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A survey on membership inference attacks and defenses in machine learning

Journal of Information and Intelligence 2024年第5期2卷 404-454页

作者： Jun Niu Peng Liu Xiaoyan Zhu Kuo Shen Yuecong Wang Haotian Chi Yulong Shen Xiaohong Jiang Jianfeng Ma Yuqing Zhang School of Computer Science and Technology Xidian UniversityXi'an 710071China Information Sciences and Technology Pennsylvania State UniversityPA 16802United States School of Telecommunications Engineering Xidian UniversityXian 710071China School of Hangzhou Institute of Technology Xidian UniversityHangzhou 311231China School of Automation and Software Engineering Shanxi UniversityTaiyuan 030006China School of Systems Information Science Future University of HakodateHakodate 041-8655Japan School of Computer&Control Engineering University of Chinese Academy of SciencesBeijing 101408China School of Cyber Engineering Xidian UniversityXian 710071China

Membership inference(MI)attacks mainly aim to infer whether a data record was used to train a target model or *** to the serious privacy risks,MI attacks have been attracting a tremendous amount of attention in the research *** existing work conducted-to our best knowledge the first dedicated survey study in this specific area:The survey provides a comprehensive review of the literature during the period of 2017~2021(e.g.,over 100 papers).However,due to the tremendous amount of progress(i.e.,176 papers)made in this area since 2021,the survey conducted by the one existing work has unfortunately already become very limited in the following two aspects:(1)Although the entire literature from 2017~2021 covers 18 ways to categorize(all the proposed)MI attacks,the literature during the period of 2017~2021,which was reviewed in the one existing work,only covered 5 ways to categorize MI *** 13 ways missing,the survey conducted by the one existing work only covers 27%of the landscape(in terms of how to categorize MI attacks)if a retrospective view is taken.(2)Since the literature during the period of 2017~2021 only covers 27%of the landscape(in terms of how to categorize),the number of new insights(i.e.,why an MI attack could succeed)behind all the proposed MI attacks has been significantly increasing since year *** a result,although none of the previous work has made the insights as a main focus of their studies,we found that the various insights leveraged in the literature can be broken down into 10 *** making the insights as a main focus,a survey study could fail to help researchers gain adequate intellectual depth in this area of *** this work,we conduct a systematic study to address these *** particular,in order to address the first limitation,we make the 13 newly emerged ways to categorize MI attacks as a main focus on the *** order to address the second limitation,we provide-to our best knowledge-the first r

关键词： Machine learning Privacy and security Membership inference attacks Defensive techniques

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Distributed Constrained Online Nonconvex Optimization with Compressed Communication

arXiv

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arXiv 2025年

作者： Zhang, Kunpeng Xu, Lei Yi, Xinlei Cao, Ming Johansson, Karl H. Chai, Tianyou Yang, Tao State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Department of Mechanical Engineering University of Victoria VictoriaBCV8W 2Y2 Canada Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai201210 China Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen GroningenAG 9747 Netherlands Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures Stockholm10044 Sweden

This paper considers distributed online nonconvex optimization with time-varying inequality constraints over a network of agents. For a time-varying graph, we propose a distributed online primal–dual algorithm with compressed communication to efficiently utilize communication resources. We show that the proposed algorithm establishes an O(T max{1−θ1,θ1}) network regret bound and an O(T 1−θ1/2) network cumulative constraint violation bound, where T is the number of iterations and θ1 ∈ (0, 1) is a user-defined trade-off parameter. When Slater’s condition holds (i.e, there is a point that strictly satisfies the inequality constraints at all iterations), the network cumulative constraint violation bound is reduced to O(T 1−θ1). These bounds are comparable to the state-of-the-art results established by existing distributed online algorithms with perfect communication for distributed online convex optimization with (time-varying) inequality constraints. Finally, a simulation example is presented to validate the theoretical results. Copyright © 2025, The Authors. All rights reserved.

关键词： Convex optimization

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Evaluating contextualized language models for Hungarian

arXiv

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arXiv 2021年

作者： Ács, Judit Lévai, Dániel Nemeskey, Dávid Márk Kornai, András Department of Automation and Applied Informatics Budapest University of Technology and Economics Hungary Institute for Computer Science and Control Hungary Alfréd Rényi Institute of Mathematics Hungary

We present an extended comparison of contextualized language models for Hungarian. We compare huBERT, a Hungarian model against 4 multilingual models including the multilingual BERT model. We evaluate these models through three tasks, morphological probing, POS tagging and NER. We find that huBERT works better than the other models, often by a large margin, particularly near the global optimum (typically at the middle layers). We also find that huBERT tends to generate fewer subwords for one word and that using the last subword for token-level tasks is generally a better choice than using the first one. Copyright © 2021, The Authors. All rights reserved.

关键词： Computational linguistics

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Application of Deep Learning Method to Estimate Bottomhole Pressure Dynamics of Oil Wells

Application of Deep Learning Method to Estimate Bottomhole P...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Haibo Cheng Shichao Li Peng Zeng Valeriy Vyatkin State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Department of Computer Science Electrical and Space Engineering Luleå University of Technology Luleå Sweden Department of Electrical Engineering and Automation Aalto University Helsinki Finland

Surrogate models, which have become an effective and popular method to close loop reservoir management problems, use a data-driven approach to predict dynamic injection and production wells parameters and optimize waterflooding development. In this study, a deep learning-based surrogate model method is proposed to estimate bottomhole pressure (BHP) of production wells in waterflooding reservoirs. Bidirectional long short-term memory (BiLSTM) network, as an efficient deep learning approach, is applied to BHP estimation using fluctuation data. Extended Fourier amplitude sensitivity test (EFAST) method is employed to analyse the influence of different input factors on BHP dynamics, and a reduced dataset is rebuilt to predict BHP parameter based on BiLSTM-EFAST algorithm. The estimation results are tested on a dataset from Volve oilfield in North Sea, and compared with other deep learning methods. The test results indicate that the proposed method can achieve higher prediction accuracy. A reduced dataset-based approach provides a new attempt to reduce model complexity and improve calculation speed for big data-driven surrogate model in oil and gas industry.

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An End-to-End Trajectory Planning Strategy for Free-floating Space Robots

An End-to-End Trajectory Planning Strategy for Free-floating...

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第40届中国控制会议

作者： Shengjie Wang Yuxue Cao Xiang Zheng Tao Zhang Department of Automation Tsinghua University Beijing Institute of Control Engineering China Academy of Space Technology Department of Computer Science City University of Hong Kong

The traditional trajectory planning methods of free-floating space robots have the dynamic singular problem and the difficulty of accurate *** learning-based approaches have achieved remarkable performance on such task,they mainly focus on single modular design such as the perception,planning,or control ***-based end-to-end method can well combine perception,planning and control,which not rely on parameters of the dynamic model and reduce the difficulty of manually adjusting modular controllers’ ***,we developed an end-to-end trajectory planning strategy based on optimization with multiple *** whole strategy consists of several multi-layer neural networks and is optimized by a deep reinforcement learning algorithm based on maximum *** results of visualization show that our strategy can capture the information of robotic arm from vision ***,we evaluate the kinematic and dynamic features of the system and testify our strategy in anti-interference *** performance of our strategy demonstrates the availability and robustness of the system.

关键词： Space robot Trajectory planning Reinforcement learning

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A Pricing Rule for Third-Party Platoon Coordination Service Provider

A Pricing Rule for Third-Party Platoon Coordination Service ...

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Asian control Conference

作者： Ting Bai Alexander Johansson Shaoyuan Li Karl Henrik Johansson Jonas Må rtensson Integrated Transport Research Lab Digital Futures and Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai China

We model a platooning system including trucks and a third-party service provider that performs platoon coordination, distributes the platooning profit within platoons, and charges the trucks in exchange for its services. This paper studies one class of pricing rules, where the third-party service provider keeps part of the platooning profit each time a platoon is formed. Furthermore, we propose a platoon coordination solution based on distributed model predictive control in which the pricing rule is integrated. To evaluate the effect of the pricing on the platooning system, we perform a simulation over the Swedish road network. The simulation shows that the platooning rate and profit highly depend on the pricing. This suggests that pricing needs to be set carefully to obtain a satisfactory platooning system in the future.

关键词： Roads Pricing Predictive control

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Formation control for mobile robot using fuzzy - PI controller

Formation control for mobile robot using fuzzy - PI controll...

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2020 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2020

作者： Lee, Min-Fan Ricky Willybrordus, H.P.M. Sukamto Hassen, Sharfiden Nugroho, Asep National Taiwan University of Science and Technology Taipei Taiwan National Taiwan University of Science and Technology Department of Electrical Engineering Taipei Taiwan National Taiwan University of Science and Technology Department of Computer Science and Information Engineering Taipei Taiwan National Taiwan University of Science and Technology College of Graduate Institute of Automation and Control Taipei Taiwan National Taiwan University of Science and Technology Graduate Institute of Automation and Control Taipei Taiwan

ISBN: (纸本)9781728198231

Protecting soldiers in the long march of platoon formation is crucial mission in the military operation. Autonomous ground mobile robots can be deployed to carry out such kind of the mission. The primary task is maintaining robot position automatically based on the movement of soldier in a platoon formation. The GPS is employed to determine the soldier current pose. This information is used as an input to create a dynamic convex hull around a platoon. The Proportional-Integral (PI) controller is applied to control each robot so it can move in a desired trajectory. The fuzzy logic control (FLC) is involved to tune the gain of PI controller to optimize the performance. Three protective robots and nine soldiers are used to evaluate the algorithm in simulation. The proposed algorithm will provide a platoon soldiers with optimal protection encirclement and enhance their safety. The simulation results show good performance using the proposed controller. © 2020 IEEE.

关键词： Mobile robots

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Modeling and fuzzy control of permanent magnet synchronous motors 10

Modeling and fuzzy control of permanent magnet synchronous m...

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10th International Conference on Power Electronics, Machines and Drives, PEMD 2020

作者： Juki, Domagoj-Kreimir Varga, Toni Beni, Tin Štil, Vedrana Jerkovi Baruki, Marinko Automation and Control Institute TU Wien Vienna Austria Faculty of Electrical Engineering Computer Science and Information Technology Osijek Josip Juraj Strossmayer University of Osijek Osijek Croatia

ISBN: (纸本)9781839535635

This paper deals with Permanent Magnet Synchronous Motor modeling and control. The derived nonlinear dq model is a combination of Finite Element Method simulation data with the classical dq model. The so derived model keeps the precision of the Finite Element Method simulations and also the fast execution times of the dq model. The Finite Element Method data is included in the dq model using Artificial Neural Networks. The derived model is also used for controller design. The chosen controller is a PI like Fuzzy Logic controller, which is tuned using Genetic Algorithm optimization. The Permanent Magnet Synchronous Motor with Fuzzy Logic controller operation is tested using Real-Time (Model-in-the-Loop) simulations. © PEMD *** right reserved.

关键词： Permanent magnets

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MG-SLAM: Structure Gaussian Splatting SLAM with Manhattan World Hypothesis

arXiv

引用

arXiv 2024年

作者： Liu, Shuhong Deng, Tianchen Zhou, Heng Li, Liuzhuozheng Wang, Hongyu Wang, Danwei Li, Mingrui Department of Information Science and Technology Department of Complexity Science and Engineering The University of Tokyo Tokyo113-8654 Japan Institute of Medical Robotics Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Department of Mechanical Engineering Columbia University New York10027 United States School of Electrical and Electronic Engineering Nanyang Technological University Singapore Department of Computer Science Dalian University of Technology Dalian116024 China

Gaussian Splatting SLAMs have made significant advancements in improving the efficiency and fidelity of real-time reconstructions. However, these systems often encounter incomplete reconstructions in complex indoor environments, characterized by substantial holes due to unobserved geometry caused by obstacles or limited view angles. To address this challenge, we present Manhattan Gaussian SLAM, an RGB-D system that leverages the Manhattan World hypothesis to enhance geometric accuracy and completeness. By seamlessly integrating fused line segments derived from structured scenes, our method ensures robust tracking in textureless indoor areas. Moreover, The extracted lines and planar surface assumption allow strategic interpolation of new Gaussians in regions of missing geometry, enabling efficient scene completion. Extensive experiments conducted on both synthetic and real-world scenes demonstrate that these advancements enable our method to achieve state-of-the-art performance, marking a substantial improvement in the capabilities of Gaussian SLAM systems. © 2024, CC BY.

关键词： Gaussian distribution

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Repetitive process based design of PD-type iterative learning control laws for batch processes with time-delays

引用

IFAC-PapersOnLine 2023年第2期56卷 1901-1906页

作者： Robert Maniarski Wojciech Paszke Eric Rogers Hongfeng Tao Institute of Automation Electronic and Electrical Engineering University of Zielona Góra ul. Szafrana 2 65-516 Zielona Góra Poland School of Electronics and Computer Science University of Southampton Southampton SO17 1BJ UK Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education Jiangnan University Wuxi 214122 P. R. China

This paper uses linear matrix inequality techniques and the Kalman-Yakubovich-Popov lemma to design an iterative learning control law for a class of batch processes with state delays. The design procedure is based on the stability theory for repetitive processes, a class of 2D systems. A numerical example illustrates the new design and demonstrates that the design has advantages compared to the existing alternatives.

关键词： Iterative learning control repetitive processes batch processes linear matrix inequalities systems with delays

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