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Enabling data-driven anomaly detection by design in cyber-physical production systems

Cybersecurity 2022年第3期5卷 34-51页

作者： Rui Pinto Gil Goncalves Jerker Delsing Eduardo Tovar Department of Informatics Engineering Faculty of EngineeringUniversity of PortoPortoPortugal EISLAB Lulea University of TechnologyLuleaSweden Research Centre in Real-Time and Embedded Computing Systems Polytechnic of Porto-School of EngineeringPortoPortugal

Designing and developing distributed cyber-physical production systems(CPPS)is a time-consuming,complex,and error-prone *** systems are typically heterogeneous,i.e.,they consist of multiple components implemented with different languages and development *** of the main problems nowadays in CPPS implementation is enabling security mechanisms by design while reducing the complexity and increasing the system’s *** the IEC 61499 standard is an excellent approach to tackle these challenges by enabling the design,deployment,and management of CPPS in a model-based engineering *** propose a method for CPPS design based on the IEC 61499 *** method allows designers to embed a bio-inspired anomaly-based host intrusion detection system(A-HIDS)in Edge *** A-HIDS is based on the incremental Dendritic Cell Algorithm(iDCA)and can analyze OPC UA network data exchanged between the Edge devices and detect attacks that target the CPPS’Edge *** study’s findings have practical implications on the industrial security community by making novel contributions to the intrusion detection problem in CPPS considering immune-inspired solutions,and cost-effective security by design system *** to the experimental data,the proposed solution can dramatically reduce design and code complexity while improving application maintainability and successfully detecting network attacks without negatively impacting the performance of the CPPS Edge devices.

关键词： Artificial immune systems Cyber-physical production systems IEC 61499 Function blocks Industrial Internet of Things Anomaly-based host intrusion detection system Model-based engineering

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Application of Bayes Rule for Precise Analysis of Class-Imbalanced Stroke Data

Application of Bayes Rule for Precise Analysis of Class-Imba...

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2023 International Conference on Innovative computing, Intelligent Communication and Smart Electrical systems, ICSES 2023

作者： Viswapriya, S.E. Rajeswari, D. SRM Institute of Science and Technology School of Computing College of Engineering and Technology Department of Data Science and Business Systems Kattankulathur Chennai India

ISBN: (纸本)9798350319200

The interpretability of stroke risk prediction is still lagging and it can be solved by using deep analysisofdata with the application of the Bayes rule. The prediction model has to be produced with accuracy, clarity, and comprehensibility without ambiguity, especially in machine learning and data analytics. The class imbalance problem is a common issue affecting the raw data, which means the imbalanced categorization of outcome feature value. In many fields, such as fraud detection, network intrusion detection, and medical diagnostics, this class imbalance issue is present where negative class samples outnumber positive class samples. If some datasets have class imbalance and imperfect issues, there will be no proper classification pattern. There are many resampling methods to address this class imbalance problem. However, these resampling methods can make an even distribution of classes by generating or omitting some samples, but theycannot handle imperfect data. The probabilistic analysis can lead to the identification of issues that exist in the dataset and provide direction to medical experts on dealing with the condition to avoid *** strength of applying the Bayes rule will provide a meaningful interpretation of stroke data. This paper investigates the Baye rule's significance in stroke data analysis. © 2023 IEEE.

关键词： Bayes rule Class imbalance probabilistic analysis Resampling Stroke data

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Phase-bias-blind computational ghost imaging with optical phased array

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Optics Express 2025年第10期33卷 21132-21141页

作者： Hirata, Sota Matsuda, Naoki Komatsu, Kento Tanemura, Takuo Horisaki, Ryoichi Department of Information Physics and Computing Graduate School of Information Science and Technology The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan Department of Electrical Engineering and Information Systems Graduate School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan

We propose a method for computational ghost imaging (CGI) with an optical phased array (OPA), wherein phase biases on the phase shifters are intrinsically unknown. In our method, an object is illuminated with a number of light fields from the OPA using random phase shifts, and the light from the object is captured by a single-pixel detector. The object and the phase biases are simultaneously estimated from the measured intensity signals. We numerically demonstrate the proposed method. Furthermore, we present complex amplitude field acquisition in OPA-based CGI with intensity measurements performed without reference light by simply adding an iris to the detector. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Computational Imaging

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Career Track Based Capstone Course Design for Information systems Curriculum 14

Career Track Based Capstone Course Design for Information Sy...

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14th IEEE Global engineering Education Conference, EDUCON 2023

作者： Gottipati, Swapna Shim, Kyong Jin Datta, Subhajit School of Computing and Information Systems Singapore Management University Singapore Heritage Institute of Technology Department of Computer Science and Engineering Kolkata India

The aim of technical education is to design a career-based curriculum that imparts a set of skills to students and enable them to contribute to a nation's economic progress. With their multifarious uses, information systems (IS) lie at the heart of modern economies. IS curricula offer several tracks for students to pursue career paths based on their interests and opportunities. To offer students an opportunity to apply the knowledge they glean from classroom instructions on real-world problems, capstone projects are essential elements in most, if not all, IS programs. As IS programs increasingly offer a wider range of career paths for students, the design and delivery of such capstone projects present a set of unique challenges. In this paper, we examine the set of challenges and share our experience from designing and delivering a career track-based capstone course for the first time at a large university. Feedback from students and faculty supervisors indicates that the course was able to meet its learning objectives to a notable extent and offered important pointers to future improvements in the course design. © 2023 IEEE.

关键词： Information systems

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Designing Pervasive Games Oriented Towards the Elderly: A Case Study 7th

Designing Pervasive Games Oriented Towards the Elderly: A Ca...

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7th and 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2021 and ICT4AWE 2022

作者： Lacuesta, Raquel Gallardo, Jesús Hernández, Silvia Pérez, Álvaro Department of Computing and Systems Engineering University of Zaragoza Teruel Spain Pre-departmental Unit of Fine Arts University of Zaragoza Teruel Spain

ISBN: (纸本)9783031374951

Elderly people is a segment of population that is quickly increasing during the last years. In the digital society where we live, it is not bearable that this segment of population remains out of the advances in information and communication technologies. In fact, such advances have the potential to improve aspects such as memory or physical condition. This is the case of computer games, and, specifically, of pervasive games. They are a new genre of games in which some of the traditional boundaries of computer games get exceeded. Therefore, in this chapter we explain the design process of a pervasive game oriented towards the elderly and some assessment activities to validate it. The game implies the elderly moving in the real world searching some targets that have to be scanned with a mobile device with the game running. When this happens, the game unlocks a memory, which is a piece of information about a past event, a person or a place. Players store the memories unlocked in an album that can be accessed at any time. Testing of the game in a real environment has started, with some interesting feedback collected. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Augmented reality

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AssemAI: Interpretable Image-Based Anomaly Detection for Manufacturing Pipelines 23

AssemAI: Interpretable Image-Based Anomaly Detection for Man...

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23rd IEEE International Conference on Machine Learning and Applications, ICMLA 2024

作者： Prasad, Renjith Shyalika, Chathurangi El Kalach, Fadi Venkataramanan, Revathy Zand, Ramtin Harik, Ramy Sheth, Amit Artificial Intelligence Institute College of Engineering and Computing University of South Carolina ColumbiaSC29208 United States College of Engineering and Computing University of South Carolina McNair Center for Aerospace Innovation and Research Department of Mechanical Engineering ColumbiaSC29208 United States College of Engineering and Computing University of South Carolina Intelligent Circuits Architectures and Systems Lab ColumbiaSC29208 United States CU-ICAR Clemson University College of Engineering and Computing GreenvilleSC29607 United States

ISBN: (纸本)9798350374889

Anomaly detection in manufacturing pipelines remains a critical challenge, intensified by the complexity and variability of industrial environments. This paper introduces AssemAI, an interpretable image-based anomaly detection system tailored for smart manufacturing pipelines. Utilizing a curated image dataset from an industry-focused rocket assembly pipeline, we address the challenge of imbalanced image data and demonstrate the importance of image-based methods in anomaly detection. Our primary contributions include deriving an image dataset, fine-tuning an object detection model YOLO-FF, and implementing a custom anomaly detection model for assembly pipelines. The proposed approach leverages domain knowledge in data preparation, model development and reasoning. We implement several anomaly detection models on the derived image dataset, including a Convolutional Neural Network, Vision Transformer (ViT), and pretrained versions of these models. Additionally, we incorporate explainability techniques at both user and model levels, utilizing ontology for user-level explanations and SCORE-CAM for indepth feature and model analysis. Finally, the best-performing anomaly detection model and YOLO-FF are deployed in a real-time setting. Our results include ablation studies on the baselines and a comprehensive evaluation of the proposed system. This work highlights the broader impact of advanced image-based anomaly detection in enhancing the reliability and efficiency of smart manufacturing processes. The image dataset, codes to reproduce the results and additional experiments are available at https:/***/renjithk4/AssemAI. © 2024 IEEE.

关键词： Smart manufacturing

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Optimized Deep Learning Mechanism for Intrusion Detection: Leveraging RFE-Based Feature Selection and PCA for Improved Accuracy 5

Optimized Deep Learning Mechanism for Intrusion Detection: L...

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5th International Conference on Sustainable Communication Networks and Application, ICSCNA 2024

作者： Rajkumar, M. Vs, Lakshi Karthik, R. Pavithra, S. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Department of Smart Computing Tamil Nadu India B. Tech-Information Technology School of Computer Science Engineering and Information Systems Vellore Institute of Technology Tamil Nadu India

ISBN: (纸本)9798331530013

With the growing demand for wireless networks, network traffic has surged, particularly involving large-scale data transmission. This results in an increased number of network security threats and the emergence of various cyber-attacks. To overcome these threats, the development of an efficient intrusion detection system (IDS) has become crucial. By leveraging the recent advancements in Artificial intelligence (AI), this project introduces an optimized deep learning mechanism utilizing a prevalent deep learning model, the Deep Neural Network (DNN) algorithm. This proposed method uses feature engineering techniques like feature selection and feature reduction. Given the high dimensionality of the selected datasets, these techniques are employed to prevent over-fitting. Recursive feature elimination performs feature selection followed by Principal Component Analysis for the feature reduction process, thus enhancing the model's efficiency. The system is assessed using two benchmark datasets: KDD and UNSW-NB15. The experimental results indicate that the presented DNN model on the KDD dataset has achieved 92.45% accuracy and 91.35% accuracy on the UNSW-NB15 dataset for intrusion classification. © 2024 IEEE.

关键词： Network intrusion

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Two-Dimensional Z-Complementary Array Quads with Low Column Sequence PMEPRs

Two-Dimensional Z-Complementary Array Quads with Low Column ...

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2023 IEEE International Symposium on Information Theory, ISIT 2023

作者： Das, Shibsankar Banerjee, Adrish Parampalli, Udaya Indian Institute of Technology Kanpur Department of Electrical Engineering Kanpur India University of Melbourne School of Computing and Information Systems VIC Australia

ISBN: (纸本)9781665475549

In this paper, we first propose a new design strategy of 2D Z-complementary array quads (2D-ZCAQs) with feasible array sizes. A 2D-ZCAQ consists of four distinct unimodular arrays satisfying zero 2D auto-correlation sums for non-trivial 2D time-shifts within certain zone. Then, we obtain the upper bounds on the column sequence peak-to-mean envelope power ratio (PMEPR) of the constructed 2D-ZCAQs by using specific auto-correlation properties of some seed sequences. The constructed 2D-ZCAQs with bounded column sequence PMEPR can be used as a potential alternative to 2D Golay complementary array sets for practical applications. © 2023 IEEE.

关键词： Peak-to-Mean Envelope Power Ratio (PMEPR) Z-Complementary Array Quads (ZCAQs) Z-Complementary Pairs (ZCPs)

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Impact of Foreign Objects on Wireless Power Transfer Efficiency in Magnetic Coupling systems 4

Impact of Foreign Objects on Wireless Power Transfer Efficie...

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4th International Conference on Electrical, Computer, Communications and Mechatronics engineering, ICECCME 2024

作者： Khalid, Hassan Mekhilef, Saad Mubin, Marizan Seyedmahmoudian, Mehdi Erel, Mehmet Zahid Bassi, Hussain Alshammari, Obaid University of Malaya Department of Electrical Engineering Kuala Lumpur Malaysia School of Science Computing and Engineering Technologies Swinburne University of Technology Department of Electrical Engineering MelbourneVIC Australia University of Malaya Department of Electrical Engineering Kuala Lumpur Malaysia School of Science Computing and Engineering Technologies Swinburne University of Technology MelbourneVIC Australia Ankara Yildirim Beyazit University Department of Energy Systems Engineering Ankara Turkey Al Jubail Saudi Arabia College of Engineering University of Hail Department of Electrical Engineering Hail Saudi Arabia

ISBN: (纸本)9798350391183

Inductive wireless charging has emerged as a viable solution for charging electric vehicles (EVs) both in stationary mode and on the go, i.e., dynamic charging. EVs are produced at a commercial level, and their wired charging stations are widely available. However, challenges still restrict the development of wireless charging infrastructure on a commercial scale. One significant challenge is the presence of foreign objects on the magnetic coupler surface. Although several foreign object detection (FOD) methods exist, the implementation of each method is cost-dependent. Among these methods, the parametric detection method is considered the most cost-effective. However, the effective precision of this method is still debatable. In this article, the performance of the magnetic coupler is analyzed under the influence of different materials as foreign objects. The analysis presented in this article is threefold. Firstly, a mathematical model of the magnetic coupler in the presence of a foreign object is developed. Secondly, the effect of different materials is analyzed as a function of coil parameters, including inductance, resistance, and coil losses. Lastly, the magnetic field distribution and magnitude are studied using finite element analysis (FEA). The influence of these materials is ultimately evaluated in terms of output power losses and efficiency. The study concludes that the presence of aluminium as a foreign object is responsible for significant power losses in the wireless power transfer system. © 2024 IEEE.

关键词： Charging stations

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A Real-Time Object Tracking Method 5

A Real-Time Object Tracking Method

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5th International Conference on Pattern Recognition and Artificial Intelligence, PRAI 2022

作者： Ismail, Ahmad Vishnyakov, Sergey Moscow Power Engineering Institute Department of Computing Machines Systems and Networks Moscow Russia

ISBN: (数字)9781665499163

ISBN: (纸本)9781665499163

Artificial Intelligence is one of the most vital prospects in our current life;its applications vary from robotics, transport, houses, to industrial facilities and planes. While neural networks offer the ability to recognize and track new objects, it takes time during learning process especially deep neural networks. There are specific computer vision systems, which require high accuracy and high speed conditions, regardless the knowledge of tracked object. Such as a tracking system for a measurement instrument which scans a certain area and follows the location of object(s). In this paper, we introduce a new tracking method for one object in real time system, based on a theory, building a new powerful algorithm to track the center of object in sub-pixel accuracy. © 2022 IEEE.

关键词： Real time systems

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