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检索条件"机构=Hubei Key Laboratory of Distributed System Security"

共 321 条记录，以下是191-200 订阅

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Effective Concurrency Testing for Go via Directional Primitive-Constrained Interleaving Exploration

Effective Concurrency Testing for Go via Directional Primiti...

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IEEE International Conference on Automated Software Engineering (ASE)

作者： Zongze Jiang Ming Wen Yixin Yang Chao Peng Ping Yang Hai Jin School of Cyber Science and Engineering Huazhong University of Science and Technology China Hubei Key Laboratory of Distributed System Security Services Computing Technology and System Lab Cluster and Grid Computing Lab Hubei Engineering Research Center on Big Data Security National Engineering Research Center for Big Data Technology and System ByteDance Beijing China School of Computer Science and Technology Huazhong University of Science and Technology China

The Go language (Go/Golang) has been attracting increasing attention from the industry over recent years due to its strong concurrency support and ease of deployment. This programming language encourages developers to use channel-based concurrency, which simplifies the development of concurrent programs. Unfortunately, it also introduces new concurrency problems that differ from those caused by the mechanism of shared memory concurrency. However, there are only few works that aim to detect such Go-specific concurrency issues. Even state-of-the-art testing tools will miss critical concurrent bugs that require fine-grained and effective interleaving exploration. This paper presents GoPie, a novel testing approach for detecting Go concurrency bugs through primitive-constrained interleaving exploration. GoPie utilizes execution histories to identify new interleavings instead of relying on exhaustive exploration or random scheduling. To evaluate its performance, we applied GoPie to existing benchmarks and large-scale open-source projects. Results show that GoPie can effectively explore concurrent interleavings and detect significantly more bugs in the benchmark. Furthermore, it uncovered 11 unique previously unknown concurrent bugs, and 9 of which have been confirmed.

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An Intelligent Recognition Algorithm for Urban Utility Tunnel Surface Intrusion via Spatio-temporal-spectral Joint Information Extraction with FPN Network

An Intelligent Recognition Algorithm for Urban Utility Tunne...

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Asia Communications and Photonics Conference and Exhibition (ACP)

作者： Tao He Zhijun Yan Shixiong Zhang Deming Liu Hao Li Qizhen Sun Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan P. R. China School of Optical and Electronic Information Huazhong University of Science and Technology Wuhan P. R. China

An intelligent recognition algorithm for utility tunnel surface intrusion based on spatio-temporal-spectral joint information extraction with FPN network is proposed. Finally, the average recognition accuracy of 93.8%... 详细信息

关键词： Target recognition Neural networks Asia Information retrieval Feature extraction Safety Monitoring

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AOCC-FL: Federated Learning with Aligned Overlapping via Calibrated Compensation

AOCC-FL: Federated Learning with Aligned Overlapping via Cal...

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IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： Haozhao Wang Wenchao Xu Yunfeng Fan Ruixuan Li Pan Zhou School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China Department of Computing The Hong Kong Polytechnic University Hong Kong Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China

Federated Learning enables collaboratively model training among a number of distributed devices with the coordination of a centralized server, where each device alternatively performs local gradient computation and communication to the server. FL suffers from significant performance degradation due to the excessive communication delay between the server and devices, especially when the network bandwidth of these devices is limited, which is common in edge environments. Existing methods overlap the gradient computation and communication to hide the communication latency to accelerate the FL training. However, the overlapping can also lead to an inevitable gap between the local model in each device and the global model in the server that seriously restricts the convergence rate of learning process. To address this problem, we propose a new overlapping method for FL, AOCC-FL, which aligns the local model with the global model via calibrated compensation such that the communication delay can be hidden without deteriorating the convergence performance. Theoretically, we prove that AOCC-FL admits the same convergence rate as the non-overlapping method. On both simulated and testbed experiments, we show that AOCC-FL achieves a comparable convergence rate relative to the non-overlapping method while outperforming the state-of-the-art overlapping methods.

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Threshold Signature Scheme Based on Non-internative Diffie-Hellman Signature

Threshold Signature Scheme Based on Non-internative Diffie-H...

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International Conference on Networking and distributed Computing (ICNDC)

作者： Xiuqun Wang Lican Huang Key Laboratory of Information System Security Ministry of Education Tsinghua University Beijing China Institute of Network and Distributed Computing Zhejiang Science and Technology University Hangzhou China

We present a threshold signature based on non-internative Diffie-Hellman signature. It works in asynchronous communication system and can tolerate Byzantine faults with optimal resilience n ≥ = 3t + 1, where n is the number of the participants and t is the number of the fault participants. The security of this scheme bases on discrete logarithm intractability assumption. We give the security analysis of our proposed threshold signature scheme.

关键词： Polynomials Protocols Public key Interpolation Robustness

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A Novel Path Planning Algorithm for Multi-Agent Collaboration in Finite Space

A Novel Path Planning Algorithm for Multi-Agent Collaboratio...

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IEEE International Conference on Communication and Information systems (ICCIS)

作者： Yihan Xu Tian Cao Xiaotong Shi Manchester Metropolitan Joint Institute Hubei University Wuhan China Ministry of Education Key Laboratory of Intelligent Sensing System and Security (Hubei University) School of Artificial Intelligence HuBei University Wuhan China

ISBN: (数字)9798331531171

ISBN: (纸本)9798331531188

Multi-agent collaboration can complete tasks that are difficult for a single agent to handle, making a big difference on the battlefield, in healthcare, and in other domains. Effective path planning is an important factor in ensuring task execution. However, the finite space increases the probability of multi-agent collisions, which poses a challenge to multi-agent path planning. To this end, we propose a novel path planning algorithm by two-module fusion (PLA-TMF). Specifically, the first module is to develop a collision detection model based on discrete point intersection probabilities, which improves the collision detection accuracy between different agents. Then, the second module is to realize the path planning algorithm under the minimum collision probability constraint, which relies on genetic algorithm. Finally, the effectiveness of the proposed algorithm is verified by simulation experiments under specific scenarios.

关键词： Accuracy Collaboration Medical services Path planning Planning Collision avoidance Information systems Genetic algorithms

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High recovery with fewer injections: practical binary volumetric injection attacks against dynamic searchable encryption 23

High recovery with fewer injections: practical binary volume...

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Proceedings of the 32nd USENIX Conference on security Symposium

作者： Xianglong Zhang Wei Wang Peng Xu Laurence T. Yang Kaitai Liang Huazhong University of Science and Technology Huazhong University of Science and Technology and Hubei Key Laboratory of Distributed System Security School of Cyber Science and Engineering Huazhong University of Science and Technology and St. Francis Xavier University Delft University of Technology

ISBN: (纸本)9781939133373

Searchable symmetric encryption enables private queries over an encrypted database, but it can also result in information leakages. Adversaries can exploit these leakages to launch injection attacks (Zhang et al., USENIX security'16) to recover the underlying keywords from queries. The performance of the existing injection attacks is strongly dependent on the amount of leaked information or injection. In this work, we propose two new injection attacks, namely BVA and BVMA, by leveraging a binary volumetric approach. We enable adversaries to inject fewer files than the existing volumetric attacks by using the known keywords and reveal the queries by observing the volume of the query results. Our attacks can thwart well-studied defenses (e.g., threshold countermeasure, padding) without exploiting the distribution of target queries and client databases. We evaluate the proposed attacks empirically in real-world datasets with practical queries. The results show that our attacks can obtain a high recovery rate (> 80%) in the best-case scenario and a roughly 60% recovery even under a large-scale dataset with a small number of injections (< 20 files).

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SYNERGISTIC CONTROL-BASED CONTROL STRATEGY FOR OPTIMIZING THE COORDINATED INERTIA SUPPORT OF WIND FARMS TO THE RECEIVING GRID VIA VSC-HVDC 12

SYNERGISTIC CONTROL-BASED CONTROL STRATEGY FOR OPTIMIZING TH...

引用

12th International Conference on Renewable Power Generation, RPG 2023

作者： Tan, Junmi Peng, Xiaotao Wang, Xiaoli Li, Xutao Yang, Jun Hubei Key Laboratory of Power Equipment & System Security for Integrated Energy School of Electrical Engineering and Automation Wuhan University Wuhan430073 China School of Electrical Engineering and Automation Wuhan University Wuhan430072 China State Grid Ningxia Electric Power Research Institute Yinchuan750001 China

In order to solve the problem of inertia reduction of the receiving power grid caused by feeding new energy source, an inertia coordination control optimization strategy for wind farm via VSC-HVDC based on cooperative control is proposed. Firstly, this paper analyzes the feasibility of coupling the voltage regulation of DC transmission line with the variation of wind farm frequency, which makes the wind farm sensing the frequency disturbance in the receiving power grid without communication. Based on synergetic control theory, a synergetic control law for the frequency-DC voltage droop coefficient of GSVSC is designed, enabling the DC capacitance to respond to the frequency change rate and quickly provide inertia support at the beginning stage of the disturbance. Further, the synergetic control law for wind farm variable proportional coefficient is also designed to make the inertia provided by the rotor kinetic energy of wind turbines in this strategy synergistically respond to frequency change and the voltage change of DC transmission line, which optimizes the inertia response and helps restore the rotor speed. Finally, the effectiveness of the proposed adaptive coefficient control strategy is verified by comparing with the fixed coefficient control strategy. © The Institution of Engineering & Technology 2023.

关键词： Kinetics

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Impedance Reconstruction Based Damping Control Strategy for Variable Speed Pumped Storage Unit 26

Impedance Reconstruction Based Damping Control Strategy for ...

引用

26th International Conference on Electrical Machines and systems, ICEMS 2023

作者： Chuang, Kaihsun Jin, Yifang Zhang, Yuanzhi Hu, Renzhi Luan, Yihang Sun, Jianjun Wuhan University School of Electrical Engineering and Automation Hubei Key Laboratory of Power Equipment and System Security for Integrated Energy Wuhan China State Grid Liaoning Electric Power Supply Co. State Grid Liaoning Electric Power Supply Co. Ltd Liaoning Liaoning China

ISBN: (纸本)9798350317589

The complicated interactions between multi-time scale control loops of grid side converter (GSC) and machine-side converter (MSC) inevitably caused system instability under weak-grid conditions. The main reasons for causing the VSPS system instability are the numerous control loop and the overlap of their control bandwidths. Unlike a single grid-connected converter, the power transmission process and the impedance characteristic are not as easy to describe. For this reason, the overall impedance model, including hydro turbine, synchronous machine, GSC, and MSC, is built in this paper. The accuracy is verified by simulation, and the influences of parameters are further discussed. Besides, an impedance reconstruction based damping control strategy for VSPS unit is proposed. The strategy reshapes the damping characteristic by applying two auxiliary control loops, which eliminates the resonance oscillation and stabilizes the system. Simulation results show that the proposed damping control strategy is feasible under both weak and extremely weak grid conditions. © 2023 IEEE.

关键词： Electric power transmission

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Machine Learning is All You Need: A Simple Token-Based Approach for Effective Code Clone Detection

Machine Learning is All You Need: A Simple Token-Based Appro...

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International Conference on Software Engineering (ICSE)

作者： Siyue Feng Wenqi Suo Yueming Wu Deqing Zou Yang Liu Hai Jin Huazhong University of Science and Technology China National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security Cluster and Grid Computing Lab Jinyinhu Laboratory Wuhan China School of Cyber Science and Engineering HUST Wuhan China Nanyang Technological University Singapore School of Computer Science and Technology HUST Wuhan China

ISBN: (数字)9798400702174

ISBN: (纸本)9798350382143

As software engineering advances and the code demand rises, the prevalence of code clones has increased. This phenomenon poses risks like vulnerability propagation, underscoring the growing importance of code clone detection techniques. While numerous code clone detection methods have been proposed, they often fall short in real-world code environments. They either struggle to identify code clones effectively or demand substantial time and computational resources to handle complex clones. This paper introduces a code clone detection method namely Toma using tokens and machine learning. Specifically, we extract token type sequences and employ six similarity calculation methods to generate feature vectors. These vectors are then input into a trained machine learning model for classification. To evaluate the effectiveness and scalability of Toma, we conduct experiments on the widely used BigCloneBench dataset. Results show that our tool outperforms token-based code clone detectors and most tree-based clone detectors, demonstrating high effectiveness and significant time savings.

关键词： Codes Scalability Computational modeling Cloning Machine learning Detectors Feature extraction

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Towards Effective and Efficient Error Handling Code Fuzzing Based on Software Fault Injection

Towards Effective and Efficient Error Handling Code Fuzzing ...

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IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)

作者： Kang Chen Ming Wen Haoxiang Jia Rongxin Wu Hai Jin School of Cyber Science and Engineering Huazhong University of Science and Technology (HRUST) Wuhan China National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Engineering Research Center on Big Data Security Hubei Key Laboratory of Distributed System Security Jin YinHu Laboratory Wuhan China School of Informatics Xiamen University Xiamen China School of Computer Science and Technology HUST Wuhan China Cluster and Grid Computing Lab

ISBN: (数字)9798350330663

ISBN: (纸本)9798350330670

Software systems often encounter various errors or exceptions in practice, and thus proper error handling code is essential to ensure the reliability of software systems. Unfortunately, error handling code is often bug-prone, while sufficiently testing them is challenging as such code often cannot be triggered under normal conditions. Motivated by this, recent studies have proposed to leverage software fault injection (SFI) based fuzzing to discover potential bugs in complicated error handling code. Despite the promising results achieved, their effectiveness and efficiency are still compromised in practice due to the huge search space of error sites, inadequate fuzzing guidance, and the overhead induced by context-sensitive SFI. To achieve effective and efficient testing of error handling code, this study presents AFL-FI, which first utilizes a similarity-based method to identify suspicious error sites, and then incorporates the idea of error site coverage to guide the fuzzing process. Finally, the design of lightweight context-sensitive SFI enables AFL-FI to execute test cases efficiently. We evaluate AFL-FI on eight large-scale open-source projects, and the results show that it can outperform existing state-of-the-art fuzzing tools significantly in terms of branch code coverage. More importantly, AFL-FI has discovered 13 previously unknown bugs, and all of them have been confirmed while 12 of them have been fixed. Besides, our evaluation also demonstrates that all the key designs of AFL- F I are effective that contribute significantly to its overall performance.

关键词： Codes Computer bugs Fuzzing Software systems Software reliability Testing

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