logs. However, it can be forged by cloud service providers during the request process. In this paper, we propose blockchain based medical records management system for secure data sharing. In order to share securely, we use proxy re-encryption scheme. Also, we use blockchain technology to audit access logs without modification.
SILVEIRA, Alexandre Marques Albano da. Prova de conhecimento nulo baseada em isomorfismo de subgrafos. 2016. 71 f. - Dissertação - Universidade Federal do Ceará, Programa de Pós-Graduação em Engenharia Elétrica e da Computação, Sobral, 2016.
Quality Control in Fact-Finding is, above all else, a very welcome addition to the literature on international fact-finding. Whilst there has been a marked increase in the number of fact-finding inquiries established in the last couple of decades,1 this has not been matched by a similar increase in the number of scholarly studies of such inquiries.2 In light of both the number and high-profile nature of such inquiries, the absence of scholarship focusing squarely on the contemporary role of inquiries up to the present day seems like an oversight. This collection, published in open access format by Florence-based, not-for-profit ‘academic EPublisher’ Torkel Opsahl (named after the late Professor Opsahl who himself briefly chaired the Commission of Experts for the Former Yugoslavia until his untimely death in 1993), attempts to address this lack of academic attention. The collection ostensibly sets out to ‘make a contribution to the emerging discourse on fact-finding mechanisms’ by ‘focusing specifically on quality awareness and quality improvement in non-criminal justice fact-work’ (at viii). Its accessible style, open access format, and the breadth of topics covered will attract the attention not only of international legal scholars, but practitioners and policy-makers too. In the opening chapter Marina Aksenova and Morten Bergsmo provide a helpful overview of the concept of international fact-finding itself and of the fact-finding missions established in recent decades. The authors define the concept of fact-finding broadly as a method of ascertaining facts used in international relations for differing purposes (at 2), before noting that traditionally there are three main purposes for establishing facts in international law. The first is the narrow purpose of fact-finding ‘in cases where differences of opinion on factual matters underlie a dispute between parties’, for which a procedure of inquiry was set out in the 1899 and 1907 Hague Conventions, and which has fallen into desuetude.3 The second purpose is that of supervising the execution of international agreements typically carried out by the UN Specialized Agencies, and the third purpose is fact-finding for the purposes of Article 34 of the UN Charter, namely the power of the Security Council to investigate any situation or dispute that may endanger international peace and security. The overview of fact-finding missions established by principal UN organs, subsidiary organs, national governments, and various Non-Governmental Organizations (NGOs), helpfully set out in the form of a table in the opening chapter, provides a valuable introduction to the subject. Commentators in the past have lamented the lack of a standard operating procedure for fact-finding missions.4 However, a recurring theme of this collection is caution against standardization in light of the inherently context-specific nature of international fact-finding inquiries. Richard Goldstone states that ‘[i]t is folly to generalise about fact-finding missions. Each situation will have its unique features. What works with regard to one may well fail if applied to another’ (at 52). Similarly, Martin Scheinin argues in favour of the maintenance of clear functional distinctions between inquiries, in particular asserting that the ‘various mechanisms of mainstream human rights bodies that seek to establish state responsibility for human rights violations should not be subjected to the evidence requirements typical for determining individual criminal accountability’ (at 54). Particularly insightful contributions to the collection are those in which the authors are able to draw on their own practical experience, such as the chapters by Goldstone, Scheinin, Chris Mahony, and David Re. Goldstone’s contribution provides a potentially crucial insight into the mind of a man who has been heavily involved in a number of landmark fact-finding missions, both domestic and international. Much of Goldstone’s account focuses on two domestic inquiries that he led in South Africa, namely the Sithole Inquiry into the death of a member of the ANC in detention shortly before the release of Nelson Mandela from prison in February 1990, and the Sebokeng Inquiry into the action of police during a mass protest-match in March 1990. The relevance of the discussion of these domestic inquiries to a collection on international fact-finding is perhaps not immediately apparent; however Goldstone’s vast experience allows him to make a number of broad proposals for improving the quality of future international fact-finding missions. Amongst them the lessons learned from the Sithole Inquiry in which the transparent nature of the inquiry (which was held in a Johannesburg City Hall instead of a courtroom with no visible security and large public galleries) created a more ‘public-friendly’ atmosphere and insulated it from political interference, and the proposals for opening the appointment process for members of commissions to public scrutiny, are amongst the most helpful and practical proposals. Goldstone’s contribution is also instructive regarding his involvement in the UN Human Rights Council’s Gaza inquiry in 2009, as it illuminates the political machinations ‘behind the scenes’ that led to the formation of the inquiry and possibly is indicative of the political process that has led to the establishment of other commissions of inquiry. Similarly interesting is the issue of consent and cooperation – the refusal of Israel to cooperate with the inquiry clearly impeded the Commission’s operation and was apparently the cause of many of the ‘sleepless nights’ that Goldstone subsequently suffered (at 50). The lack of cooperation, coupled with new facts subsequently coming to light, put Goldstone in the position where he felt he had to row back on some of the inquiry’s factual findings in a Washington Post opinion-editorial. This episode cautions against reliance on any findings-of-fact derived from an inquiry with restricted access to the area investigated, and a resultant need to rely to a much greater extent on secondary sources and press reports. The critical remarks of Wu Xiaodan that Goldstone’s change of heart and the furore surrounding Professor Christine Chinkin’s alleged bias had cast some doubt on the credibility and impartiality of the Goldstone Report provide a useful counterpoint to Goldstone’s chapter (at 201) although an even more robust critique was perhaps warranted. Similarly, Scheinin draws on decades of practical experience in his contribution dealing with fact-finding in the context of treaty-based human rights mechanisms and the Special Procedures of the UN Human Rights Council. Scheinin’s contribution provides a helpful typology of the fact-finding apparatus and organizational structure of treaty-based fact-finding mechanisms, including the reporting procedure, individual complaints, and inquiries. Perhaps the most useful part of this contribution is the section dealing with Special Procedures in which the thoughts of an experienced practitioner are key, given the nature of the topic that would otherwise be largely impenetrable to most. For instance, the contribution explores the two fact-finding functions of Special Rapporteurs, namely communications (letters) to governments and country visits. Scheinin is critical of the communications function, noting that the response rate to letters is low and the information gained from communications is such that they cannot be considered a fact-finding mechanism at all. However, Scheinin is able to draw on his own experience as Special Rapporteur, having paid visits to states such as Turkey and Tunisia, and is positive about governmental compliance with requests made by Special Rapporteurs, access to areas under investigation, and ultimately even the uncovering of facts that could later be used for a number of purposes including criminal prosecution. Among the most important contributions to the collection is that of Mahony dealing with the security implications for witnesses appearing before fact-finding commissions. This extended, detailed, contribution draws on the author’s own experience in Nepal, and both the Truth and Reconciliation Commission and Special Court in Sierra Leone. Whilst having a relatively narrow focus on a small number of situations, the author’s own first-hand experience and the level of detail and practical examples provided allow important conclusions to be drawn regarding means of ensuring the safety of witnesses, including details of the legal regime needed for witness protection, consideration of the crucial issue of funding, and more practical issues such as personnel and the institutional location of the programme that could potentially be of use in the context of other commissions. David Re’s contribution is based on his involvement in the criminal courts in the Former Yugoslavia and Sierra Leone and poses a fundamentally important question: what did the ICTY trial and appeals chamber actually do with UN and NGO fact-finding reports? Interestingly, Re shows that relatively minimal (at least explicit) use was made of such factual findings by the ICTY chambers between 1994 and 2013. Most often such findings were utilized as investigative leads for the prosecutor (at 296). Further, Re argues that the findings-of-fact made by such inquiries are likely to be more politically and historically important than judicially influential (at 280). The conclusions to be drawn from this argument are not fully fleshed out, but it is submitted that it is fundamentally important for the future of international fact-finding that they are considered. Tackling more theoretical issues, Simon De Smet’s contribution addresses the theoretical foundations of fact-finding. He takes as his starting point that most fact-finders approach the subject intuitively; ‘[e]ven though they may display great care and circumspection in making their findings, they do not necessarily have a strongly developed understanding of what the underlying principles and concepts of fact-finding are’ (at 74). De Smet provides a helpful introduction to the epistemology of fact-finding and evidence (at 80) and takes us through important theoretical issues such as the epistemology of how beliefs can be justified, including both probabilistic or Bayesian epistemology and so-called ‘inference to best explanation’ or relative plausibility theory. In doing so De Smet seeks to provide the basis for improving the overall epistemic quality of fact-finding, without making any claims that doing so would in actual fact improve the accuracy of fact-finding in practice. De Smet tackles a wide array of the goals he has set for himself with relish, although one gets the impression that there is simply not enough space to do justice to the substantial number of important issues ranging from philosophical conceptions of probability to the epistemology of testimony, trustworthiness, competence, and cognitive consensus, to name just a few. While the author’s forthcoming monograph will provide a more in-depth analysis,5 in the context of this collection, it might have been better to choose a smaller number of discrete issues and explore them in greater detail, but this is a minor quibble. Despite claiming to deal with non-criminal justice fact-finding (at viii) international criminal law inevitably finds its way into the collection through the contribution by Dov Jacobs and Catherine Harwood which considers the use of international criminal law (ICL) by fact-finding commissions. More specifically, the contribution assesses the creep of international criminal law concepts into the work of fact-finding missions and considers the utility of ICL in general ‘outside the courtroom’. The contribution highlights a number of concerns regarding the use of such concepts in fact-finding inquiries, including the problematic use of the criminal law burden and standard of proof in non-judicial situations which raise issues of due process. For instance, cursory legal determinations of complex situations and divergent legal determinations between different commissions of inquiry have caused controversy in recent times.6 The contribution ultimately concludes that not only does the use of ICL concepts not help to solve some of the operational problems that fact-finding inquiries face, it in effect creates a number of new problems (at 353). Whilst this contribution complements excellent existing work in this field,7 the topic of fact-finding in international criminal law remains one of the most under-researched areas of fact-finding and further research in this area, where the personal liberty of individuals is at stake, is undoubtedly needed. Other contributions address selected issues including quality control in the context of truth and reconciliation (Liu Daqun at Chapter 5), how commissions of inquiry can provide international prosecutors with the background information they need on specific international criminal law situations (Lyal S. Sunga at Chapter 13), fact-finding difficulties encountered by NGOs (Wolfgang Kaleck and CarolijnTerwindt at Chapter 14), and the role of information technology in the work of fact-finding commissions (Ilia Utmelidze at Chapter 16). In the penultimate chapter Charles Garraway provides a contribution on the International Humanitarian Fact-Finding Commission established under Article 90 of the First Additional Protocol to the Geneva Conventions of 1949, which has never been used to date, but which could be of potential use in the future according to the author, although its competences are in some crucial respects limited in scope. Mention is made of these contributions in order to highlight the sheer breadth of the collection, which endeavours to cover so many discrete and diverse issues in relation to international fact-finding. Ultimately, Quality Control in Fact-Finding is a commendable attempt to address the paucity of literature in an area of international law that is seen as increasingly significant. Whilst a final concluding chapter drawing together some of the main themes and findings of the collection would have been welcome, it contains some genuinely useful contributions, in particular those in which the authors are able to draw on their own experience and those which attempt to systematize and make sense of the operation of international fact-finding. Marina Aksenova and Morten Bergsmo, Non-Criminal Justice Fact-Work in the Age of Accountability; Richard J. Goldstone, Quality Control in International Fact-Finding Outside Criminal Justice for Core International Crimes; Martin Scheinin, Improving Fact-Finding in Treaty-Based Human Rights Mechanisms and the Special Procedures of the United Nations Human Rights Council; Simon De Smet, Justified Belief in the Unbelievable; Liu Daqun, Quality Control in Truth and Reconciliation Processes; Fan Yuwen, Quality Control and the Mandate of International Fact-Finding; Isabelle Lassée, Coherence in the Design and Implementation of the Mandates of International Fact-Finding Commissions: Internal and External Dimensions; Wu Xiaodan, Quality Control and the Selection of Members of International Fact-Finding Mandates; Dan Saxon, Purpose and Legitimacy in International Fact-Finding Bodies; Chris Mahony, Witness Sensitive Practices in International Fact-Finding Outside Criminal Justice: Lessons for Nepal; David Re, Fact-Finding in the Former Yugoslavia: What the Courts Did; Dov Jacobs and Catherine Harwood, International Criminal Law Outside the Courtroom: The Impact of Focusing on International Crimes for the Quality of Fact-Finding; Lyal S. Sunga, Can International Criminal Investigators and Prosecutors Afford to Ignore Information from United Nations Human Rights Sources?; Wolfgang Kaleck and Carolijn Terwindt, Non-Governmental Organisation Fact-Work: Not Only a Technical Problem; Charles Garraway, Fact-Finding and the International Humanitarian Fact-Finding Commission; Ilia Utmelidze, Information Technology and Quality Control in Non-Criminal Justice Fact-Work.
This paper introduce a dynamic audit service for integrity verification of untrusted and outsourced storages. Our audit service is constructed based on the techniques, fragment structure, random sampling, and index-hash table, supporting provable updates to outsourced data and timely anomaly detection. Constructed on interactive proof system (IPS) with the zero knowledge property, our audit service can provide public auditability without downloading raw data and protect privacy of the data. Also, our audit system can support dynamic data operations and timely anomaly detection with the help of several effective techniques, such as fragment structure, random sampling, and index-hash table (IHT). We also propose an efficient approach based on probabilistic query and periodic verification for improving the performance of audit services. A proof-ofconcept prototype is also implemented to evaluate the feasibility and viability of our proposed approaches. Our experimental results not only validate the effectiveness of our approaches, but also show that our system does not create any significant computation cost and require less extra storage for integrity verification.