Aug 1, 2018·2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE)
Saqib Ali, Guojun Wang, Bebo White, Roger Leslie Cottrell
The blockchain is an innovative technology which opened doors to new applications for solving numerous problems in distributed environments. In this work, we design a blockchain-based data storage and access framework for PingER (worldwide end-to-end Internet performance measurement project) to remove its total dependence on a centralized repository. We use the permissioned blockchain and Distributed Hash Tables (DHT) for this purpose. In the proposed framework, metadata of the files are stored on the blockchain whereas the actual files are stored off-chain through DHT at multiple locations using a peer-to-peer network of PingER Monitoring Agents. This will provide decentralized storage, distributed processing, and efficient lookup capabilities to the PingER framework.
This work presents ChainFS, a middleware system that secures cloud storage services using a minimally trusted Blockchain. ChainFS hardens the cloud-storage security against forking attacks. The ChainFS middleware exposes a file-system interface to end users. Internally, ChainFS stores data files in the cloud and exports minimal and necessary functionalities to the Blockchain for key distribution and file operation logging. We implement the ChainFS system on Ethereum and S3FS and closely integrate it with FUSE clients and Amazon S3 cloud storage. We measure the system performance and demonstrate low overhead.
Jul 1, 2018·2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)
Robert Norvill, Beltrán Borja Fiz Pontiveros, Radu State, Andréa Cullen
In this paper we propose a system that moves the bytecode of an Ethereum contract creation transaction off-chain. As blockchains are append-only we present a way to help reduce the chain size and growth for Ethereum. Contract creation transaction data is replaced with hashes which identify a file in InterPlanetary File System (IPFS). Doing so reduces the size of data stored in such transactions by 93.86% in our dataset. The proposed system retains the assurance provided by blockchain and reduces network traffic under certain conditions.
When dot.com has become a quaint idea, when electronic shops have lost the mass attention, while classical and margin trading has become obsolete, something new is coming: cryptocurrencies. Hundreds of virtual coins have been invented for a single reason: the profit. The high price volatility of these new markets and the fact that the virtual coins price is not regulated by a central bank or a single exchange, gives us opportunities for arbitrage trading. The existence of important price differences makes possible the profit when an automated system buy cheaper and sell more expensive in the same time. This paper will present the general principles underpinning the implementation of arbitrage trading software for virtual coins market. The very large number of cryptocurrencies and exchanges fundamentally change the server architecture of the trading software. The distributed price data in hundreds of sources and the technical differences of each of these data providers make all the things difficult to be implemented in a single application. The low-latency order calculation needed for the fast delivery before a significant price change, in the presence of thousands of price quotes coming from hundreds of distributed servers makes everything special.
Die Preisvorhersage ist eine der größten Herausforderungen der quantitativen Finanzierung. Diese Thesis stellt ein Neuronales Netz-Framework vor, das eine tiefgreifende maschinelle Lernlösung für das Preisvorhersageproblem bietet. Das Framework wird in drei Zeitpunkten mit einem Multilayer Perzeptron (MLP), einem einfachen Recurrent Neural Network (RNN) und einem Long Short Term Memory (LSTM) realisiert, die lange Abhängigkeiten lernen können. Wir beschreiben die Theorie der neuronalen Netze und des Deep Learning, um eine reproduzierbare Methode für unsere Anwendungen auf dem Kryptowährungsmarkt zu erstellen. Da die Preisvorhersage verwendet wird, um finanzielle Entscheidungen wie Handelssignale zu treffen, vergleichen wir verschiedene Ansätze des Vorhersageproblems, indem wir überwachte Lernmethoden in Klassifikationsaufgaben untersuchen. Wir untersuchen diese Modelle, um Preisrichtungen von wichtitgen Kryptowährungen außerhalb der Stichprobe mit einer rolling window regression Methode vorherzusagen. Für dieses Ziel erstellen wir ein Klassifikationsproblem, das voraussagt, ob der Preis jeder Kryptowährung als Grundlage für dreimonatige Handelsstrategien erheblich zu- oder abnimmt. Wir bauen verschiedene Handelsstrategien auf, basierend auf Long- oder Long- / Short-Positionen, die auf unseren Prognosen aufbauen, und vergleichen ihre Performance mit einer passiven Index-Investition auf dem Cryptowährungsmarkt, die CRIX (Trimborn and Härdle, 2016) folgt. Cryptocurrencies, Bitcoins sind die bekanntesten, basieren auf elektronischem Geld auf Blockchain-Technologie, die als eine dezentrale Alternative zu Währungen verwendet werden kann. Dank ihrer zahlreichen Anwendungen hat der Markt für Kryptowährung im Jahr 2017 ein exponentielles Wachstum erfahren. Wir vergleichen verschiedene gewichtete Portfolios, um zu testen, wie ein Anleger von fundamentalen Indikatoren wie der Marktkapitalisierung profitieren kann. Wir finden, dass LST die beste Genauigkeit für die Vorhersage von Richtungsbewegungen für die wichtigsten Kryptowährungen von CRIX hat und dass ein gleich gewichtetes Portfolio CRIX in den ersten Quartalen 2017 schlägt.
This thesis focuses on the integration of smart contracts into the Bazo Blockchain with the goal of creating a platform for decentralized applications. Smart contracts are programs that are stored on a blockchain and can be triggered by transactions. Smart contracts offer opportunities in automation and bring along advantages provided by blockchains such as immutability, public visibility of transactions and decentralization. As blockchains are trust-less protocols, it is guar- anteed that smart contracts are executed as intended. The integration of smart contracts was solved by implementing a virtual machine that executes the instructions sent by a transaction. This stack based virtual machine uses byte arrays as base type, which enables the virtual machine to deal with numbers of arbitrary length. Working with elements of arbitrary size requires taking the length of the elements into account, when calculating the gas cost, in addition to the base cost of the instruction type. Furthermore, the virtual machine was embedded within the mining application, which required to alter the blockchain protocol and the mining application. As a result, smart contracts can be deployed and transactions that call functions of smart contracts can be executed. Calling a smart contract function leads to the execution of the contract in the virtual machine and persisting the result in the blockchain. The Bazo Blockchain contin- ues to be a research project, this means it’s not ready for production use due to complex setup and handling. Follow-up theses could simplify the development of smart contracts for the Bazo Blockchain by creating a high-level programming language that can be compiled to Bazo virtual machine instructions.
Jun 1, 2018·2018 5th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/2018 4th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom)
Information Centric Networking (ICN) achieves high efficient via in-networking cache and direct object retrieval, i.e., content can be replicated and cached at any network nodes. However, the content is out of owner's control after published. With access control issues becoming more prominent, we propose combining the blockchain with traditional access control schemes in this paper. As all we know, blockchain has become one of the most popular technologies in recent years. This technology has been applied to various cryptographic currency, such as Bitcoin, Litecoin and so on. Due to its decentralized and untempered paradigm, using blockchain in access control is an ideal scheme. We utilize xor-based encoding/decoding scheme to realize fast encryption and decryption, which would save content provider plenty of time. Especially, when the content provider is off-line, our scheme could realize that authorized users also can obtain decryption information related contents. The security analysis proves that our access control framework is pretty safe.
The rise in popularity of permissioned blockchain platforms in recent time is significant. Hyperledger Fabric is one such permissioned blockchain platform and one of the Hyperledger projects hosted by the Linux Foundation. The Fabric comprises various components such as smart-contracts, endorsers, committers, validators, and orderers. As the performance of blockchain platform is a major concern for enterprise applications, in this work, we perform a comprehensive empirical study to characterize the performance of Hyperledger Fabric and identify potential performance bottlenecks to gain a better understanding of the system. We follow a two-phased approach. In the first phase, our goal is to understand the impact of various configuration parameters such as block size, endorsement policy, channels, resource allocation, state database choice on the transaction throughput & latency to provide various guidelines on configuring these parameters. In addition, we also aim to identify performance bottlenecks and hotspots. We observed that (1) endorsement policy verification, (2) sequential policy validation of transactions in a block, and (3) state validation and commit (with CouchDB) were the three major bottlenecks. In the second phase, we focus on optimizing Hyperledger Fabric v1.0 based on our observations. We introduced and studied various simple optimizations such as aggressive caching for endorsement policy verification in the cryptography component (3x improvement in the performance) and parallelizing endorsement policy verification (7x improvement). Further, we enhanced and measured the effect of an existing bulk read/write optimization for CouchDB during state validation & commit phase (2.5x improvement). By combining all three optimizations1, we improved the overall throughput by 16x (i.e., from 140 tps to 2250 tps).
Being a new kind of software leveraging blockchain to execute real contracts, smart contracts are in great demand due to many advantages. Ethereum is the largest blockchain platform that supports smart contracts by running them in its virtual machine. To ensure that a smart contract will terminate eventually and prevent abuse of resources, Ethereum charges the developers for deploying smart contracts and the users for executing smart contracts. Although our previous work shows that under-optimized smart contracts may cost more money than necessary, it just lists 7 anti-patterns and the detection method for 3 of them. In this paper, we conduct the first in-depth investigation on such under-optimized smart contracts. We first identify 24 anti-patterns from the execution traces of real smart contracts. Then, we design and develop GasReducer, the first tool to automatically detect all these anti-patterns from the bytecode of smart contracts and replace them with efficient code through bytecode-to-bytecode optimization. Using GasReducer to analyze all smart contracts and their execution traces, we detect 9,490,768 and 557,565,754 anti-pattern instances in deploying and invoking smart contracts, respectively.
Doriane Perard, Jérôme Lacan, Yann Bachy, Jonathan Detchart
The concept of a decentralized ledger usually implies that each node of a blockchain network stores the entire blockchain. However, in the case of popular blockchains, which each weigh several hundreds of GB, the large amount of data to be stored can incite new or low-capacity nodes to run lightweight clients. Such nodes do not participate to the global storage effort and can result in a centralization of the blockchain by very few nodes, which is contrary to the basic concepts of a blockchain. To avoid this problem, we propose new low storage nodes that store a reduced amount of data generated from the blockchain by using erasure codes. The properties of this technique ensure that any block of the chain can be easily rebuild from a small number of such nodes. This system should encourage low storage nodes to contribute to the storage of the blockchain and to maintain decentralization despite of a globally increasing size of the blockchain. This system paves the way to new types of blockchains which would only be managed by low capacity nodes.
Hao Xu, Long Yu, Liu Zhiqiang, Zhen Liu · 5 authors
This paper describes a novel Byzantine fault tolerant protocol that allows replicas to join and exit dynamically. With the astonishing success of cryptocurrencies, people attach great importance in “blockchain” and robust Byzantine fault tolerant (BFT) protocols for consensus. Among the conventional wisdom, the Practical Byzantine Fault Tolerance (PBFT), proposed by Miguel and Liskov in 1999, occupies an important position. Although PBFT has many advantages, it has fatal disadvantages. Firstly, it works in a completely enclosed environment, where users who want to add or take out any node must stop the whole system. Secondly, although PBFT guarantees liveness and safety if at most [n-1/ 3] c out of a total n replicas are faulty, it takes no measure to deal with these ineffective or malicious replicas, which is harmful to the system and will cause system crash finally. These drawbacks are unbearable in practice. In order to solve them, we present an alternative, Dynamic PBFT.
Decentralized currencies and similar blockchain applications require consensus. Bitcoin achieves eventual consensus in a fully-decentralized setting, but provides very low throughput and high latency with excessive energy consumption. In this paper, we propose identity aging as a novel and more efficient consensus approach. Our main idea is to establish reliable, long-term identities and choose the oldest identity as the miner on each round. Based on this approach, we design two blockchain systems. Our first system, SCIFER, leverages Intel's SGX attestation for identity bootstrapping in a partially-decentralized setting, where blockchain is permissionless, but we trust Intel for attestation. Our second system, DIFER, creates new identities through a novel mining mechanism and provides consensus in a fully-decentralized setting, similar to Bitcoin. One of the main benefits of identity aging is that it does not require constant computation. Our analysis and experiments show that identity aging provides significant performance improvements over Bitcoin with strong security guarantees.
In identity federations, users assigned to identity providers (IDPs) can access applications operated by service providers (SPs) without SP-specific credentials for authentication and authorization. While OpenID Connect and SAML are the two most widely adopted federation standards, using them inherently results in a trade-off between data quality guarantees and scalability, given how they handle the Metadata about the involved IDPs and SPs. This paper presents a novel approach for federation membership and federation Metadata management based on Distributed Ledger Technology. It applies the core idea of Certificate Transparency, as known from Global-PKI certificate authorities for X.509v3 server certificates, to SAML federation Metadata; therefore, it achieves OpenID Connect's federation building flexibility without losing the significant advantages of traditional SAML federations. An implementation based on Hyperledger Fabric is used to evaluate typical use cases by measuring impacts on Metadata distribution latency and Metadata size, and to discuss the feasibility of the presented approach.
The importance of big data in machine learning cannot be overemphasized in recent times. Through the evolution of big data, most scientific technologies that relied heavily on enormous data in solving complex issues in human lives gained grounds; machine learning is an instance of these technologies. Various machine learning models that yield groundbreaking throughputs with high efficiency rates in predicting, detecting, classifying, discovering and acquiring in-depth knowledge about events that would otherwise be very difficult to ascertain have been made possible due to big data. Although big data has undoubtedly helped in the field of machine learning research ,over the years, its mode of acquisition has posed great challenge in industries,education and other agencies that obtained them for various purposes. This is because these large quantities of data cannot be stored on personal computers with limited storage capabicity but required the use of high storage capacity servers for effective storage. These servers may be owned by a group of companies or individuals who had the singular priviledge to modify the data in their possession as and when deemed relevant thus the creation of a centralized data storage environment. These were mostly refered to as the Third Parties (TP) in the data acquisition process. For the services they rendered, these trusted parties priced data in their possession expensively. The adverse effect is a limitation on various researches that could help solve a number of problems in human lives. It is worth mentioning that the security of these data being purchased expensively cannot be even assured limiting various researches that thrive on secured data. In order to curb these occurrences and have better machine learning models, the incorporation of Blockchain Technology databases into machine learning. This paper discusses the concept of big data, Machine Learning and Blockchains. It further discusses how Big data has impacted the Machine learning Community, the significance of Machine Learning and how the BlockChain Technology could be used similarly impact the Machine Learning Community. The aim of this paper is to encourge further research in incoporating the BlockChain Technology into Machine Learning.
Initial Coin Offerings (ICO) are public offers of new cryptocurrencies in exchange of existing ones, aimed to finance projects in the blockchain development arena. In the last 8 months of 2017, the total amount gathered by ICOs exceeded 4 billion US$, and overcame the venture capital funnelled toward high tech initiatives in the same period. A high percentage of ICOS is managed through Smart Contracts running on Ethereum blockchain, and in particular to ERC-20 Token Standard Contract. In this work we examine 1388 ICOs, published on December 31, 2017 on icobench.com Web site, gathering information relevant to the assessment of their quality and software development management, including data on their development teams. We also study, at the same date, the financial data of 450 ICO tokens available on coinmarketcap.com Web site, among which 355 tokens are managed on Ethereum blochain. We define success criteria for the ICOs, based on the funds actually gathered, and on the behavior of the price of the related tokens, finding the factors that most likely influence the ICO success likeliness.
Sheng Wang, Tien Tuan Anh Dinh, Qian Lin, Zhongle Xie · 10 authors
Existing data storage systems offer a wide range of functionalities to accommodate an equally diverse range of applications. However, new classes of applications have emerged, e.g., blockchain and collaborative analytics, featuring data versioning, fork semantics, tamper-evidence or any combination thereof. They present new opportunities for storage systems to efficiently support such applications by embedding the above requirements into the storage. In this paper, we present ForkBase, a storage engine specifically designed to provide efficient support for blockchain and forkable applications. By integrating the core application properties into the storage, ForkBase not only delivers high performance but also reduces development effort. Data in ForkBase is multi-versioned, and each version uniquely identifies the data content and its history. Two variants of fork semantics are supported in ForkBase to facilitate any collaboration workflows. A novel index structure is introduced to efficiently identify and eliminate duplicate content across data objects. Consequently, ForkBase is not only efficient in performance, but also in space requirement. We demonstrate the performance of ForkBase using three applications: a blockchain platform, a wiki engine and a collaborative analytics application. We conduct extensive experimental evaluation of these applications against respective state-of-the-art system. The results show that ForkBase achieves superior performance while significantly lowering the development cost.
Beltrán Borja Fiz Pontiveros, Robert Norvill, Radu State
In this work we propose a compression method for smart contracts deployed in the Ethereum blockchain. By taking advantage of the repetition of sections of bytecode among multiple smart contracts previously deployed in the Ethereum blockchain we propose a new pseudo opcode that acts as a pointer that will allow smart contracts to reuse previously deployed code. We show that our proposed algorithm achieves space savings of up to 75% in a dataset of deployed Ethereum smart contracts bytecode, on par with other state of the art compression algorithms while remaining compatible with other methods currently in use for space reduction.
Derrick Chan, R. O. Decker, William Nguyen, Yuya Oguchi
Cryptocurrencies are rapidly receiving mainstream attention and adoption. As a result, new technologies are developing to store and transact cryptocurrencies to keep up with a rapidly developing market. We have developed a way to utilize a mobile phone to communicate with the Ethereum blockchain in order to monitor and initiate cryptocurrency transactions. The project allows users to create new Ethereum addresses and to send arbitrary amounts of Ether to existing Ethereum addresses, while maintaining security for the end user. We conclude that this method of communication with the Ethereum blockchain is viable and is an avenue for exploration in the future. As a result from this project, we anticipate a growth of new cryptocurrency applications on mobile devices. Furthermore, the various security features utilized in this project such as pin randomization, mnemonic recovery, and hardware level encryption can be implemented in other applications to increase security for all users.
Cryptocurrencies has become a very hot topic recently, with Bitcoin being the most popular. The increase in interest has led to an incentive to create payment systems for the currency that makes it easier to use for day-to-day shopping. A lot of companies are inves- tigating possible solutions for credit cards that are used for cryptocurrencies. This thesis aims to present and perform a security analysis on an already created concept of a credit card payment system for Bitcoin. The security analysis is done in a systematical approach where the modules were analyzed with predetermined restrictions and assumptions. The restricitons and assumptions are then removed one-by-one to find potential threats in the system. The outcome of the analysis is then evaluated in an attempt to find possible im- plementation methods that would mitigate or prevent the discovered threats. The possible implementations are also evaluated in terms of how they would affect the system.
With increasing popularity, the scalability of blockchain-based crypto-currencies becomes an urgent concern. Bitcoin, among other crypto-currencies, have known limitations in transaction throughput and speedbut no agreed upon solution. Many of the proposals increasing throughput also increase the load on the Bitcoin network. Lightning is a proposal enabling payments to be conducted without affecting the Bitcoin network. Lightning is a protocol using payment channels to enable instant and cheap payments using the blockchain for security. With Lightning, payments can be sent through a network of nodes connected by payment channels. In this thesis, the current state of Lightning is explored and an evaluation for use on Bitcoin exchanges is performed. The usability, privacy and security of Lightning are the topics evaluated. In order to evaluate the usability, an exchange interface application was built allowing deposits and withdrawals using Lightning. The protocol specification and relevant literature are examined in order to evaluate the security and privacy of Lightning. The exchange interface showed that Lightning can be integrated into an exchange and provide a fast and cheap way to deposit and withdraw money for clients. In this paper some integration designs are proposed and ways to improve the client user experience are discussed. The Lightning node implementations need to mature a bit before real usage and there are some security issues that also need to be considered. With monitoring and network analysis the privacy can be compromised.