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Socio-Technical Security Modelling and Simulations in Cyber-Physical Systems: Outlook on Knowledge, Perceptions, Practices, Enablers, and Barriers

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IET Cyber-Physical Systems: Theory and Applications 2025年第1期10卷

作者： Ani, Uchenna Daniel Al-Mhiqani, Mohammed Tuptuk, Nilufer Hailes, Stephen McKendrick Watson, Jeremy Daniel School of Computer Science and Mathematics Keele University Keele United Kingdom Department of Computer Science University of Huddersfield Huddersfield United Kingdom Department of Security and Crime Science University College London London United Kingdom Department of Computer Science University College London London United Kingdom Department of Science Technology Engineering and Public Policy University College London London United Kingdom

Socio-Technical Security Modelling and Simulation (STSec-M&S) is a technique used for reasoning and representing security viewpoints that include both the social and technical aspects of a system. It has shown great potential for improving the cybersecurity and resilience of Critical Infrastructure (CI). This study involved a multi-methods approach, consisting of a scoping literature review and a focus group workshop, conducted with stakeholder engagement from critical infrastructure stakeholders to explore their perceptions and practices regarding the use of socio-technical security modelling and simulation. The findings suggest that the current state of knowledge regarding the use and effectiveness of STSec-M&Ss approaches is limited in CI domains. Consequently, there is little application of it in existing CI systems, regardless of its recognised benefits of enabling a better understanding of CI functionalities, security goals, early and more holistic risk identifications and selection of appropriate countermeasures. The benefits of the STSec-M&S approach can be better realised by effective cross-sector communications and collaborations, team partnerships, system and approach sophistication, and better security awareness amongst others. The potential barriers that can impede such benefits include high expense for implementing the technique, low data availability and quality, regulatory compliance, and competency gaps etc. Helpful recommendations include exploring and using realistic data, validating system security models, and exploring new ways of reskilling and upskilling CI stakeholders in socio-technical security-thinking and M&S approaches to enhance cybersecurity and resilience of CIs. © 2025 The Author(s). IET Cyber-Physical Systems: Theory & Applications published by John Wiley & Sons Ltd on behalf of The Institution of engineering and Technology.

关键词： Cyber attacks

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Deep Neural Network Ensembles for the Detection of Alzheimer's Disease Using Imbalanced Clock Drawing Test Images

Deep Neural Network Ensembles for the Detection of Alzheimer...

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IEEE Annual Computing and Communication Workshop and Conference (CCWC)

作者： Sai Santosh Reddy Danda Alper Kursat Uysal Tian Qin Anu Kumar Varshitha Sannareddy Mengyao Hu Richard Gonzalez Yi Lu Murphey Department of Electrical&Computer Engineering University of Michigan-Dearborn Dearborn USA Department of Computer Engineering Alanya Alaaddin Keykubat University Alanya Turkiye School of Public Health The University of Texas Health Science Center at Houston Houston United States Department of Psychology and Statistics University of Michigan Ann Arbor MI USA

ISBN: (数字)9798331507695

ISBN: (纸本)9798331507701

This paper explores innovative machine learning technologies for the detection of Alzheimer's Disease (AD) from large and imbalanced clock drawing test (CDT) images. We present a deep ensemble learning framework, 2Level MM-MD, which includes two-level ensemble of MultiModel deep neural networks (DNN) trained on MultiData blocks. The data blocks are generated by applying partition based and bootstrap statistical data resampling methods to the large but imbalanced CDT image data. To produce a more robust system that is better adapted to imbalanced CDT data, the 2Level MM-MD ensemble framework attempts to leverages both 1) the richness of large data blocks generated using effective data re-sampling schemes, and 2) multiple deep neural network systems that are trained on the resembled data blocks through transfer learning to produce a more robust system that is better adapted to more generalized CDT image domains. Three deep neural network models (EfficientNet, ResNet101, and ViT), along with six different sampling methods are used to generate re-balanced data blocks, and five different decision schemes are implemented and evaluated. The ensemble systems are trained and evaluated using a large CDT image dataset from Rounds 1 to 9 of the National Health and Aging Trends Study (NHATS), which contains over 47,723 CDT images, where 92% are class 0 (no dementia) and 8% are class 1 (probable dementia). The top classification system is a 2Level MM-MD system E5 with a two-level decision rule SoM. The system generated 0.67 Recall and 0.35 F1-Score on the test data. This represents a 123% improvement in Recall and a 25% improvement in F1-Score compared to the best baseline system, which is a classifier trained using EfficientNet with the training data balanced by oversampling the minority class.

关键词： Transfer learning Training data Artificial neural networks Aging Sampling methods Probabilistic logic Data models Ensemble learning Alzheimer's disease Clocks

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Examining the development of attitude scales using Large Language Models (LLMs)

arXiv

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arXiv 2024年

作者： Symeonaki, Maria Stamou, Giorgos Kazani, Aggeliki Tsouparopoulou, Eva Stamatopoulou, Glykeria School of Political Sciences Department of Social Policy Panteion University of Social and Political Sciences Greece School of Electrical and Computer Engineering National Technical University of Athens Greece

For nearly a century, social researchers and psychologists have debated the efficacy of psychometric scales for attitude measurement, focusing on Thurstone’s equal appearing interval scales and Likert’s summated rating scales. Thurstone scales fell out of favour due to the labour-intensive process of gathering judges’ opinions on the initial items. However, advancements in technology have mitigated these challenges, nullifying the simplicity advantage of Likert scales, which have their own methodological issues. This study explores a methodological experiment to develop a Thurstone scale for assessing attitudes towards individuals living with AIDS. An electronic questionnaire was distributed to a group of judges, including undergraduate, postgraduate, and PhD students from disciplines such as social policy, law, medicine, and computer engineering, alongside established social researchers, and their responses were statistically analysed. The primary innovation of this study is the incorporation of an Artificial Intelligence (AI) Large Language Model (LLM) to evaluate the initial 63 items, comparing its assessments with those of the human judges. Interestingly, the AI provided also detailed explanations for its categorisation. Results showed no significant difference between AI and human judges for 35 items, minor differences for 23 items, and major differences for 5 items. This experiment demonstrates the potential of integrating AI with traditional psychometric methods to enhance the development of attitude measurement scales. © 2024, CC BY-NC-SA.

关键词： Students

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PTQ4ADM: Post-Training Quantization for Efficient Text Conditional Audio Diffusion Models

arXiv

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arXiv 2024年

作者： Vora, Jayneel Krishnan, Aditya Bouacida, Nader Shankar, Prabhu R.V. Mohapatra, Prasant Department of Computer Science University of California Davis United States Department of Electrical and Computer Engineering University of California Davis United States Department of Public Health Sciences University of California Davis Health United States Department of Computer Science University of South Florida Tampa United States

Denoising diffusion models have emerged as state-of-the-art in generative tasks across image, audio, and video domains, producing high-quality, diverse, and contextually relevant data. However, their broader adoption is limited by high computational costs and large memory footprints. Post-training quantization (PTQ) offers a promising approach to mitigate these challenges by reducing model complexity through low-bandwidth parameters. Yet, direct application of PTQ to diffusion models can degrade synthesis quality due to accumulated quantization noise across multiple denoising steps, particularly in conditional tasks like text-to-audio synthesis. This work introduces PTQ4ADM, a novel framework for quantizing audio diffusion models(ADMs). Our key contributions include (1) a coverage-driven prompt augmentation method and (2) an activation-aware calibration set generation algorithm for text-conditional ADMs. These techniques ensure comprehensive coverage of audio aspects and modalities while preserving synthesis fidelity. We validate our approach on TANGO, Make-An-Audio, and AudioLDM models for text-conditional audio generation. Extensive experiments demonstrate PTQ4ADM’s capability to reduce the model size by up to 70% while achieving synthesis quality metrics comparable to full-precision models( Copyright © 2024, The Authors. All rights reserved.

关键词： Digital elevation model

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Identity-Focused Inference and Extraction Attacks on Diffusion Models

arXiv

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arXiv 2024年

The increasing reliance on diffusion models for generating synthetic images has amplified concerns about the unauthorized use of personal data, particularly facial images, in model training. In this paper, we introduce a novel identity inference framework to hold model owners accountable for including individuals’ identities in their training data. Our approach moves beyond traditional membership inference attacks by focusing on identity-level inference, providing a new perspective on data privacy violations. Through comprehensive evaluations on two facial image datasets, Labeled Faces in the Wild (LFW) and CelebA, our experiments demonstrate that the proposed membership inference attack surpasses baseline methods, achieving an attack success rate of up to 89% and an AUC-ROC of 0.91, while the identity inference attack attains 92% on LDM models trained on LFW, and the data extraction attack achieves 91.6% accuracy on DDPMs, validating the effectiveness of our approach across diffusion models. © 2024, CC BY.

关键词： Differential privacy

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Design Considerations for Building Credible Security Testbeds: Perspectives from Industrial Control System Use Cases

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Journal of Cyber Security Technology 2021年第2期5卷 71-119页

作者： Ani, Uchenna P. Daniel Watson, Jeremy M. Green, Benjamin Craggs, Barnaby Nurse, Jason R. C. Department of Science Technology Engineering and Public Policy University College London United Kingdom Computing and Communications Lancaster University United Kingdom Department of Computer Science University of Bristol United Kingdom School of Computing University of Kent United Kingdom

This paper presents a mapping framework for design factors and an implementation process for building credible Industrial Control Systems (ICS) security testbeds. The security and resilience of ICSs has become a critical concern to operators and governments following widely publicised cyber security events. The inability to apply conventional Information Technology security practice to ICSs further compounds challenges in adequately securing critical systems. To overcome these challenges, and do so without impacting live environments, testbeds are widely used for the exploration, development, and evaluation of security controls. However, how a testbed is designed and its attributes, can directly impact not only its viability but also its credibility. Combining systematic and thematic analysis, and the mapping of identified ICS security testbed design attributes, we propose a novel relationship map of credibility-supporting design factors (and their associated attributes) and a process implementation flow structure for ICS security testbeds. The framework and implementation process highlight the significance of demonstrating some design factors such as user/experimenter expertise, clearly defined testbed design objectives, simulation implementation approach, covered architectural components, core structural and functional characteristics covered, and evaluations to enhance confidence, trustworthiness and acceptance of ICS security testbeds as credible. These can streamline testbed requirement definition, improve design consistency and quality while reducing implementation costs. © 2020 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Testbeds

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Cyber Attack Detection and Classification for Integrated On-board Electric Vehicle Chargers subject to Stochastic Charging Coordination

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Transportation Research Procedia 2023年 70卷 44-51页

作者： Ali Arsalan Laxman Timilsina Behnaz Papari Grace Muriithi Gokhan Ozkan Phani Kumar Christopher S. Edrington Department of Automotive Engineering Clemson University Greenville 29607 U.S. The Holcombe Department of Electrical and Computer Engineering Clemson University Clemson 29631 U.S Distribution A. Approved for public release distribution unlimited. (OPSEC 7474)

Cyber-physical system (CPS) of EV on-board chargers is connected to an IOT-based communication network for coordinated control, which is highly vulnerable to cyber-attacks. This charging coordination control incorporating hundreds of EVs and associated charging sessions, feed in a stochastic reference input to energy management system (EMS) of on-board EV chargers. Hence, under these varying operating conditions, a pure data-driven-based detection model can experience a disturbance detection failure. Therefore, a model predictive control (MPC) based machine learning (ML) network, integrated with a residual based training data pre-processing is proposed in this paper. This MPC based ML approach can effectively detect a tempered response while addressing the aleatory behaviour of cooperative control with enhanced disturbance detection accuracy. The proposed model utilizing various system level signals can also efficiently classify a normal condition, cyber-attack, and a physical fault. The superior performance of the proposed approach is validated by using different case study scenarios of training datasets.

关键词： Integrated on-board chargers (IOBCs) cyber-attack MOSFET fault, neural networks model predictive control direct power control

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Compact Millimeter-Wave Antenna Operating in 28/38 GHz Spectrum

Compact Millimeter-Wave Antenna Operating in 28/38 GHz Spect...

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2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022

作者： Rizvi, Syed Naheel Raza Sarfraz, Muhammad Alibakhshikenari, Mohammad Dalarsson, Mariana Falcone, Francisco Chungbuk National University Department of Information and Communication Engineering Cheongju Korea Republic of Virtual University of Pakistan Department of Computer Science Lahore Pakistan Universidad Carlos III de Madrid Department of Signal Theory and Communications Madrid Leganés28911 Spain KTH Royal Institute of Technology School of Electrical Engineering and Computer Science StockholmSE 100-44 Sweden Public University of Navarre Electric Electronic and Communication Engineering Department Pamplona31006 Spain Public University of Navarre Institute of Smart Cities Pamplona31006 Spain

ISBN: (数字)9781665496582

ISBN: (纸本)9781665496582

We present a compact wideband antenna operating in the 28 GHz and 38 GHz millimeter-wave spectrum. The proposed antenna is designed on the Rogers RT/duroid 5880 substrate. The proposed antenna has a simple geometry and compact dimensions of 17 mm × 12 mm × 0.79 mm. The antenna design is simulated using the ANSYS HFSS software. The features of the proposed antenna are also compared to similar designs from the literature, to demonstrate the potential of our antenna for use in the targeted frequency band. The results in the present paper indicate that our design is a good candidate for use in future wireless communication systems. © 2022 IEEE.

关键词： Microwave antennas

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Multi-Agent Based Stochastic Dynamical Model to Measure Community Resilience

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Journal of Social Computing 2022年第3期3卷 262-286页

作者： Jaber Valinejad Lamine Mili C.Natalie Van Der Wal Data and System Science Lab Harvard Medical SchoolHarvard UniversityCambridgeMA 02138USA Bradley Department of Electrical and Computer Engineering Virginia TechNorthern Virginia CenterFalls ChurchVA 22043USA Department of Multi-Actor Systems Faculty of TechnologyPolicy and ManagementDelft University of TechnologyDelft2600 AAthe Netherlands.

Emergency services and utilities need appropriate planning tools to analyze and improve infrastructure and community resilience to *** as a key metric of community resilience is the social well-being of a community during a disaster,which is made up of mental and physical social *** factors influencing community resilience directly or indirectly are emotional health,emergency services,and the availability of critical infrastructures services,such as food,agriculture,water,transportation,electric power,and communications *** turns out that in computational social science literature dealing with community resilience,the role of these critical infrastructures along with some important social characteristics is not *** address these weaknesses,we develop a new multi-agent based stochastic dynamical model,standardized by overview,design concepts,details,and decision(ODD+D)protocol and derived from neuro-science,psychological and social sciences,to measure community resilience in terms of mental and physical *** this model,we analyze the micro-macro level dependence between the emergency services and power systems and social characteristics such as fear,risk perception,informationseeking behaviour,cooperation,flexibility,empathy,and experience,in an artificial ***,we simulate this model in two case studies and show that a high level of flexibility,experience,and cooperation enhances community *** for both theory and practice are discussed.

关键词： community resilience collective behavior emergency services power systems critical infrastructures artificial society overview,design concepts,details,and decision(ODD+D) cyber-physical-social system

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engineering Casimir interactions with epsilon-near-zero materials

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Physical Review A 2022年第6期105卷 L061501-L061501页

作者： Miguel Camacho Tao Gong Benjamin Spreng Iñigo Liberal Nader Engheta Jeremy N. Munday Department of Electrical and Systems Engineering University of Pennsylvania Philadelphia Pennsylvania 19104 USA Department of Electronics and Electromagnetism Universidad de Sevilla 41012 Seville Spain Department of Electrical and Computer Engineering University of California Davis California 95616 USA Department of Materials Science and Engineering University of California Davis California 95616 USA Department of Electrical and Electronic Engineering Public University of Navarra 31006 Pamplona Spain

In this paper, we theoretically demonstrate the tunability of the Casimir force both in sign and magnitude between parallel plates coated with dispersive materials. We show that this force, existing between uncharged plates, can be tuned by carefully choosing the value of the plasma frequency (i.e., the epsilon-near-zero frequency) of the coating in the neighborhood of the resonance frequency of the cavity. The coating layer enables a continuous variation of the force between four limiting values when a coating is placed on each plate. We explore the consequences of such variation when pairs of electric and magnetic conductors (i.e., low and high impedance surfaces) are used as substrates on either side, showing that this continuous variation results in changes in the sign of the force, leading to both stable and unstable conditions, which could find interesting potential applications in nanomechanics, including nanoparticle tweezing.

关键词： Casimir effect Electromagnetic interactions Light-matter interaction Metamaterials Optical materials & elements

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