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Towards Comprehensively Understanding the Run-time Security of Programmable Logic controllers: A 3-year Empirical Study

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arXiv 2022年

作者： Ma, Rongkuan Wei, Qiang Wang, Jingyi Zhu, Shunkai Ji, Shouling Cheng, Peng Jia, Yan Wang, Qingxian State Key Laboratory of Mathematical Engineering and Advanced Computing Henan Zhengzhou450001 China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310000 China College of Cyber Science Nankai University Tianjin China

Programmable Logic controllers (PLCs) are the core control devices in Industrial control Systems (ICSs), which control and monitor the underlying physical plants such as power grids. PLCs were initially designed to work in a trusted industrial network, which however can be brittle once deployed in an Internet-facing (or penetrated) network. Yet, there is a lack of systematic empirical analysis of the run-time security of modern real-world PLCs. To close this gap, we present the first large-scale measurement on 23 off-the-shelf PLCs across 13 leading vendors. We find many common security issues and unexplored implications that should be more carefully addressed in the design and implementation. To sum up, the unsupervised logic applications can cause system resource/privilege abuse, which gives adversaries new means to hijack the control flow of a runtime system remotely (without exploiting memory vulnerabilities);2) the improper access control mechanisms bring many unauthorized access implications;3) the proprietary or semi-proprietary protocols are fragile regarding confidentiality and integrity protection of run-time data. We empirically evaluated the corresponding attack vectors on multiple PLCs, which demonstrates that the security implications are severe and broad. Our findings were reported to the related parties responsibly, and 20 bugs have been confirmed with 7 assigned CVEs. Copyright © 2022, The Authors. All rights reserved.

关键词： Programmable logic controllers

Biosignal-Based Attention Monitoring for Evaluating Train Driver Safety-Relevant Tasks

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SSRN

SSRN 2024年

作者： Kim, Jung Hwan Kim, Yeongjun Cho, Younggeol Kim, Tae Kyun Jang, Tongil Park, Chanwoo Kang, Seongkeun Advanced Instrumentation & Control Research Section Korea Atomic Energy Research Institute Daejeon Korea Republic of Department of Nuclear & Quantum Engineering Korea Advanced Institute of Science and Technology Daejeon Korea Republic of School of Computing Korea Advanced Institute of Science and Technology Daejeon Korea Republic of Department of Railroad Electrical & Electronic Engineering Korea National University of Transportation Uiwang Korea Republic of System Safety Research Department Korea Railroad Research Institute Uiwang Korea Republic of

This study explores the impact of phone usage on train driver performance, a critical aspect influencing the safety of railroad operations. The persistent problem of phone distractions, which severely impair situational awareness and contribute to accidents, necessitates innovative solutions to enhance operational safety. Leveraging advancements in technology, this study introduces a novel approach combining electroencephalogram (EEG)-based analysis with deep learning algorithms to assess the effects of phone usage on the attention states of train drivers. Utilizing a full-type train simulator to replicate real-life scenarios, this study conducts an experimental design involving scenarios with and without phone engagement, aiming to provide a comprehensive assessment of phone usage on performance in critical situations. The deep learning model employed achieved an impressive classification accuracy of approximately 85.6% in distinguishing attention states among 25 participants, with high precision and recall values indicating its efficacy in detecting phone interaction. Moreover, findings reveal that phone usage leads to a 1.4 times increase in response time to situational awareness, significantly affecting driver performance. These findings highlight the significant impact of phone usage on train driver attention and underscore the potential of EEG-based analysis and deep learning in improving railroad safety measures. This study contributes to the growing body of safety literature by focusing on train drivers, offering fresh insights and practical implications for enhancing the safety and efficiency of railroad operations. © 2024, The Authors. All rights reserved.

关键词： Railroads

A Mobile Ar End-to-End Integrated Registration Method for Intelligent Assisted Assembly of Rail Transit Equipment

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SSRN

SSRN 2024年

作者： Yong, Jiu Wei, Jianguo Lei, Xiaomei Wang, Yangping Dang, Jianwu Lu, Wenhuan College of Intelligence and Computing Tianjin University Tianjin300072 China The National Virtual Simulation Experiment Teaching Center of Railway Traffic Information and Control Lanzhou Jiaotong Univeristy Lanzhou730070 China The School of Electronic and Information Engineering Lanzhou Jiaotong Univeristy Lanzhou730070 China Meteorological Information and Technological Supporting Center Gansu Province Meteorological Bureau Lanzhou730020 China

To improve the efficiency of rail transit equipment assembly operations, augmented reality (AR) technology is used to integrate rich virtual auxiliary guidance information into the assembly process, establish a virtual-real fusion rail transit assembly operation environment, and strengthen the perception and understanding ability of assembly business personnel to their assembly environments. In this paper, an AR end-to-end integration registration network (AR-EIRNet) is proposed for mobile AR intelligent assisted assembly of rail transit equipment. This network includes three main stages: feature extraction, pose estimation, and registration parameter solving. In the feature extraction stage, multiscale features are extracted based on a feature attention mechanism and local contextual information. In the pose estimation stage, the pose of the assembly object is directly inferred based on the aggregation of multiscale features and global features, and the pose is calibrated using a differentiable renderer. The registration parameter solving stage calculates the AR registration alignment matrix integrate virtual information overlay rendering. In addition, AR-EIRNet utilizes RGB image synthesis enhancement strategies to increase data diversity and enhance the learning of AR assembly objects. Finally, assembly application and utility analyses are conducted on the ZD6 switch machine equipment in rail transit. The results indicate that the registration error of the AR assembly is within 5 mm, and AR-EIRNet has strong stability and robustness, which can effectively improve the assembly operation efficiency. © 2024, The Authors. All rights reserved.

关键词： Augmented reality

Reinforcement Learning Algorithms for Online Single-Machine Scheduling 15

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Reinforcement Learning Algorithms for Online Single-Machine ...

15th Federated Conference on Computer Science and Information Systems, FedCSIS 2020

作者： Li, Yuanyuan Fadda, Edoardo Manerba, Daniele Tadei, Roberto Terzo, Olivier Links Foundation-Advanced Computing and Applications Torino10138 Italy Politecnico di Torino Department of Control and Computer Engineering Torino10129 Italy University of Brescia Department of Information Engineering Brescia25123 Italy

ISBN: (纸本)9788395541674

Online scheduling has been an attractive field of research for over three decades. Some recent developments suggest that Reinforcement Learning (RL) techniques have the potential to deal with online scheduling issues effectively. Driven by an industrial application, in this paper we apply four of the most important RL techniques, namely Q-learning, Sarsa, Watkins's Q(lambda), and Sarsa(lambda), to the online single-machine scheduling problem. Our main goal is to provide insights on how such techniques perform. The numerical results show that Watkins's Q(lambda) performs best in minimizing the total tardiness of the scheduling process. © 2020 Polish Information Processing Society - as it is since 2011.

关键词： Reinforcement learning

Diff9D: Diffusion-Based Domain-Generalized Category-Level 9-DoF Object Pose Estimation

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arXiv 2025年

作者： Liu, Jian Sun, Wei Yang, Hui Deng, Pengchao Liu, Chongpei Sebe, Nicu Rahmani, Hossein Mian, Ajmal National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering School of Robotics State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha410082 China Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an710049 China Department of Information Engineering and Computer Science University of Trento Trento38123 Italy School of Computing and Communications Lancaster University LA1 4YW United Kingdom Department of Computer Science The University of Western Australia WA6009 Australia

Nine-degrees-of-freedom (9-DoF) object pose and size estimation is crucial for enabling augmented reality and robotic manipulation. Category-level methods have received extensive research attention due to their potential for generalization to intra-class unknown objects. However, these methods require manual collection and labeling of large-scale real-world training data. To address this problem, we introduce a diffusion-based paradigm for domain-generalized category-level 9-DoF object pose estimation. Our motivation is to leverage the latent generalization ability of the diffusion model to address the domain generalization challenge in object pose estimation. This entails training the model exclusively on rendered synthetic data to achieve generalization to real-world scenes. We propose an effective diffusion model to redefine 9-DoF object pose estimation from a generative perspective. Our model does not require any 3D shape priors during training or inference. By employing the Denoising Diffusion Implicit Model, we demonstrate that the reverse diffusion process can be executed in as few as 3 steps, achieving near real-time performance. Finally, we design a robotic grasping system comprising both hardware and software components. Through comprehensive experiments on two benchmark datasets and the real-world robotic system, we show that our method achieves state-of-the-art domain generalization performance. Our code will be made public at https://***/CNJianLiu/Diff9D. Copyright © 2025, The Authors. All rights reserved.

关键词： Augmented reality

Full life-cycle cost model for practical application of solar energy system

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Energy Informatics 2025年第1期8卷

作者： Sha, Ang Xiong, Zhen Zang, Xiaolin Zhao, Wei Ge, Ruibang Yao, Wanxiang Aiello, Marco Innovation Institute for Sustainable Maritime Architecture Research and Technology Qingdao University of Technology Qingdao266033 China School of Architecture and Urban Planning Qingdao University of Technology Qingdao266033 China School of Information and Control Engineering Qingdao University of Technology Qingdao266520 China School of Continuing Education Qingdao University of Technology Qingdao266033 China Service Computing Department Institute of Architecture of Application Systems University of Stuttgart Universitätsstraße 38 Stuttgart70569 Germany

In pursuit of carbon neutrality, a swift transformation is underway in the global energy structure, marked by a consistent rise in the installed capacity of solar energy systems. Meanwhile, the substantial reduction of government subsidies in the solar industry intensifies focus on the economic viability of solar energy installations. In this study, we propose a full life-cycle cost model, named the F-LCC model, for calculating the cost of the solar energy system on the long term, e.g., 20–30 years. This model integrates replacement costs, residual value calculation, interest rate, and inflation impacts while supporting market price estimation for individual components, thereby aiding feasibility analysis in the early project phase. We design an investment cost recovery algorithm based on the F-LCC model to calculate the break-even electricity price for solar energy system. Moreover, we analyze component cost distributions, Net Present Value (NPV), and Discounted Payback Period (DPP) for grid-connected and off-grid solar energy systems with capacities of 10 kWp and 100 kWp in the Chinese market. The results show that the proposed model, compared to other models, captures the fact that payback times are longer. In a solar energy system without storage, solar panels have the highest component cost share at 28.8%. With battery storage, batteries dominate the total cost, reaching up to 74.6%. And the the grid-connected systems DPP ranging from a minimum of 5.5 to a maximum of 7.0 years by grid-connected electricity price, while off-grid systems require at least 19.9 years. The 10 kWp off-grid fixed mounting system’s break-even price being 137.1% higher than its grid-connected counterpart. In addition, tracking-mount systems offer greater cost-reduction potential than fixed installations, with the payback period reduced by 20% for 100 kWp grid-connected systems and 15% for off-grid systems. Finally, we develop a plugin based on the F-LCC model. These findings deepen unde

关键词： Commerce

A Human-friendly Verbal Communication Platform for Multi-Robot Systems: Design and Principles

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arXiv 2022年

作者： Carr, Christopher Wang, Peng Wang, Shenglin The Department of Mathematics and Computing Manchester Metropolitan University M15 6BH United Kingdom The Department of Automatic Control and Systems Engineering The University of Sheffield SheffieldS10 2TN United Kingdom

While multi-robot systems have been broadly researched and deployed, their success is built chiefly upon the dependency on network infrastructures, whether wired or wireless. Aiming at the first steps toward de-coupling the application of multi-robot systems from the reliance on network infrastructures, this paper proposes a human-friendly verbal communication platform for multi-robot systems, following the deliberately designed principles of being adaptable, transparent, and secure. The platform is network independent and is subsequently capable of functioning in network infrastructure lacking environments from underwater to planet explorations. A series of experiments were conducted to demonstrate the platform’s capability in multi-robot systems communication and task coordination, showing its potential in infrastructure-free applications. To benefit the community, we have made the codes open source at GitHub. Copyright © 2022, The Authors. All rights reserved.

关键词： Multipurpose robots

SEMI-SUPERVISED MEDICAL IMAGE SEGMENTATION WITH CO-DISTRIBUTION ALIGNMENT

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arXiv 2023年

作者： Wang, Tao Huang, Zhongzheng Wu, Jiawei Cai, Yuanzheng Li, Zuoyong Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University China College of Computer and Data Science Fuzhou University China The Key Laboratory of Cognitive Computing and Intelligent Information Processing of Fujian Education Institutions Wuyi University China School of Electrical and Mechanical Engineering Fujian Agriculture and Forestry University China

Medical image segmentation has made significant progress when a large amount of labeled data are available. However, annotating medical image segmentation datasets is expensive due to the requirement of professional skills. Additionally, classes are often unevenly distributed in medical images, which severely affects the classification performance on minority classes. To address these problems, this paper proposes Co-Distribution Alignment (Co-DA) for semi-supervised medical image segmentation. Specifically, Co-DA aligns marginal predictions on unlabeled data to marginal predictions on labeled data in a class-wise manner with two differently initialized models before using the pseudo-labels generated by one model to supervise the other. Besides, we design an over-expectation cross-entropy loss for filtering the unlabeled pixels to reduce noise in their pseudo-labels. Quantitative and qualitative experiments on three public datasets demonstrate that the proposed approach outperforms existing state-of-the-art semi-supervised medical image segmentation methods on both the 2D CaDIS dataset and the 3D LGE-MRI and ACDC datasets, achieving an mIoU of 0.8515 with only 24% labeled data on CaDIS, and a Dice score of 0.8824 and 0.8773 with only 20% data on LGE-MRI and ACDC, respectively. Copyright © 2023, The Authors. All rights reserved.

关键词： Alignment

Design and development of multiple protocols supported embedded gateway for industrial networked electrical metering systems 16

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Design and development of multiple protocols supported embed...

16th International Conference on Electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2019

作者： Charukwongsawat, Siripong Nuratch, Santi Boonpramuk, Panuthat Faculty of Engineering KMUTT Embedded Computing and Control Laboratory Thailand

ISBN: (纸本)9781728133614

This paper presents the design and development of multiple protocols supported gateway for industrial networked electrical metering systems. There are two main parts proposed in this paper. Firstly, the flexible hardware design and development of smart meter that allow users to customize the communication protocols. Secondly, the firmware design and implementation techniques for the multiple protocols supported gateway. The smart meters used in this research are divided into three groups. The first group uses WebSockets as communication protocol. The second group utilizes MQTT protocol. The third group uses Modbus serial and Modbus TCP. All meters can measure all required electrical parameters, e.g., voltage, current, watt-hour, power factor and many other. The gateway can handle all required protocols and it can perform all communication channels concurrently. In addition, a plug-and-play algorithm is also mentioned. The firmware of the meters and the gateway are implemented based on Free-RTOS with C language to maintain speed and system performance. All communication protocols of the smart meters and gateway are implemented follow industrial standards. Therefore, the gateway and all groups of meters can be deployed to all standard industrial networks. In experiments, the gateway is connected to the internet to serve external requests from clients. The meters and gateway are evaluated in various possible conditions. The experimental results show that the meters can measure the desired electrical parameters and exchange their data correctly as expected. The gateway can perform all protocols and can respond to all incoming requests from clients concurrently and correctly. © 2019 IEEE.

关键词： Internet of things