2019 IEEE International Conference on Blockchain (Blockchain)最新文献_第8页

Data Mining-Based Ethereum Fraud Detection 基于数据挖掘的以太坊欺诈检测

2019 IEEE International Conference on Blockchain (Blockchain) Pub Date : 2019-07-01 DOI: 10.1109/Blockchain.2019.00042

E. Jung, Marion Le Tilly, Ashish Gehani, Yunjie Ge

{"title":"Data Mining-Based Ethereum Fraud Detection","authors":"E. Jung, Marion Le Tilly, Ashish Gehani, Yunjie Ge","doi":"10.1109/Blockchain.2019.00042","DOIUrl":"https://doi.org/10.1109/Blockchain.2019.00042","url":null,"abstract":"The popularity of blockchain-based currencies, such as Bitcoin and Ethereum, has grown among enthusiasts since 2009. Relying on the anonymity provided by the blockchain, hustlers have adapted offline scams to this new ecosystem. As a result, Ponzi schemes are proliferating on Ethereum, dressed up as secure investment schemes. They reward early investors with funds from the later ones before collapsing, leaving the last investors empty handed. Illegal in the offline world, they are creating thousands of victims on Ethereum, while stealing millions of dollars worth of ether. We use data mining to provide a detection model for Ponzi schemes on Ethereum, improving over prior work. We built a dataset of likely benign Ethereum smart contracts, in addition to known Ponzi scheme smart contracts, and designed features based on their compiled code and transactions. Using Weka to benchmark several classification algorithms, we obtained models that achieve both high precision and high recall. Our 0-day model can be used as soon as a smart contract is uploaded on the blockchain. The full-feature model continued to show high performance for almost 250 days. A detailed analysis on top-strength features provides novel perspectives on Ponzi scheme behavior.","PeriodicalId":221068,"journal":{"name":"2019 IEEE International Conference on Blockchain (Blockchain)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126458019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 43

Aurora: A Robust and Trustless Verification and Synchronization Algorithm for Distributed Ledgers Aurora:一种用于分布式账本的鲁棒且无需信任的验证和同步算法

2019 IEEE International Conference on Blockchain (Blockchain) Pub Date : 2019-07-01 DOI: 10.1109/Blockchain.2019.00052

Federico Matteo Bencic, Alen Hrga, Ivana Podnar Žarko

{"title":"Aurora: A Robust and Trustless Verification and Synchronization Algorithm for Distributed Ledgers","authors":"Federico Matteo Bencic, Alen Hrga, Ivana Podnar Žarko","doi":"10.1109/Blockchain.2019.00052","DOIUrl":"https://doi.org/10.1109/Blockchain.2019.00052","url":null,"abstract":"Current consumer grade hardware running a full DLT node takes a long time to synchronize with the network and requires a lot of resources. Nodes that have never before synchronized with the network require significant resources to verify entire ledger history. The initial synchronization assumes inherent trust in the bootstrap nodes, which is a point of centralization. In the case when bootstrap nodes cannot be trusted, a new node might find itself in a malicious cluster of nodes that can either make the node waste resources before realizing that it has been exposed to malicious data, or subvert it into thinking that it has downloaded the longest chain. The Aurora algorithm is able to detect the existence of malicious cliques with a certain plausibility when a new node is attempting to synchronize with the network, and will try to exit cliques identified as malicious. If the node is unable to exit a malicious clique, the node will halt its operation. Furthermore, the same algorithm can be applied to verify if a specific transaction has been included into a referent block with a certain plausibility without the need to download the entire chain (or the header chain), or to trust centralized block explorers. Thus, the Aurora algorithm has the potential to significantly improve the scalability of DLT by reducing the time necessary for initial blockchain synchronization. Furthermore, it strengthens the trustless environment by incentivizing users not willing to run a full or even a light node to partly verify transaction inclusion without relying on third party entities.","PeriodicalId":221068,"journal":{"name":"2019 IEEE International Conference on Blockchain (Blockchain)","volume":"41 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125707166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Cascading Machine Learning to Attack Bitcoin Anonymity 级联机器学习攻击比特币匿名性

2019 IEEE International Conference on Blockchain (Blockchain) Pub Date : 2019-07-01 DOI: 10.1109/Blockchain.2019.00011

Francesco Zola, Maria Eguimendia, Jan L. Bruse, Raul Orduna Urrutia

引用次数: 30

TrustChain: Trust Management in Blockchain and IoT Supported Supply Chains TrustChain:区块链和物联网支持的供应链中的信任管理

2019 IEEE International Conference on Blockchain (Blockchain) Pub Date : 2019-06-05 DOI: 10.1109/Blockchain.2019.00032

Sidra Malik, Volkan Dedeoglu, S. Kanhere, R. Jurdak

{"title":"TrustChain: Trust Management in Blockchain and IoT Supported Supply Chains","authors":"Sidra Malik, Volkan Dedeoglu, S. Kanhere, R. Jurdak","doi":"10.1109/Blockchain.2019.00032","DOIUrl":"https://doi.org/10.1109/Blockchain.2019.00032","url":null,"abstract":"Traceability and integrity are major challenges for the increasingly complex supply chains of today's world. Although blockchain technology has the potential to address these challenges through providing a tamper-proof audit trail of supply chain events and data associated with a product life-cycle, it does not solve the trust problem associated with the data itself. Reputation systems are an effective approach to solve this trust problem. However, current reputation systems are not suited to the blockchain based supply chain applications as they are based on limited observations, they lack granularity and automation, and their overhead has not been explored. In this work, we propose TrustChain, as a three-layered trust management framework which uses a consortium blockchain to track interactions among supply chain participants and to dynamically assign trust and reputation scores based on these interactions. The novelty of Trustchain stems from: (a) the reputation model that evaluates the quality of commodities, and the trustworthiness of entities based on multiple observations of supply chain events, (b) its support for reputation scores that separate between a supply chain participant and products, enabling the assignment of product-specific reputations for the same participant, (c) the use of smart contracts for transparent, efficient, secure, and automated calculation of reputation scores, and (d) its minimal overhead in terms of latency and throughput when compared to a simple blockchain based supply chain model.","PeriodicalId":221068,"journal":{"name":"2019 IEEE International Conference on Blockchain (Blockchain)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124106380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 170

Access Control for Electronic Health Records with Hybrid Blockchain-Edge Architecture 基于混合区块链边缘架构的电子健康记录访问控制

2019 IEEE International Conference on Blockchain (Blockchain) Pub Date : 2019-06-04 DOI: 10.1109/Blockchain.2019.00015

Hao Guo, Wanxin Li, Mark M. Nejad, Chien-Chung Shen

引用次数: 84

C2P2: A Collective Cryptocurrency Up/Down Price Prediction Engine C2P2:一个加密货币上下价格预测引擎

2019 IEEE International Conference on Blockchain (Blockchain) Pub Date : 2019-06-03 DOI: 10.1109/Blockchain.2019.00065

Chongyang Bai, Thomas White, Linda Xiao, V. S. Subrahmanian, Ziheng Zhou

{"title":"C2P2: A Collective Cryptocurrency Up/Down Price Prediction Engine","authors":"Chongyang Bai, Thomas White, Linda Xiao, V. S. Subrahmanian, Ziheng Zhou","doi":"10.1109/Blockchain.2019.00065","DOIUrl":"https://doi.org/10.1109/Blockchain.2019.00065","url":null,"abstract":"We study the problem of predicting whether the price of the 21 most popular cryptocurrencies (according to coinmarketcap.com) will go up or down on day d, using data up to day d-1. Our C2P2 algorithm is the first algorithm to consider the fact that the price of a cryptocurrency c might depend not only on historical prices, sentiments, global stock indices, but also on the prices and predicted prices of other cryptocurrencies. C2P2 therefore does not predict cryptocurrency prices one coin at a time - rather it uses similarity metrics in conjunction with collective classification to compare multiple cryptocurrency features to jointly predict the cryptocurrency prices for all 21 coins considered. We show that our C2P2 algorithm beats out a recent competing 2017 paper by margins varying from 5.1-83% and another Bitcoin-specific prediction paper from 2018 by 16%. In both cases, C2P2 is the winner on all cryptocurrencies considered. Moreover, we experimentally show that the use of similarity metrics within our C2P2 algorithm leads to a direct improvement for 20 out of 21 cryptocurrencies ranging from 0.4% to 17.8%. Without the similarity component, C2P2 still beats competitors on 20 out of 21 cryptocurrencies considered. We show that all these results are statistically significant via a Student's t-test with p < 10^-5.","PeriodicalId":221068,"journal":{"name":"2019 IEEE International Conference on Blockchain (Blockchain)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115445796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Proximity Neighbor Selection in Blockchain Networks 区块链网络中的邻近邻居选择

2019 IEEE International Conference on Blockchain (Blockchain) Pub Date : 2019-06-03 DOI: 10.1109/Blockchain.2019.00016

Yusuke Aoki, Kazuyuki Shudo

引用次数: 20

A Security Reference Architecture for Blockchains 区块链的安全参考架构

2019 IEEE International Conference on Blockchain (Blockchain) Pub Date : 2019-04-15 DOI: 10.1109/Blockchain.2019.00060

I. Homoliak, Sarad Venugopalan, Qingze Hum, Pawel Szalachowski

引用次数: 27

Proteus: A Scalable BFT Consensus Protocol for Blockchains Proteus:用于区块链的可扩展BFT共识协议

2019 IEEE International Conference on Blockchain (Blockchain) Pub Date : 2019-03-11 DOI: 10.1109/Blockchain.2019.00048

M. M. Jalalzai, C. Busch, G. Richard

引用次数: 38

BlendMAS: A Blockchain-Enabled Decentralized Microservices Architecture for Smart Public Safety BlendMAS:用于智能公共安全的区块链分布式微服务架构

2019 IEEE International Conference on Blockchain (Blockchain) Pub Date : 2019-02-27 DOI: 10.1109/Blockchain.2019.00082

Ronghua Xu, S. Nikouei, Yu Chen, Erik Blasch, Alexander J. Aved

{"title":"BlendMAS: A Blockchain-Enabled Decentralized Microservices Architecture for Smart Public Safety","authors":"Ronghua Xu, S. Nikouei, Yu Chen, Erik Blasch, Alexander J. Aved","doi":"10.1109/Blockchain.2019.00082","DOIUrl":"https://doi.org/10.1109/Blockchain.2019.00082","url":null,"abstract":"Thanks to rapid technological advances in the Internet of Things (IoT), a smart public safety (SPS) system has become feasible by integrating heterogeneous computing devices to collaboratively provide public protection services. While service-oriented architecture (SOA) has been adopted by IoT and cyber-physical systems (CPS), it is difficult for a monolithic architecture to provide scalable and extensible services for a distributed IoT based SPS system. Furthermore, traditional security solutions rely on a centralized authority, which can be a performance bottleneck or single point failure. Inspired by microservices architecture and blockchain technology, this paper proposes a BLockchain-ENabled Decentralized Microservices Architecture for Smart public safety (BlendMAS). Within a permissioned blockchain network, a microservices based security mechanism is introduced to secure data access control in an SPS system. The functionality of security services is decoupled into separate containerized microservices that are built using a smart contract and deployed on edge and fog computing nodes. An extensive experimental study verified that the proposed BlendMAS is able to offer a decentralized, scalable and secured data sharing and access control to distributed IoT based SPS system.","PeriodicalId":221068,"journal":{"name":"2019 IEEE International Conference on Blockchain (Blockchain)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126647728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 47