Blockchain Papers

Daehan Kim, Doojin Ryu, Robert I. Webb

No abstract is available for this record.

Barbara Guidi

No abstract is available for this record.

Pascal Lafourcade, Daiki Miyahara, Takaaki Mizuki, Léo Robert · 6 authors

We propose a technique to construct physical Zero-Knowledge Proof (ZKP) protocols for puzzles that require a single loop draw feature. Our approach is based on the observation that a loop has only one hole and this property remains stable by some simple transformations. Using this trick, we can transform a simple big loop, which is visible to anyone, into the solution loop by using transformations that do not disclose any information about the solution. We illustrate our technique by applying it to construct physical ZKP protocols for two Nikoli puzzles: Slitherlink and Masyu.

Luka Lukić, Nenad Kojić, Mladen Veinović

Since 2009, with the invention of Bitcoin, the usage of blockchain technology is constantly increasing. From its initial financial use case, blockchain as a decentralized data storage system has grown to an entirely new information ecosystem and has been successfully applied in a wide range of applications in other industrial sectors, outside of finance. Given that the data is decentralized, the computer nodes participating in the network are in charge of adding new data to the blockchain, the authenticity of which is determined by consensus algorithms as a mechanism for maintaining data integrity. Bearing that in mind, consensus algorithms and their application are crucial for the reliability and data security in a blockchain. The aim of this paper is to perform an analysis of currently most used consensus algorithms, as well as their impact on key blockchain attributes.

Sultan Alsehibani

No abstract is available for this record.

Gëzim Sejdiu

Over the past decade, vast amounts of machine-readable structured information have become available through the automation of research processes as well as the increasing popularity of knowledge graphs and semantic technologies. 
\nToday, we count more than 10,000 datasets made available online following Semantic Web standards.
\nA major and yet unsolved challenge that research faces today is to perform scalable analysis of large-scale knowledge graphs in order to facilitate applications in various domains including life sciences, publishing, and the internet of things.
\nThe main objective of this thesis is to lay foundations for efficient algorithms performing analytics, i.e. exploration, quality assessment, and querying over semantic knowledge graphs at a scale that has not been possible before.
\nFirst, we propose a novel approach for statistical calculations of large RDF datasets, which scales out to clusters of machines. 
\nIn particular, we describe the first distributed in-memory approach for computing 32 different statistical criteria for RDF datasets using Apache Spark.
\nMany applications such as data integration, search, and interlinking, may take full advantage of the data when having a priori statistical information about its internal structure and coverage.
\nHowever, such applications may suffer from low quality and not being able to leverage the full advantage of the data when the size of data goes beyond the capacity of the resources available.
\nThus, we introduce a distributed approach of quality assessment of large RDF datasets.
\nIt is the first distributed, in-memory approach for computing different quality metrics for large RDF datasets using Apache Spark. We also provide a quality assessment pattern that can be used to generate new scalable metrics that can be applied to big data.
\nBased on the knowledge of the internal statistics of a dataset and its quality, users typically want to query and retrieve large amounts of information.
\nAs a result, it has become difficult to efficiently process these large RDF datasets.
\nIndeed, these processes require, both efficient storage strategies and query-processing engines, to be able to scale in terms of data size.
\nTherefore, we propose a scalable approach to evaluate SPARQL queries over distributed RDF datasets by translating SPARQL queries into Spark executable code.
\nWe conducted several empirical evaluations to assess the scalability, effectiveness, and efficiency of our proposed approaches.
\nMore importantly, various use cases i.e. Ethereum analysis, Mining Big Data Logs, and Scalable Integration of POIs, have been developed and leverages by our approach. 
\nThe empirical evaluations and concrete applications provide evidence that our methodology and techniques proposed during this thesis help to effectively analyze and process large-scale RDF datasets.
\nAll the proposed approaches during this thesis are integrated into the larger SANSA framework.

Aman Sharma, Ankit Agrawal, Ashutosh Bhatia, Kamlesh Tiwari

Bitcoin is the most popular cryptocurrency used worldwide. It provides pseudonymity to its users by establishing identity using public keys as transaction end-points. These transactions are recorded on an immutable public ledger called Blockchain which is an append-only data structure. The popularity of Bitcoin has increased unreasonably. The general trend shows a positive response from the common masses indicating an increase in trust and privacy concerns which makes an interesting use case from the analysis point of view. Moreover, since the blockchain is publicly available and up-to-date, any analysis would provide a live insight into the usage patterns which ultimately would be useful for making a number of inferences by law-enforcement agencies, economists, tech-enthusiasts, etc. In this paper, we study various applications and techniques of performing data analytics over Bitcoin blockchain from a graph theoretic perspective. We also propose a framework for performing such data analytics and explored a couple of use cases using the proposed framework.

Xiaoyao Qian

One of the most important components in a public blockchain like Bitcoin and Ethereum is the authenticated data structure that keeps track of all block data, transactions, and the world state (account balance, smart contract states, etc.) Thanks to authenticated data structures, lightweight nodes only need to store authentication information and can delegate queries to those nodes with a full replica of data and the authenticated data structure. The lightweight nodes can trust the query results after verifying against the authentication information. It is also critical to have enough nodes in the network that are equipped with the authenticated data structure to ensure scalability and availability, which is especially important for public blockchains. Therefore, every public blockchain highly encourages users to download the authenticated data structure as the first step.\n\nFetching all elements from the entire authenticated data structure is a novel query type that has not gathered attention in the past. We describe this new emerging query type in the three-party authenticated data structure (ADS). We improve the design and implementation of the authenticated data structure so that the new query type is well-supported. We specifically apply the improvements to the Ethereum blockchain network. With our proposed ADS system in Ethereum, we improve Ethereum state synchronization performance by 216 times.

B. Moustapha

In this paper, we revisit the fundamental question of Bitcoins security against selfish-mine attack introduced by I. Eyal and E. G. Sirer in We study the state machine of Bitcoin's network under the influence of one pool miner adopting the selfish mine strategy while the rest of the community following the standard protocol. We prove that the process following by the states of Bitcoin's system is a irreducible, positive-recurrent, aperiodic, and discrete Markov chain. We give an invariant (stationary) distribution for this Markov chain and deduce easily the rate of convergence towards the stationary equilibrium situation.

Seied Hoseini

Blockchain is a technology to exchange digital assets including cryptocurrencies, data, software, patents etc. Blockchain is designed in various types depending on different architectures and configurations for different purposes. The mathematical and cryptographic mechanisms and consensus algorithms, implemented in the Blockchain, guarantee trust, security, integrity and availability of transactions between participants.
\nThis thesis is aimed to consider mathematical foundation and algorithmic aspects of Ethereum from the base network to high level of its functionality with the comparison to mathematical mechanisms of Bitcoin. In this thesis we describe Ethereum as stack of layers. Our mission is to extract cryptographic and mathematical mechanisms implemented in each layer.
\nWe present how hash function is utilized to construct cost function and Hashcash protocol. Hashcash protocol is implemented in Proof of Work (PoW) mechanism. Also, we explain how hash function is used to connect blocks in the chain of blocks and how hash function is used to organize transactions in a Merkle tree and in a Merkle-Patricia-trie.
\nThis thesis describes how Elliptic Curve Digital Signature Algorithm (ECDSA) and Lamport signing algorithm provide integrity of transactions. Elliptic Curve Integrated Encryption Scheme (ECIES) is hybrid encryption scheme which is utilized to provide confidentiality of transactions. The Elliptic Curve Cryptography (ECC) is used to disguise identities in both Bitcoin and Ethereum network. The new approaches to provide privacy are Ring signatures and Zk-Snarks.
\nThis thesis also explains Bloom filter structure in Ethereum. The Bloom filter is a probabilistic data structure to test membership of elements in big data bases.

Navneet Kaur, Nidhi Chahal, Ritu Dewan, Shikha Singh · 7 authors

Distributed ledger technology, a method of storing and maintaining the integrity of multiple copies of critical data using a massively redundant network of participating machines, has found a “killer application” in blockchain, a type of distributed ledger. A blockchain consists of sequential blocks that may never be modified or reordered, leaving a public, auditable record that is consistent and highly resistant to tampering and deletion. These qualities make blockchain eminently suitable for its most common use, cryptocurrency, and its occasional variants in the form of cryptocurrency tokens, used to represent ownership or some other right to virtual or physical goods and capabilities. Blockchain also enables smart contracts, discrete bodies of software written to serve both as the memorial and the means of execution of an agreement between parties. Smart contracts can have all the elements of a traditional contract, and as jurisdictions legislate or jurists rule on the fine points of enforceability and the acceptability of smart contracts as traditional contracts, applications in nearly every area of commerce have emerged. Digital lawyers may not need to become software developers, but deepening their understanding of the capabilities and limitations of the technology, developing a keen awareness of the issues at the intersection between code and the law, as well as the law’s readiness in this area, will be of great advantage to them and their clients in this rapidly evolving area at the intersection of technology, commerce and law.

Alexandre Marques Albano da Silveira

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.

Ayush Dubey, Greg D. Hill, Robert Escriva, Emin Gün Sirer

Graph databases have become an increasingly common infrastructure component. Yet existing systems either operate on offline snapshots, provide weak consistency guarantees, or use expensive concurrency control techniques that limit performance. In this paper, we introduce a new distributed graph database, called Weaver, which enables efficient, transactional graph analyses as well as strictly serializable ACID transactions on dynamic graphs. The key insight that allows Weaver to combine strict serializability with horizontal scalability and high performance is a novel request ordering mechanism called refinable timestamps. This technique couples coarse-grained vector timestamps with a fine-grained timeline oracle to pay the overhead of strong consistency only when needed. Experiments show that Weaver enables a Bitcoin blockchain explorer that is 8x faster than Blockchain.info, and achieves 12x higher throughput than the Titan graph database on social network workloads and 4x lower latency than GraphLab on offline graph traversal workloads.

Michele Spagnuolo, Federico Maggi, Stefano Zanero

No abstract is available for this record.