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40th IEEE International Conference on Data Engineering, ICDE 2024

作者： Gao, Junhui Wang, Qianru Zhang, Xin Shi, Juan Zhao, Xiang Han, Qingye Pan, Yan School of Computer Science Northwestern Polytechnical University China School of Computer Science and Technology Xidian University China Air Force Engineering University China National University of Defense Technology Laboratory for Big Data and Decision China School of Management Science and Real Estate Chongqing University China National University of Defense Technology National Key Laboratory of Information Systems Engineering China National University of Defense Technology National Key Laboratory of Parallel and Distributed Computing China

ISBN: (纸本)9798350317152

Instant delivery has become a fundamental service in people's daily lives. Different from the traditional express service, the instant delivery has a strict shipping time constraint after being ordered. However, the labor shortage makes it challenging to realize efficient instant delivery. To tackle the problem, researchers have studied to introduce vehicles (i.e., taxis) or Unmanned Aerial Vehicles (UAVs or drones) into instant delivery tasks. Unfortunately, the delivery detour of taxis and the limited battery of UAVs make it hard to meet the rapidly increasing instant delivery demands. Under this circumstance, this paper proposes an air-ground cooperative instant delivery paradigm to maximize the delivery performance and meanwhile minimize the negative effects on the taxi passengers. Specifically, a data-driven delivery potential-demands-aware cooperative strategy is designed to improve the overall delivery performance of both UAVs and taxis as well as the taxi passengers' experience. The experimental results show that the proposed method improves the delivery number by 30.1% and 114.5% compared to the taxi-based and UAV-based instant delivery respectively, and shortens the delivery time by 35.7% compared to the taxi-based instant delivery. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Some critical problems of botnets

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Jisuanji Xuebao/Chinese Journal of Computers 2012年第6期35卷 1192-1208页

作者： Wang, Tian-Zuo Wang, Huai-Min Liu, Bo Shi, Pei-Chang Institute of Network and Information Security School of Computer Science National University of Defense Technology Changsha 410073 China National Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha 410073 China

As a complex, flexible and effective platform for network attacking, the botnet spreads widely in the Internet. Botnets can provide the botmasters with the ability to launch large-scale malicious activities such as spamming and DDoS (distributed Denial of Service) attacks. Botnets are continuously bringing more and more severe threats, so that the study on botnets has already become one of the focuses in the field of network security. However, in recent years, some new developments of botnets are challenging the existing understanding on botnets. In this paper, according to the new conditions of botnets and the researches in existence, a definition of botnet is proposed based on the works of other researchers, taxonomies of botnets are introduced respectively from the views of network structure, dependency and delivery pattern of C&C (Command and Control) information. Then the techniques on detecting, measuring and restraining botnets are analyzed systematically. In the end, we give the evolution trends of botnets and the future research trends in this area.

关键词： Botnet

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A Multi-agent Simulation of Escape Panic

A Multi-agent Simulation of Escape Panic

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International Joint Conference on Computational sciences and Optimization, CSO

作者： Chuanjun Ren Chenghui Yang Shiyao Jin National Laboratory for Parallel & Distributed Processing College of Computer Science National University of Defense Technology Changsha China National Laboratory for Parallel & Distributed Processinz National University of Defense Technology Changsha China National University of Defense Technology Changsha Hunan CN

The modeling and simulation on evacuation has recently become a topic of great interest. We present an agent-based model to construct crowd evacuations for emergency response from an area under an explosion. Various types of agents are designed as well as the interactions of them are concerned in contrast to traditional models in which the total populations are considered to be consisted of identical individuals and the interactions between them are omitted. Different cases are taken into account to test the effect of our model by iterative simulations. At last, plenty simulation results suggest several effective ways to minimize the harmful consequences of such life-threaten events.

关键词： Explosions Computational modeling Computer simulation Testing Accidents Humans Analytical models Concurrent computing distributed computing distributed processing

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A Survey on Talking Head Generation: The Methods, Status and Challenges

SSRN

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SSRN 2023年

作者： Cai, Yali Qiao, Peng Li, Dongsheng National Key Laboratory of Parallel and Distributed Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China

The talking head generation aims to synthesize a speech video of the source identity from a driving video or audio or text data irrelevant to the source identity. It can not only be applied to games and virtual reality applications, but also provide data for fake data detection. In recent years, the research of talking head generation is widely popular, and the authenticity of the generated results has also been greatly improved. However, the synthetic results still have great room for progress. We summarize the existing researches in this paper, hoping to offer assistance for later researchers. Furthermore, we divide these methods into three categories according to the input data type, namely video, audio and text driven talking head generation methods, and analyze them in detail. In addition, we also summarize the data sets commonly used in this kind of research and explore the evaluation criteria for measuring the performance of the method. Finally, the shortcomings of the existing methods in this field and the future direction are presented in last section. © 2023, The Authors. All rights reserved.

关键词： Deep learning

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DaBA: Data-free Backdoor Attack against Federated Learning via Malicious Server

DaBA: Data-free Backdoor Attack against Federated Learning v...

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Image Processing, Computer Vision and Machine Learning (ICICML), International Conference on

作者： Kuiqi Chen Liming Fang Mengxin Wang Changchun Yin College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China Science and Technology on Parallel and Distributed Processing Laboratory (PDL) Changsha China

Current research shows that the privacy of FL is threatened by an honest-but-curious server. However, existing research focus on privacy attacks against the malicious server while overlooking that it could also compromise the shared model's integrity by introducing poisoning attacks. In this work, we propose a novel data-free backdoor attack (DaBA) against FL via malicious server to bridge the gap. Specifically, we utilize global model inversion to obtain a dummy dataset on the server side, then add backdoor triggers to a portion of the inputs in the dummy dataset and replace their labels with the target label, and finally retrain part of the global model on the poisoned dummy dataset. Our experimental results show that DaBA can achieve a high attack success rate on poisoned samples and high prediction accuracy on clean samples, which means the effectiveness and stealthiness of DaBA, respectively. For example, in the experiment of the MNIST dataset, DaBA can achieve a 99.6% attack success rate and 96.3% accuracy rate. We also discuss possible defense strategies against our attack. Our research reveals a significant security risk of FL.

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A Discrete Data Dividing Approach for Erasure-Code-Based Storage Applications

A Discrete Data Dividing Approach for Erasure-Code-Based Sto...

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2014 IEEE 8th International Symposium on Service Oriented System Engineering

作者： Weidong Sun Yijie Wang Yongquan Fu Xiaoqiang Pei Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha Hunan P. R. China

Erasure codes are promising for improving the reliability of the storage system due to its space efficiency compared to the replication methods. Traditional erasure codes split data into equalsized data blocks and encode strips in different data blocks. This brings heavy repairing traffic when clients read parts of the data, since most strips read for repairing are not in the expected blocks. This paper proposes a novel discrete data dividing method to completely avoid this problem. The key idea is to encode strips from the same data block. We could see that for repairing failed blocks, the strips to be read are either in the same data block with corrupted strips or from the encoded strips. Therefore, no data is wasted. We design and implement this data layout into a HDFS-like storage system. Experiments over a small-scale testbed shows that the proposed discrete data divided method avoids downloading data blocks that are not needed for clients during the repairing operations.

关键词： Strips Decoding Encoding distributed databases Writing Reliability Magnetic heads

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Learning environmental sounds with multi-scale convolutional neural network

arXiv

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arXiv 2018年

作者： Zhu, Boqing Wang, Changjian Liu, Feng Lei, Jin Lu, Zengquan Peng, Yuxing Science and Technology on Parallel and Distributed Laboratory National University of Defense Technology College of Meteorology and Oceanology National University of Defense Technology Changsha China

Deep learning has dramatically improved the performance of sounds recognition. However, learning acoustic models directly from the raw waveform is still challenging. Current waveform-based models generally use time-domain convolutional layers to extract features. The features extracted by single size filters are insufficient for building discriminative representation of audios. In this paper, we propose multi-scale convolution operation, which can get better audio representation by improving the frequency resolution and learning filters cross all frequency area. For leveraging the waveform-based features and spectrogram-based features in a single model, we introduce twophase method to fuse the different features. Finally, we propose a novel end-to-end network called WaveMsNet based on the multi-scale convolution operation and two-phase method. On the environmental sounds classification datasets ESC-10 and ESC-50, the classification accuracies of our WaveMsNet achieve 93.75% and 79.10% respectively, which improve significantly from the previous methods. Copyright © 2018, The Authors. All rights reserved.

关键词： Convolution

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JointCloud Cross-chain Verification Model of Decentralized Identifiers

JointCloud Cross-chain Verification Model of Decentralized I...

引用

IEEE International Conference on Performance, Computing and Communications (IPCCC)

作者： Tao Zhong Peichang Shi Junsheng Chang Science and Technology on Parallel and Distributed Processing Laboratory (PDL) Institute of Computer Technology College of Computer National University of Defense Technology Changsha China

ISBN: (纸本)9781665443326

When multiple entities communicate or collaborate in JointCloud, identities are the very prior basis to build trust with each other. Decentralized identifier (DID) can provide a trusted identity with blockchain technology and a complete method of identity verification based on verifiable credentials, which solves problems of conventional centralized identity. However, current DIDs can only conduct verification within a single blockchain, which limits the interoperability of DIDs on different blockchains. Network isolation hinders the verification of DIDs on different blockchains and thus there is a need to break the barrier between blockchains. In this paper, we propose a model to conduct cross-chain verification of DIDs. We build a system of credit evaluation to describe the credibility of DIDs in a unified way and deploy smart contracts to implement cross-chain verification of DIDs. Experimental results verifies the feasibility of the model, which realizes cross-chain verification of DIDs in the networks of blockchain.

关键词： Couplings Computational modeling Scalability Conferences Smart contracts Prototypes Data structures

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Stigmergic Collaboration: A Sign-Based Perspective of Stigmergy

Stigmergic Collaboration: A Sign-Based Perspective of Stigme...

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2010 International Conference on Intelligent Computation technology and Automation(2010 智能计算技术与自动化国际会议 ICICTA 2010)

作者： Chuanjun Ren Hongbing Huang Shiyao Jin National Laboratory for Parallel & Distributed Processing College of Computer Science National University of Defense Technology Changsha 410073 China

ISBN: (纸本)9781424472796

Insects build architecturally complex nests and search for remote food by collaboration work despite their limited sensors, minimal individual intelligence and the lack of a central control system. Insets' collaborations emerge as a response of the individual insects to Stigmergy. A sign-based model of Stigmergy to discuss collaboration is proposed in this paper where we picked up "sign" as a key notion to understand it. Therefore, sign is the link of all the components in a Stigmergic complex adaptive system. Based on this understanding, we propose a definition that reveals the nature of signs and exploit the significations and relationships carried by the notion of sign. Then, a sign-based model of Stigmergy is consequently reached, which captures the essentials of Stigmergy. A basic architecture of Stigmergy as well as its constituents are presented and discussed. At last, some applications of the model are discussed.

关键词： Stigmergy Sign Emergence Collaboration CAS

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Two-dimensional euler PCA for face recognition 21

Two-dimensional euler PCA for face recognition

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21st International Conference on MultiMedia Modeling, MMM 2015

作者： Tan, Huibin Zhang, Xiang Guan, Naiyang Tao, Dacheng Huang, Xuhui Luo, Zhigang Science and Technology on Parallel Distributed Processing Laboratory College of Computer National University of Defense Technology Changsha Hunan410073 China Department of Computer Science and Technology College of Computer National University of Defense Technology Changsha Hunan410073 China Centre for Quantum Computation and Intelligent Systems and the Faculty of Engineering and Information Technology University of Technology Sydney 235 Jones Street UltimoNSW2007 Australia

ISBN: (纸本)9783319144412

Principal component analysis (PCA) projects data on the directions with maximal variances. Since PCA is quite effective in dimension reduction, it has been widely used in computer vision. However, conventional PCA suffers from following deficiencies: 1) it spends much computational costs to handle high-dimensional data, and 2) it cannot reveal the nonlinear relationship among different features of data. To overcome these deficiencies, this paper proposes an efficient two-dimensional Euler PCA (2D-ePCA) algorithm. Particularly, 2D-ePCA learns projection matrix on the 2D pixel matrix of each image without reshaping it into 1D long vector, and uncovers nonlinear relationships among features by mapping data onto complex representation. Since such 2D complex representation induces much smaller kernel matrix and principal subspaces, 2D-ePCA costs much less computational overheads than Euler PCA on large-scale dataset. Experimental results on popular face datasets show that 2D-ePCA outperforms the representative algorithms in terms of accuracy, computational overhead, and robustness. © Springer International Publishing Switzerland 2015.

关键词： Principal component analysis

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