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Achieving Runtime State Verification Assurance in Critical Cyber-Physical Infrastructures

Achieving Runtime State Verification Assurance in Critical C...

2021 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2021

作者： Rivera, Abel O. Gomez Tosh, Deepak K. Shetty, Sachin University of Texas at El Paso Department of Computer Science TX United States Virginia Modeling Analysis and Simulation Center Old Dominion University TX United States

ISBN: (纸本)9781665415026

Industrial Cyber-Physical Systems (ICPS) are an essential backbone of national critical infrastructures. They help monitor and control crucial cyber-enabled services such as energy generation. Commonly ICPS monitors the physical process through Supervisory Control and Data Acquisition (SCADA) systems. The SCADA ecosystem takes critical real-time and future system operational decisions based on the runtime state behavior of field sensors. Traditional SCADA systems use legacy and insecure communication protocols such as the Modbus protocol that lack adequate security mechanisms to provide robust runtime state behavior assurance of constrained field sensors. Therefore, constrained field sensors are commonly vulnerable to standard semantic attacks that gradually change the behavior state of infected devices. This paper discusses process integrity assurance techniques necessary to enhance the security of behavior-based protocols such as the Modbus protocol. The Runtime State Verification (RSV) protocol proposed in this paper aims to address semantic attacks in the SCADA ecosystem by integrating behavior-based Mandatory Results Automata (MRA) and a Hyperledger Fabric (HLF) network. The RSV protocol provides high process integrity assurance through enhanced behavior-based MRA suitable for the constrained field devices. A proof of concept of the RSV protocol has been evaluated in an emulated water-tube boiler. Preliminary evaluations of the RSV protocol aimed to measure the efficiency of the proposed protocol by monitoring an Combustion Efficiency (CE) process necessary to preserve optimal combustion, thus minimizing costs and future maintenance of water-tube boilers. We analyze the overall network overhead and latency of the proposed RSV protocol by evaluating the HLF network performance and comparing the proposed RSV protocol with the state-of-art BloSPAI protocol. Through the preliminary evaluations of the proposed RSV protocol, this paper demonstrates that the proposed

关键词： Water tube boilers

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EM-PAD: An Effective Mechanism for Phishing Attack Detection

EM-PAD: An Effective Mechanism for Phishing Attack Detection

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International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Aakash Saksham Mittal Mohammad Wazid Amit Kumar Mishra Ashok Kumar Das Sachin Shetty Mohsen Guizani Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun India Department of Computer Science and Engineering Graphic Era Hill University Dehradun India Center for Security Theory and Algorithmic Research International Institute of Information Technology Hyderabad India Department of Computational Modeling and Simulation Engineering Virginia Modeling Analysis and Simulation Center Old Dominion University Suffolk VA USA Machine Learning Department Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) Abu Dhabi UAE

ISBN: (数字)9798350361261

ISBN: (纸本)9798350361278

In the present era, the increasing number of network devices and ubiquitous computing leads to the flow of enormous amounts of data traffic, including sensitive and confidential information, on the internet and carrying out commercial and banking transactions online. This gives cybercriminals an opportunity to launch an attack like phishing to steal confidential information from the user and gain unauthorized access. This can be mitigated by the help of an intelligent machine learning-based phishing detection system, which can detect potential phishing attacks and take appropriate action. In this paper, we have addressed this major cyber issue and proposed a machine learning-based phishing detection scheme (in short, EM-PAD), which is trained on a benchmark dataset and evaluated on standard metrics: F1-score and Accuracy. The proposed model is compared with different existing schemes based on Accuracy, indicating that it has outperformed them with remarkable results.

关键词： Wireless communication Measurement Accuracy Phishing Computational modeling Banking Benchmark testing

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AKM-FCCI: Secure Authentication and Key Management Mechanism for Fog Computing-Based IoT-Driven Critical Infrastructure

AKM-FCCI: Secure Authentication and Key Management Mechanism...

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International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Vijay Karnatak Neha Tripathi Amit Kumar Mishra Mohammad Wazid Ashok Kumar Das Mohsen Guizani Sachin Shetty Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun India Department of Computer Science and Engineering Graphic Era Hill University Dehradun India Center for Security Theory and Algorithmic Research International Institute of Information Technology Hyderabad India Machine Learning Department Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) Abu Dhabi UAE Department of Computational Modeling and Simulation Engineering Virginia Modeling Analysis and Simulation Center Old Dominion University Suffolk VA USA

ISBN: (数字)9798350361261

ISBN: (纸本)9798350361278

Critical infrastructure refers to the key systems, assets, and facilities, whether they are physical or virtual, that are necessary for the overall functioning of a country. As our reliance on technology and networked systems continues to expand, so does the significance of taking precautions to protect critical infrastructure from being compromised by cyberattacks. We need some security schemes to secure the communication happening in the critical infrastructure devices. Therefore, in this paper, we focus on the design of an authentication and key establishment scheme, which is used in the critical infrastructure to secure its data transmissions. A secure authentication and key management mechanism for fog computing-based IoT-driven critical infrastructures (in short, AKM-FCCI) is proposed in the paper. We then provide the network model and threat model of the proposed AKM-FCCI to explain its deployment and organization of devices and servers. The threat model further explains the various threats of this communication environment. In addition, the security analysis of AKM-FCCI is presented to demonstrate that it is secure against the many different kinds of attacks that could be launched against it. The comparisons demonstrate that the performance of AKM-FCCI is superior to that of the other currently used schemes. In addition to that, it offers a high level of security and utility. Therefore, the proposed AKM-FCCI is appropriate for use in protecting critical infrastructure equipment against a wide variety of threats.

关键词： Threat modeling Wireless communication Performance evaluation Authentication Organizations Critical infrastructure Safety

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Assessing Media’s Representation of Frustration Towards Venezuelan Migrants in Colombia 16th

Assessing Media’s Representation of Frustration Towards Ven...

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16th International Conference on Social Computing, Behavioral-Cultural modeling and Prediction and Behavior Representation in modeling and simulation, SBP-BRiMS 2023

作者： Llinas, Brian Huseynli, Guljannat Frydenlund, Erika Palacio, Katherine Llinas, Humberto Padilla, Jose J. Computer Science Department Old Dominion University NorfolkVA United States Graduate Program of International Studies Old Dominion University NorfolkVA United States Virginia Modeling Analysis and Simulation Center Old Dominion University SuffolkVA United States Universidad del Norte Kilómetro 5 Vía Atlántico Puerto Colombia Colombia

ISBN: (纸本)9783031431289

This research utilizes statistical path modeling to examine the relationship between the number of Venezuelans migrating to Colombia due to economic collapse and the media's coverage of specific topics. We focus on media coverage expressing frustration regarding migration, infrastructure, government, and geopolitics. Our approach combines quantitative analysis of code frequencies from qualitative content analysis of 1,360 regional newspaper articles on migration-related issues. Our findings indicate that an increase in the Venezuelan population in Colombia leads to more negative media coverage of infrastructure impacts, such as hospitals and schools. This negative coverage, referred to as "frustration," indirectly contributes to increased coverage of infrastructure frustration. This suggests an opportunity for intervention by balancing media coverage to reduce the excessive use of negative language and stereotypes, potentially mitigating anti-migrant sentiment fueled by frustration towards infrastructure. Furthermore, we observe that as migration increases, coverage of frustration towards geopolitics decreases, while frustration towards the Colombian government rises. This shift may reflect a transition from contemplating the causes of migration to focusing on the humanitarian response (or lack thereof) by the host government in accommodating the new arrivals. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Artificial intelligence

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An Auto-Parallel Method for Deep Learning Models Based on Genetic Algorithm 29

An Auto-Parallel Method for Deep Learning Models Based on Ge...

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29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Zeng, Yan Huang, Chengchuang Ni, Yijie Zhou, Chunbao Zhang, Jilin Wang, Jue Zhou, Mingyao Xue, Meiting Zhang, Yunquan Hangzhou Dianzi University School of Computer Science and Technology Hangzhou310018 China Ministry of Education Key Laboratory for Modeling and Simulation of Complex Systems Hangzhou310018 China Data Security Governance Zhejiang Engineering Research Center Hangzhou310018 China Hangzhou Dianzi University School of ITMO Joint Institute Hangzhou310018 China Institute of Computer Network Information Center of the Chinese Academy of Sciences Beijing100086 China HuaWei China Institute of Computing Technology of the Chinese Academy of Sciences State Key Laboratory of Computer Architecture Beijing100086 China

ISBN: (纸本)9798350330717

As the size of datasets and neural network models increases, automatic parallelization methods for models have become a research hotspot in recent years. The existing auto-parallel methods based on machine learning or graph algorithms still have issues with search efficiency and applicability. This paper proposes an automatic parallel method based on a dual-population genetic algorithm, TGA, which transforms model partitioning and placement into an integer linear programming problem and constructs a cost model to evaluate the solution. The solution space is built using the neural network's dataflow graph and device cluster's topology, and the dual-population genetic algorithm is used to search for the optimal model parallel strategy. Experiments with various models show that the proposed method can improve single-step execution time by up to 42% compared to the Baechi method and up to 37.7% compared to the Hierarchical method. © 2023 IEEE.

关键词： Auto-Parallel Distributed machine learning Genetic algorithm Integer linear programming Model parallelism

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Electro-magneto-hydrodynamic Eyring-Powell fluid flow through micro-parallel plates with heat transfer and non-Darcian effects

Electro-magneto-hydrodynamic Eyring-Powell fluid flow throug...

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作者： Bhatti, Muhammad Mubashir Doranehgard, Mohammad Hossein Ellahi, Rahmat College of Mathematics and Systems Science Shandong University of Science and Technology Qingdao China Department of Mechanical and Aerospace Engineering Hong Kong University of Science and Technology Clear Water Bay Hong Kong Center for Modeling & Computer Simulation Research Institute King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia Department of Mathematics and Statistics International Islamic University Islamabad Pakistan

The Eyring-Powell fluid flow between two micro-parallel plates in the context of electro-magneto-hydrodynamic is the focus of the article. The Lorentz force, which is generated by the interactions of a vertical magnetic field and an externally imposed horizontal electrical field, is presumed to be unilateral and one-dimensional. Using the Darcy-Brinkman-Forchheimer model, the medium of the micro-parallel plates is assumed to be porous. The energy equation evaluates the effect of viscous dissipation and joule heating as well. To solve the nonlinear coupled differential equations, analytical solutions are derived using the multi-step differential transform method. For the velocity and temperature profiles, the impact of all evolving variables is explored and illustrated in graphs and tables. It can be seen from the graphical results that the Darcy parameter, and also the magnetic field, are oppositional to both fluid motion and temperature profile. Additionally, the thermal Grashof number improves the velocity and temperature profiles of the system. On the velocity and temperature profiles, the outcomes for both fluid parameters are nearly identical. © 2022 John Wiley & Sons Ltd.

关键词： Temperature control

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Multimodal Fluorescence Lifetime Imaging and Optical Coherence Elastography for Mesoscopic Structural, Biomechanical, and Molecular Imaging

Multimodal Fluorescence Lifetime Imaging and Optical Coheren...

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2024 Clinical and Translational Biophotonics, Translational 2024 - Part of Optica Biophotonics Congress: Biomedical Optic

作者： Chavez, Luis Gao, Shan Pandey, Vikas Yuan, Nanxue Li, Jiayue Hepburn, Matt S. Smith, Percy Edelheit, Caroline Corr, David T. Kennedy, Brendan F. Intes, Xavier Center for Modeling Simulation and Imaging for Medicine Rensselaer Polytechnic Institute TroyNY12180 United States BRITElab Harry Perkins Institute of Medical Research QEII Medical Centre Nedlands and Centre for Medical Research The University of Western Australia PerthWA6009 Australia Department of Electrical Electronic & Computer Engineering School of Engineering The University of Western Australia PerthWA6009 Australia Institute of Physics Nicolaus Copernicus University Torun Poland

We report on a methodology to manufacture multimodal phantoms with fluorescence lifetime imaging and optical coherence elastography contrasts. Phantom validation demonstrates the ability to tune fluorescence and strai... 详细信息

关键词： Phantoms

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Energy-Efficient Trajectory and Age of Information Optimization for Urban Air Mobility

Energy-Efficient Trajectory and Age of Information Optimizat...

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IEEE Symposium on Network Operations and Management

作者： Hyeonsu Kim Yu Min Park Pyae Sone Aung Md. Shirajum Munir Choong Seon Hong Department of Artificial Intelligence Kyung Hee University Yongin Republic of Korea Department of Computer Science and Engineering Kyung Hee University Yongin Republic of Korea Virginia Modeling Analysis and Simulation Center Old Dominion University Suffolk VA USA

ISBN: (数字)9798350327939

ISBN: (纸本)9798350327946

Urban air Mobility (UAM) has been conceived as a new form of transportation. UAM ultimately aims to operate unmanned, so it needs to select its trajectory and periodically send its status to the base station (BS). As an status indicator, the age of information (AoI) signifies the freshness of the information, and it is crucial for applications like real-time control systems. In this article, we address two main challenges: optimizing the UAM’s trajectory and updating the AoI between the UAM and the BS. We formulate an algorithm to maximize the energy efficiency of each UAM’s trajectory and jointly minimize the AoI cycle. As a complicated and non-convex problem, we approach proximal policy optimization (PPO) as our solution in this paper. Experiment results show that our proposed method outperformed the direct trajectory baseline in similar energy efficiency but achieved 46% increased efficiency in average AoI.

关键词： Three-dimensional displays Trajectory planning simulation Transportation Information processing Information age Energy efficiency

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GPT-4 Generated Narratives of Life Events using a Structured Narrative Prompt: A Validation Study

arXiv

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arXiv 2024年

作者： Lynch, Christopher J. Jensen, Erik Munro, Madison H. Zamponi, Virginia Martínez, Joseph O’Brien, Kevin Feldhaus, Brandon Smith, Katherine Reinhold, Ann Marie Gore, Ross Virginia Modeling Analysis and Simulation Center Old Dominion University SuffolkVA United States Electrical and Computer Engineering Department Old Dominion University NorfolkVA United States College of Engineering Montana State University BozemanMT United States

Large Language Models (LLMs) play a pivotal role in generating vast arrays of narratives, facilitating a systematic exploration of their effectiveness for communicating life events in narrative form. In this study, we employ a zero-shot structured narrative prompt to generate 24,000 narratives using OpenAI’s GPT-4. From this dataset, we manually classify 2,880 narratives and evaluate their validity in conveying birth, death, hiring, and firing events. We observe that 87.43% of the narratives sufficiently convey the intention of the structured narrative prompt. To automate the identification of valid and invalid narratives, we train and validate nine Machine Learning models on the classified datasets. Leveraging these models, we extend our analysis to predict the classifications of the remaining 21,120 narratives. The ML models all excelled at classifying valid narratives as valid, but experienced challenges at simultaneously classifying invalid narratives as invalid. Our findings advance the study of LLM capabilities, limitations, and validity and also offer practical insights for narrative generation and natural language processing applications. © 2024, CC BY.

关键词： Zero-shot learning

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Automatic classification of activities in classroom videos

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computers and Education: Artificial Intelligence 2024年 6卷

作者： Foster, Jonathan K. Korban, Matthew Youngs, Peter Watson, Ginger S. Acton, Scott T. Department of Educational Theory and Practice University at Albany United States C.L. Brown Department of Electrical and Computer Engineering University of Virginia United States Department of Curriculum Instruction and Special Education University of Virginia United States Virginia Modeling Analysis and Simulation Center Old Dominion University United States

Classroom videos are a common source of data for educational researchers studying classroom interactions as well as a resource for teacher education and professional development. Over the last several decades emerging technologies have been applied to classroom videos to record, transcribe, and analyze classroom interactions. With the rise of machine learning, we report on the development and validation of neural networks to classify instructional activities using video signals, without analyzing speech or audio features, from a large corpus of nearly 250 h of classroom videos from elementary mathematics and English language arts instruction. Results indicated that the neural networks performed fairly-well in detecting instructional activities, at diverse levels of complexity, as compared to human raters. For instance, one neural network achieved over 80% accuracy in detecting four common activity types: whole class activity, small group activity, individual activity, and transition. An issue that was not addressed in this study was whether the fine-grained and agnostic instructional activities detected by the neural networks could scale up to supply information about features of instructional quality. Future applications of these neural networks may enable more efficient cataloguing and analysis of classroom videos at scale and the generation of fine-grained data about the classroom environment to inform potential implications for teaching and learning. © 2024 The Authors

关键词： computer vision

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