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Detecting Ethereum Phishing Scams via Multi-transaction-view Graph Attention network

Detecting Ethereum Phishing Scams via Multi-transaction-view...

引用

International conference on parallel and distributed Systems (ICPADS)

作者： Shaoxuan Zhuo Guang Li Weigang Wu Jing Bian School of Computer Science and Engineering Sun Yat-Sen University Guangzhou China Guangdong Province Key Laboratory of Big Data Analysis and Processing Chain Guangdong Province Key Laboratory of Computational Science Sun Yat-Sen University Guangzhou China

Cryptocurrency phishing scams is a significant treat to Ethereum, one of the most popular blockchain platforms. Most of existing Ethereum phishing detection methods are based on traditional machine learning or graph representation learning, which mostly rely on only statistical and structural features in local scope. In this paper, we propose Multi-transaction-view Graph Attention network (MTvGAT), a novel phishing scam detection model that can make use of transaction patterns of different scopes. To obtain global-view information, we apply graph clustering and construct the global-view graph with multiple clusters, including all the nodes of the original transaction network. To obtain local view information, we apply neighborhood sampling, and construct local-view graphs with target nodes and their neighborhood nodes. Then, node features, edge features, and attention coefficients are aggregated to merge multi-view information into representation of nodes. We further combine global-view and local-view representations to finally identify phishing addresses from target nodes. Extensive experiments demonstrate that the proposed method can outperform existing ones with significant improvement.

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network public opinion monitoring based on MapReduce

Network public opinion monitoring based on MapReduce

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2021 International conference on Artificial Intelligence and Information Technology, ICAIIT 2021

作者： Zhao, Yunhong Li, Suruo Jingchu University of Technology HuBei Jingmen China

Public opinion information on the network is abundantly decentralized in Internet, these false ones, easily misleading, not legally binding, it is difficult to deal with. Quickly master information is a prerequisite to deal with the network of public opinion, clustering algorithm in data mining plays an important role in in the collection of information statistics. Disadvantages of classical clustering methods are high resources consumption, low efficiency, high time and space complexity, and difficult to deal with large-scale data processing in massive network. To the network public opinion text as the research object, in-depth study of summarizing the network public opinion monitoring technology based on distributed MapReduce, including parallel technology, improved clustering algorithm, relational database and distributed database construction, which is in order to improve the efficiency of information processing, to reduce the pin. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： MapReduce

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A New Method for Evaluating Core Developers In Open Source Software 13

A New Method for Evaluating Core Developers In Open Source S...

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13th IEEE International conference on Software Engineering and Service Science, ICSESS 2022

作者： Song, Yulin Wang, Tao Shen, Yang Chang, Junsheng National University of Defense Technology National Laboratory for Parallel and Distributed Processing Hunan Province Changsha China National University of Defense Technology Institute for Quantum Information State Key Laboratory of High Performance Computing Hunan Province Changsha China

ISBN: (数字)9781665410328

ISBN: (纸本)9781665410311

The high-quality development of Open Source Software(OSS) benefits from the contributions of developers. An important research question is how to truly assess the extent of contribution of all developers in open source software and effectively identify the core developers to avoid their loss. In this paper, we use the undirected weighted network model to build a Developer Collaboration network(DCN) based on developers and their contributions to the GitHub community's open source software Rails, analyse the characteristics of developer partnerships through the Developer Collaboration network, and propose a Developer Personal Impact Factor(DPIF) to evaluate the importance of developer, select the top 10 core developers in Rails, focus on their participation in the open source software process, and predicting the changes of their contributions. The experimental results show that core developers with extensive partnerships are more likely to associate with developers with fewer partnerships. The average degree of developer contribution does not increase with more developers. Developer partnerships are characterized by close localization and loose overall relationships. The Developer Personal Impact Factor identifies the core developers in open source software well. The Developer Personal Impact Factor gives a ranking in which the core team members rank in the top 1.17% on average. © 2022 IEEE.

关键词： Open source software

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The Stream Reasoning System I-DLV-sr: Enhancements and Applications in Smart Cities 6th

The Stream Reasoning System I-DLV-sr: Enhancements and Appli...

引用

6th International Joint conference on Rules and Reasoning (RuleML+RR)

作者： Calimeri, Francesco Mastria, Elena Perri, Simona Zangari, Jessica Univ Calabria Dept Math & Comp Sci Arcavacata Di Rende Italy DLVSyst Srl Arcavacata Di Rende Italy

ISBN: (纸本)9783031215407;9783031215414

I-DLV-sr is a recently proposed logic-based system for reasoning over data streams, which relies on a framework enabling a tight, fine-tuned interaction between Apache Flink and the ASP system I-2-DLV. Flink enables distributed stream processing, whereas I2-DLV acts as full-fledged reasoner capable of transparently performing incremental evaluations. In this paper, we present a new and optimized version of I-DLV-sr that features an improved management of parallel computations and communications between Flink and I-2-DLV, along with new linguistic extensions aiming at allowing its effective application in smart city scenarios.

关键词： Stream reasoning Stream processing Knowledge representation and reasoning Answer set programming Smart city Applications

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A Cross-Platform OpenVX Library for FPGA Accelerators

A Cross-Platform OpenVX Library for FPGA Accelerators

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euromicro conference on parallel, distributed and network-based processing

作者： Maria Angélica Dávila-Guzmán Rubén Gran Tejero María Villarroya-Gaudó Darío Suárez Gracia Lester Kalms Diana Göhringer DIIS-I3A Universidad de Zaragoza – HiPEAC Network of Excellence Technische Universität Dresden – HiPEAC Network of Excellence

In Computer Vision, open programming standards such as OpenVX have emerged to bring together portability and acceleration across devices. Unfortunately, achieving both goals on FPGAs remains a challenge because FPGAs still require to adapt the code with proprietary extensions. Exclusively for Xilinx devices, the HiFlipVX open source library partially solves this problem by offering a clean C++ OpenVX API that offers the performance of proprietary extensions without exposing its complexity to programmer. While HiFlipVX enables portability within Xilinx devices, portability between FPGA manufacturers remains an open challenge. This work extends the HiFlipVX's capabilities with a twofold goal: i) to support Intel FPGA devices with different memory configurations, and ii) to enable execution on FPGAs as discrete accelerators. To accomplish these goals, the proposed implementation combines two HLS programming models: C++, using Intel's system of tasks that enables to coalesce nodes and reduce control overhead, and OpenCL, which provides efficient compute kernel nodes. On Intel FPGAs, compared with pure OpenCL implementations, the proposed implementation reduces kernel dispatch resources, saving up to 24% of ALUT resources for each kernel in a graph, and improves performance. Gains are 2.6× on average for representative applications, such as Canny edge detector, or Census transform, compared with state-of-the-art frameworks.

关键词： Performance evaluation C++ languages Transforms Programming Libraries Acceleration Kernel

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Trustless, Censorship-Resilient and Scalable Votings in the Permission-based Blockchain Model

Trustless, Censorship-Resilient and Scalable Votings in the ...

引用

26th International conference on parallel and distributed Computing (Euro-Par)

作者： Gajek, Sebastian Lewandowsky, Marco Flensburg Univ Appl Sci Flensburg Germany

ISBN: (纸本)9783030715939;9783030715922

Voting systems are the tool of choice when it comes to settle an agreement of different opinions. We propose a solution for a trustless, censorship-resilient and scalable electronic voting platform. By leveraging the blockchain together with the functional encryption paradigm, we fully decentralize the system and reduce the risks that a voting provider, like a corrupt government, does censor or manipulate the outcome.

关键词： Voting Functional encryption Blockchain Hyperledger

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GPU Optimization of Biological Macromolecule Multi-tilt Electron Tomography Reconstruction Algorithm 1

引用

19th International conference on Advanced Intelligent Computing Technology and Applications (ICIC)

作者： Fu, Zi-Ang Wan, Xiaohua Zhang, Fa Lanzhou Univ Sch Informat Sci & Engn Lanzhou 730000 Gansu Peoples R China Chinese Acad Sci Inst Comp Technol Beijing 100190 Peoples R China

ISBN: (数字)9789819947492

ISBN: (纸本)9789819947485;9789819947492

Three-dimensional (3D) reconstruction in cryo-electron tomography (cryo-ET) plays an important role in studying in situ biological macromolecular structures at the nanometer level. Owing to limited tilt angle, 3D reconstruction of cryo-ET always suffers from a "missing wedge" problem which causes severe accuracy degradation. Multi-tilt reconstruction is an effective method to reduce artifacts and suppress the effect of the missing wedge. As the number of tilt series increases, large size data causes high computation and huge memory overhead. Limited by the memory, multi-tilt reconstruction cannot be performed in parallel on GPUs, especially when the image size reaches 1 K, 2 K, or even larger. To optimize large-scale multi-tilt reconstruction of cryo-ET, we propose a newGPU-based large-scale multi-tilt tomographic reconstruction algorithm (GMSIRT). Furthermore, we design a two-level data partition strategy in GM-SIRT to greatly reduce the memory required in the whole reconstructing process. Experimental results show that the performance of the GM-SIRT algorithm has been significantly improved compared with DM-SIRT, the distributed multi-tilt reconstruction algorithm on the CPU cluster. The acceleration ratio is over 300%, and the memory requirement only decreases to one-third of DM-SIRT when the image size reaches 2 K.

关键词： Graphics processing unit

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Classification Algorithm for Motor Imagery EEG Signals based on Multi-Domain Information CNN

Classification Algorithm for Motor Imagery EEG Signals Based...

引用

distributed Computing and Electrical Circuits and Electronics (ICDCECE), IEEE International conference on

作者： Gengyou Xu Yumiao Ren Jieling Jiang Fei Yao Jiaxin Cao School of Electronic Information Engineering Xi'an Technological University Xi'an China

ISBN: (数字)9798350318609

ISBN: (纸本)9798350318616

In order to solve the problems of low recognition rate of single feature and poor adaptability of motor imagination EEG signals, a multi-input time-frequency-spatial hybrid convolution neural network algorithm is proposed in this paper. Classify and identify the motor imagery EEG signals. Firstly, the time domain signal matrix is obtained by pre-processing and data amplification of EEG signals, and then the time-frequency transform and spatial filtering of EEG signals are carried out by continuous wavelet transform and common space mode, respectively, and the time-frequency matrix and space-time matrix are obtained. finally, three types of characteristic matrices are input into the parallel hybrid convolution neural network training model, and the final classification results are obtained. The proposed method is verified by using the 2008 BCI competition Datasets2a data set, and the average classification accuracy is 94.81%. The results show that this method can effectively enhance the recognition rate of motor imagination, offering a novel idea and approach for the research on brain-computer interfaces related to motor imagination.

关键词： Training Time-frequency analysis Image recognition Continuous wavelet transforms Filtering Convolution Motors

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Quantum Information Technology for network Security: An Application-Focused Overview

Quantum Information Technology for Network Security: An Appl...

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IEEE International conference on Big Data and Cloud Computing (BdCloud)

作者： Huan Wang XiaoYang Lai China Electronics Technology Group Corporation Beijing China China Innovation Fund Management Co. Ltd Beijing China

In recent years, Quantum information technology (QIT) has accelerated its development in academic research with continuously highlights and achievements that have attracted the attention of the entire society. network security is currently the main application field of QIT and two types of quantum security products have been released: Quantum Key Distribution systems and Quantum Random Number Generators. This article introduces the two quantum security products and reveals that the application of QIT in network security is currently in its initial stage, consisting of a total of six stages. Both product and market sides need continuous innovation and development, and it may take time for QIT to truly manifest significant commercial value. It also offers prospects for the technological evolution of the two quantum products in the further process of industrialization, mainly involving the multiplexing of QKD with classical optical communication and the chip based QRNG. The aim of this study is to consolidate consensus and contribute to the industrial application of QIT in network security.

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Query Optimization and Rebalancing Methods based on CMD 2021

Query Optimization and Rebalancing Methods based on CMD

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3rd International conference on Big Data Engineering and Technology (BDET)

作者： Wang, Shuo Zhang, Zhaogong Meng, Qingyu Heilongjiang Univ Harbin Heilongjiang Peoples R China

ISBN: (纸本)9781450389280

As the amount of user data increase, the computer performance and I/O speed required for data processing and analysis are getting higher and higher. distributed file system has become the primary option for big data storage and query. According to the characteristics of high dimensionality and sparseness of data, this paper uses the distributed storage idea of CMD (coordinate modulo distribution) to store data in blocks. We only need to use cheap storage devices to form a distributed storage system, which solves the problem of big data disk I/O read performance to a certain extent. We have improved range query function under the CMD storage method;at the same time, the optimized B+ tree index technology has been used to solve the precise search problem of sparse data. Finally, in view of the unbalanced distribution of different sub-node data, we propose a new data rebalancing method on the CMD storage method.

关键词： Coordinate modulo distribution Multidimensional parallel query Data rebalance parallel storage

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