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5th International Conference on Electronic engineering and Informatics, EEI 2023

作者： Li, Chenwei Pan, Mengyuan Yang, Bo Zhang, Hengwei Henan Key Laboratory of Information Security State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Guizhou University School of Chemistry and Chemical Engineering Guiyang China

ISBN: (纸本)9798350327076

Convolutional neural networks are widely used in computer vision and image processing. However, when the original input is added with manually imperceptible perturbations, these deep network models mostly tend to output incorrect predictions. The vulnerability of these models poses great threat to intelligent applications, and these manually imperceptible perturbations are called adversarial examples. Current baseline methods have achieved considerable white-box attack success rate, but black-box rate remains to be improved. To boost the adversarial generalization, ensemble models method is introduced to the process of generating adversarial examples. This paper proposes multiple ensemble strategies with baseline attack methods based on existing ensemble strategy used by former methods. Experiment on ImageNet dataset empirically verifies the optimal ensemble strategy on boosting adversarial generalization. © 2023 IEEE.

关键词： Image classification

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Honeypot Detection Method Based on Anomalous Requests Response Differences 23

Honeypot Detection Method Based on Anomalous Requests Respon...

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6th International Conference on Electronics, Communications and Control engineering, ICECC 2023

作者： Chen, Xingyu Lu, Bin Sun, Rongbo Jiang, Mi State Key Laboratory of Mathematical Engineering and Advanced Computing Information Engineering University China Cyber Security College Information Engineering University China

ISBN: (纸本)9798400700002

Honeypot detection is a popular technology in the current cyber security, which can be used to check the disguise and protection level of deployed honeypots. To address the problem of low detection accuracy of existing honeypot detection techniques, this paper proposes a honeypot detection method based on the differences of anomalous requests' response. The method uses the anomalous request packet construction method designed in this paper to construct anomalous request packets, and sends the constructed anomalous request packets to the identity-known devices to collect the responses. Combined with the responses analysis method designed in this paper, the responses are analyzed in terms of similarity in both content and structure dimensions, which enables the evaluation of anomalous request packets in turn, and the selection of those that can consistently trigger a differential response from the honeypots to form a probing packets set based on anomaly. A deep learning model aiming at honeypot detection is designed using the responses of the identity-known devices in response to the probing packets set based on anomaly. The model and the responses of the nodes to detect to the probing packets set based on anomaly are used to detect honeypots. Experiment shows that the method is able to detect the nodes to detect with an accuracy of 96.4%. © 2023 ACM.

关键词： Deep learning

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Pixel+ and Pixel++: Compact and Efficient Forward-Secure Multi-Signatures for PoS Blockchain Consensus 33

Pixel+ and Pixel++: Compact and Efficient Forward-Secure Mul...

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33rd USENIX Security Symposium, USENIX Security 2024

作者： Wei, Jianghong Tian, Guohua Wang, Ding Guo, Fuchun Susilo, Willy Chen, Xiaofeng Xidian University China State Key Laboratory of Mathematical Engineering and Advanced Computing China College of Cyber Science Nankai University China School of Computing and Information Technology University of Wollongong Australia

ISBN: (纸本)9781939133441

Multi-signature schemes have attracted considerable attention in recent years due to their popular applications in PoS blockchains. However, the use of general multi-signature schemes poses a critical threat to the security of PoS blockchains once signing keys get corrupted. That is, after an adversary obtains enough signing keys, it can break the immutable nature of PoS blockchains by forking the chain and modifying the history from some point in the past. Forward-secure multi-signature (FS-MS) schemes can overcome this issue by periodically updating signing keys. The only FS-MS construction currently available is Drijvers et al's Pixel, which builds on pairing groups and only achieves forward security at the time period level. In this work, we present new FS-MS constructions that either are free from pairing or capture forward security at the individual message level (i.e., fine-grained forward security). Our first construction Pixel+ works for a maximum number of time periods T. Pixel+ signatures consist of only one group element, and can be verified using two exponentiations. It is the first FS-MS from RSA assumption, and has 3.5x and 22.8x faster signing and verification than Pixel, respectively. Our second FS-MS construction Pixel++ is a pairing-based one. It immediately revokes the signing key's capacity of re-signing the message after creating a signature on this message, rather than at the end of the current time period. Thus, it provides more practical forward security than Pixel. On the other hand, Pixel++ is almost as efficient as Pixel in terms of signing and verification. Both Pixel+ and Pixel++ allow for non-interactive aggregation of signatures from independent signers and are proven to be secure in the random oracle model. In addition, they also support the aggregation of public keys, significantly reducing the storage overhead on PoS blockchains. We demonstrate how to integrate Pixel+ and Pixel++ into PoS blockchains. As a proof-of-concept, we prov

关键词： Blockchain

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Multiuser Computation Offloading for Long-Term Sequential Tasks in Mobile Edge computing Environments

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Tsinghua Science and Technology 2023年第1期28卷 93-104页

作者： Huanhuan Xu Jingya Zhou Wenqi Wei Baolei Cheng School of Computer Science and Technology Soochow UniversitySuzhou 215006China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214125China Provincial Key Laboratory for Computer Information Processing Technology Soochow UniversitySuzhou 215006China School of Computer Science Georgia Institute of TechnologyAtlantaGA 30332USA

Mobile edge computing has shown its potential in serving emerging latency-sensitive mobile applications in ultra-dense 5G networks via offloading computation workloads from the remote cloud data center to the nearby network ***,current computation offloading studies in the heterogeneous edge environment face multifaceted challenges:Dependencies among computational tasks,resource competition among multiple users,and diverse long-term *** applications typically consist of several functionalities,and one huge category of the applications can be viewed as a series of sequential *** this study,we first proposed a novel multiuser computation offloading framework for long-term sequential ***,we presented a comprehensive analysis of the task offloading process in the framework and formally defined the multiuser sequential task offloading ***,we decoupled the long-term offloading problem into multiple single time slot offloading problems and proposed a novel adaptive method to solve *** further showed the substantial performance advantage of our proposed method on the basis of extensive experiments.

关键词： mobile edge computing sequential tasks computation offloading dependency

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Impacts of spatially inconsistent permafrost degradation on streamflow in the Lena River Basin

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Science China(Technological Sciences) 2024年第11期67卷 3559-3570页

作者： XUE ZeHuan WANG YiChu ZHAO Yi LI DongDeng BORTHWICK Alistair George Liam The Key Laboratory of Water and Sediment Sciences Ministry of EducationCollege of Environmental Sciences and EngineeringPeking UniversityBeijing 100871China College of Water Sciences Beijing Normal UniversityBeijing 100875China State Key Laboratory of Hydraulics and Mountain River Engineering Sichuan UniversityChengdu 610065China State Environmental Protection Key Laboratory of All Materials Fluxes in River Ecosystems Peking UniversityBeijing 100871China School of Engineering The University of EdinburghEdinburgh EH93JLUnited Kingdom School of Engineering Computing and MathematicsUniversity of PlymouthPlymouth PL48AAUnited Kingdom

Although permafrost degradation contributes significantly to hydrological change in cold regions, gaps remain in our understanding of streamflow variation induced by degrading permafrost in different river basins. We therefore used a deep learning model to simulate the long-term(≥ 30 years) monthly streamflow at 60 hydrological stations along the Lena River, the third longest circum-Arctic river. Analyzing the effects of precipitation, temperature, and thaw depth on streamflow variation throughout the Lena River Basin, we identified two feedback patterns relating streamflow to warming permafrost, observed in areas of continuous and discontinuous permafrost. In northern plain regions with continuous permafrost, 94% of stations presented an increasing trend in annual streamflow from the 1900s to the 2010s due to permafrost degradation. The enhanced streamflow was mainly due to increased meltwater in the flood season. In southern regions covered by both continuous and discontinuous permafrost, approximately 38% of stations exhibited a declining trend in annual streamflow in response to permafrost degradation, with a high proportion(61%) located in mountain regions(elevation ≥ 500 m). The decline is attributed to the enhanced infiltration capacity of thawing frozen layers within discontinuous permafrost regions. Our study provides new insights into the mechanisms behind permafrost degradation-induced streamflow variation and highlights the importance of formulating tailored strategies for sustainable river management in cold regions experiencing climate change.

关键词： permafrost degradation streamflow variation deep learning model climate change large cold basin

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Numerical analysis of the performance of a three-bladed vertical-axis turbine with active pitch control using a coupled unsteady Reynolds-averaged Navier-Stokes and actuator line model

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Journal of Hydrodynamics 2023年第3期35卷 516-532页

作者： Rui-wen Zhao Angus C.W.Creech Ye Li Vengatesan Venugopal Alistair G.L.Borthwick Laboratory of Multi-function Towing Tank State Key Laboratory of Ocean EngineeringSchool of Naval ArchitectureOcean and Civil EngineeringShanghai Jiao Tong UniversityShanghai 200240China School of Engineering and Physical Sciences Heriot-Watt UniversityEdinburghUK School of Engineering The University of EdinburghEdinburghUK School of Engineering Computing and MathematicsUniversity of PlymouthPlymouthUK

In this paper,we present a numerical model of a vertical-axis turbine(VAT)with active-pitch torque *** model is based upon the Wind and Tidal Turbine Embedded Simulator(WATTES)and WATTES-V turbine realisations in conjunction with the actuator line method(ALM),and uses OpenFOAM to solve the unsteady Reynolds-averaged Navier-Stokes(URANS)equations with two-equation k-εturbulence *** novel pitch-controlled system is based on an even pressure drop across the entire rotor to mitigate against dynamic stall at low tip speed *** numerical model is validated against experimental measurements and alternative numerical predictions of the hydrodynamic performance of a 1:6 scale UNH-RM2 hydrokinetic *** deploying the variable pitch mechanism exhibit improved turbine performance compared to measured data and fixed zero-pitch model ***-wake characteristics are investigated by examining the vorticity distribution near the *** pitch-controlled system is demonstrated to theoretically decrease turbulence generated by turbine rotations,mitigate the intensity of vortex shedding and size of detached vortices,and significantly enhance the performance of a vertical-axis hydrokinetic turbine for rated tip-speed ratios.

关键词： Vertical-axis turbine pitch control hydrodynamic performance unsteady Reynolds-averaged Navier-Stokes(URANS) numerical simulation

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Research on key Techniques for Reverse engineering of Deep Learning Models for x86 Executable Files 24

Research on Key Techniques for Reverse Engineering of Deep L...

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2024 7th International Conference on Computer Information Science and Artificial Intelligence, CISAI 2024

作者： Shi, Meng Lin, Wei Deng, Wenbo College of Cyberspace Security Information Engineering University Henan Zhengzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing Department of Cyberspace Security Henan Zhengzhou China

ISBN: (纸本)9798400707254

In recent years, with the continuous development of machine learning and deep learning, their related applications have gradually appeared in our field of vision, showing explosive growth. A deep learning compiler optimizes a deep learning model, compiles it, and generates a binary file. When this binary file is placed into an edge device, the device can perform model inference. However, the generated binary file shares characteristics with ordinary executable files, meaning that important information within the binary file could potentially be leaked through disassembly. This paper leverages this critical characteristic by reverse-engineering the binary library files of the model to extract key parameters and thereby restore the model’s framework. Using model library files deployed on edge devices, combined with disassembly, model prediction, dynamic analysis, and other methods, this study successfully recovers the model’s operators, topology, and network hyperparameters. Experimental evaluations demonstrate that the framework of the model can be accurately reconstructed, and the substitute model trained using the original dataset achieves accuracy comparable to that of the original model. © 2024 Copyright held by the owner/author(s).

关键词： Contrastive Learning

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Probing the interlayer mechanical coupling of 2D layered materials-A review

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Progress in Natural Science:Materials International 2022年第5期32卷 528-537页

作者： Yinghui Sun Yufei Sun Rongming Wang Kai Liu Beijing Advanced Innovation Center for Materials Genome Engineering Beijing Key Laboratory for Magneto-Photoelectrical Composite and Interface Science School of Mathematics and Physics University of Science and Technology Beijing State Key Laboratory of New Ceramics and Fine Processing School of Materials Science and Engineering Tsinghua University Key Laboratory of Advanced Materials of Ministry of Education School of Materials Science and Engineering Tsinghua University

Two-dimensional(2D) layered materials are assembled through the intralayer covalent bonds and interlayer van der Waals(vdWs) interactions. The relatively weak interlayer vdWs interactions result in the weak interlayer mechanical coupling between layers, which strongly impacts the overall mechanical properties of multilayer 2D materials or heterostructures. Experimentally probing the interlayer mechanical coupling is of vital importance on the accumulation of fundamental parameters for their applications in flexible and stretchable devices, yet there are hardly comprehensive reviews in this research field. In this review, we firstly introduce the probing methods of interlayer mechanical coupling, including high-frequency and ultralow-frequency Raman characterizations,nanoindentation of multilayer 2D materials or heterostructures, surface indentation, pressurized blister test,characterization of spontaneously formed nanoblisters, and nano-friction tests. Based on the analysis and comparison of the existing methods and results, we also discuss the advantages and limitations of each ***, the challenges and opportunities in this promising field are discussed. This review summarizes the recent progress in the probing of interlayer mechanical coupling of 2D layered materials and will provide important reference for the rational design of flexible and stretchable devices.

关键词： van der Waals interaction Mechanical properties Indentation Heterostructures

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A survey of proactive defense in industrial control system

A survey of proactive defense in industrial control system

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2022 International Conference on Electronic Information Technology, EIT 2022

作者： Liu, Ke Wu, Qianqiong Geng, Yangyang Ma, Rongkuan Wei, Qiang State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China

ISBN: (纸本)9781510655096

With the development of Industrial 4.0, the popularity of information technology (IT) systems in industrial control systems (ICSs) has brought great cyber-attack risk. The proactive defense technology, an important defense approach, plays a vital role in ICSs. This paper introduces the definition, taxonomy and application of proactive defense in ICSs. We divide the existing ICS proactive defense approaches into three categories and summarize their technical characteristics. Finally, the application prospects and open issues of proactive defense in ICS are summarized. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Cybersecurity

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Research on Cascading Failures of Power Grid

Research on Cascading Failures of Power Grid

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2021 International Conference on Applied mathematics, Modeling and Computer Simulation, AMMCS 2021

作者： Wang, Hongmin Wei, Qiang Xie, Yaobin State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China

ISBN: (纸本)9781643682549

The safe and stable operation of power system is related to the national economy and people's livelihood of the whole country. Blackouts are almost always caused by cascading failures. This paper first analyzes the global blackouts in the past 20 years, and points out that the scale and probability distribution of blackouts obey the power-law relationship. Secondly, it is concluded that transmission line fault, bus fault, large-scale power flow transfer and relay protection device misoperation are the main factors causing cascading failures. Then, the five stages of cascading failure evolution are analyzed, which are slow successive interruption process, fast successive interruption process, transient oscillation, avalanche blackout and long recovery. Finally, the research results of cascading failure at home and abroad in recent years are analyzed from three research points: small world network, topological network and two-layer coupling network. © 2022 The authors and IOS Press.

关键词： Cyber Physical System

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