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IEEE International Conference on Trust, Security and Privacy in Computing and communications (TrustCom)

作者： Zahra Pooranian Mohammad Shojafar Pedram Asef Matthew Robinson Harry Lees Mark Longden Department of Computer Science University of Reading UK 5G/6GIC Institute for Communication Systems (ICS) University of Surrey Guildford UK Dept. of Mechanical Engineering University College London London UK Dept. of Engineering and Technology University of Hertfordshire Hatfield UK R&D Group RL Auto Ltd Basingstoke UK

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

This paper focuses on the requirement for creating novel frameworks to monitor and identify cyberattacks in Connected Vehicles (CVs). The health of the sensors in CVs becomes crucial when performance predictions and communication-related errors can compromise the resilience of the sensory network. To meet the evolving demands of connected vehicle (CV) systems, Intrusion Detection systems (IDS) must be regularly updated and tailored as powerful monitoring entities. To equip cloud-tied operators with the ability to comprehend unusual sensor data originating from vehicles at the cloud level, we designed an innovative Real-time Cloud-based Adversarial IDS called RCA-IDS. This system exclusively focuses on detecting and explaining instances of sensor data manipulation caused by poisoning attacks. Two attack mechanisms were created utilizing random-based and silhouette-based clustering methods. Subsequently, two defence mechanisms based on multi-layer neural network-type deep learning were proposed to counter these attacks. The newly introduced RCA-IDS demonstrates a minimum accuracy of 90% in detecting cyberattacks.

关键词： Deep learning Cloud computing Connected vehicles Clustering algorithms Real-time systems Liquid crystal displays Classification algorithms

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Hybrid Gromov-Wasserstein Embedding for Capsule Learning

arXiv

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arXiv 2022年

作者： Shamsolmoali, Pourya Zareapoor, Masoumeh Das, Swagatam Granger, Eric García, Salvador Dept. of Automation Shanghai Jiao Tong University Shanghai China Electronics and Communication Sciences Unit Indian Statistical Institute Kolkata India Dept. of Systems Engineering Ecole de tech-nologie supérieure Université du Québec Montreal Canada Dept. of Computer Science and Artificial Intelligence University of Granada Granada Spain

Capsule networks (CapsNets) aim to parse images into a hierarchy of objects, parts, and their relations using a two-step process involving part-whole transformation and hierarchical component routing. However, this hierarchical relationship modeling is computationally expensive, which has limited the wider use of CapsNet despite its potential advantages. The current state of CapsNet models primarily focuses on comparing their performance with capsule baselines, falling short of achieving the same level of proficiency as deep CNN variants in intricate tasks. To address this limitation, we present an efficient approach for learning capsules that surpasses canonical baseline models and even demonstrates superior performance compared to high-performing convolution models. Our contribution can be outlined in two aspects: firstly, we introduce a group of subcapsules onto which an input vector is projected. Subsequently, we present the Hybrid Gromov-Wasserstein framework, which initially quantifies the dissimilarity between the input and the components modeled by the subcapsules, followed by determining their alignment degree through optimal transport. This innovative mechanism capitalizes on new insights into defining alignment between the input and subcapsules, based on the similarity of their respective component distributions. This approach enhances CapsNets’ capacity to learn from intricate, high-dimensional data while retaining their interpretability and hierarchical structure. Our proposed model offers two distinct advantages: (i) its lightweight nature facilitates the application of capsules to more intricate vision tasks, including object detection;(ii) it outperforms baseline approaches in these demanding tasks. Our empirical findings illustrate that Hybrid Gromov-Wasserstein Capsules (HGWCapsules) exhibit enhanced robustness against affine transformations, scale effectively to larger datasets, and surpass CNN and CapsNet models across various vision tasks. © 202

关键词： Object detection

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A New Hybrid Cipher based on Prime Numbers Generation Complexity: Application in Securing 5G networks

A New Hybrid Cipher based on Prime Numbers Generation Comple...

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ACS/IEEE International Conference on computer systems and Applications

作者： Adda Boualem Abdelkader Berrouachedi Marwane Ayaida Hisham Kholidy Elhadj Benkhelifa Department of Computer Science Ibn Khaldoun University Tiaret Algeria Paragraphe Lab University of Paris 8 Paris France Polytechnique Hauts-de-France CNRS Univ. Lille UMR 8520 - IEMN France CReSTIC EA 3804 Univ. Reims Champagne Ardenne France Dept. of Networks and Computer Security College of Engineering SUNY Polytechnic Institute Utica New Yourk USA Smart Systems AI and Cybersecurity Research Centre Staffordshire Univ UK

Today’s cellular networks (known as 2G, 3G, and 4G) provide a solid foundation for connecting things. The Internet of Things (IoT) is helping people live and work smarter and take full control of their lives. In addition to providing smart devices for home automation, IoT is also critical for businesses. The security of classical cryptosystems is characterized by their simple arithmetic complexity. This type uses; shifts, arrangements, permutations, and substitutions of letters, words, or phrases to encrypt a given message. Moreover, this kind of cryptosystem is easy to break, because the complexity of their scheme is convergent. On the other hand, the security of modern cryptosystems is characterized by complex arithmetic, using the concept of keys; private keys to encrypt and public keys to decrypt. This type is hard to break because of the complexity of their scheme being divergent. This paper aims to secure the 5G networks with a new variant of the classical Polybius Checkerboard Cipher (HPCC). The system of letter substitution is based on the complexity and the divergence of private key generation. Filling a magic square with primes is an NP-hard task, which shows the complexity and divergence of the strategy adopted in this variant.

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Plasmonic Pentamer-Arranged Nanohole Arrays

Plasmonic Pentamer-Arranged Nanohole Arrays

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Photonics North

作者： Weil Ru Wong Hyung Woo Choi Fatemeh Fouladi Mahani Luis Angel Mayoral Astorga Arash Mokhtari Pierre Berini Department of Electrical Engineering Integrated Lightwave Research Group University of Malaya Kuala Lumpur Malaysia School of Electrical Engineering and Computer Science University of Ottawa Ottawa ON Canada Nexusfor Quantum Technologies Institute University of Ottawa ON Canada Electrical Engineering Dept. Optical and RF Communication Systems (ORCS) Lab Shahid Bahonar University of Kerman Kerman Iran Department of Physics University of Ottawa Ottawa ON Canada

ISBN: (数字)9798350366365

ISBN: (纸本)9798350366372

We report the theoretical and experimental investigation of pentamer arrangements of nanoholes in a thin Au film arrayed over a large area. The pentamer arrangements support coupled plasmonic resonances localized to the nanoholes that exhibit a high near-field sensitivity and low polarization dependance. The structures are compelling for applications in biosensing and in surface enhanced Raman scattering (SERS).

关键词： Gold Sensitivity Biological system modeling Raman scattering Plasmons Sensors Biosensors

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Simplified Framework for Diagnosis Brain Disease Using Functional Connectivity

Simplified Framework for Diagnosis Brain Disease Using Funct...

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communication & Computing (WCONF), World Conference on

作者： T. Swarnalatha B. Supraja Akhila Akula Raaid Alubady K Saikumar Patakottu Prasadareddy Department of CSE PBR Visvodaya Institute Of Technology And Science Kavali Department of CSE GNITC Hyderabad Department of Electronics and Communication Engineering MLR Institute of Technology Hyderabad Telangana India Technical Engineering College Al-Ayen University Thi-Qar Iraq College of Information Networks University of Babylon Babylon Iraq Computer Science Malla Reddy University Malla Reddy University School of Engineering Maisammaguda Dulapally Hyderabad Telangana Dept. of ECE Student MVGR College of Engineering Vijayaram Nagar campus Chintalavalasa Vizianagaram Andhra Pradesh

ISBN: (数字)9798350395327

ISBN: (纸本)9798350395334

Diagnosing brain infections is another region where artificial intelligence and neuroscience research meet. Functional connectivity (FC) examination has turned into the standard method for checking out fMRI information. The quantitative investigation of functional magnetic resonance imaging (fMRI) information might uncover significant variables that assistance in clinical assessment. Then again, the greater part of the review done in the past has zeroed in on placing mind sicknesses into bunches in light of low-request FC characteristics and has disregarded the conceivable significance of high-request utilitarian connections between cerebrum regions. To protect this issue, physicists formulated an unusual MFC a multi-level fusion classification paradigm for recognizing mental disorders. To begin, they built a model using a deep neural network (DNN) to collect and formulate vital fundamental portrayals for the depressed-request and extreme-request FC designs we fashioned. During the preparation of the DNN model, there were both uncontrolled and directed learning steps. During the managed calibrating, model learning was added to make the element portrayal more reduced inside each class and simpler to distinguish from different classes. Then, at that point, to characterize mind illnesses, we consolidated the theoretical staggered FC highlights we had learned and utilized various leveled stacking learning techniques to prepare a troupe classifier. Deliberate tests were finished with two genuine, enormous-scope fMRI datasets. The recommended MFC model worked effectively in ordering information for various preprocessing processes, different mind parcellations, and different cross-approval techniques, which shows that it works and can be utilized in a wide range of circumstances. By and large, this work gives an effective method for consolidating significant low-request and high-request FC examples to make it more straightforward to order mind sicknesses.

关键词： Neuroscience Reviews Mental disorders Stacking Cerebrum Artificial neural networks Functional magnetic resonance imaging Standards Medical diagnostic imaging Diseases

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Healthier and Independent Living of the Elderly: Interoperability in a Cross-Project Pilot

Healthier and Independent Living of the Elderly: Interoperab...

引用

2022 Interoperability for Enterprise systems and Applications Workshops, I-ESA Workshops 2022

作者： Agostinho, Carlos Pimenta, Andreia Marques, Maria Tsiouris, Kostas M. Kalatzis, Fanis Nikitas, Christos Iliadou, Eleftheria Occhipinti, Mattia Kouris, Ioannis Koutsouris, Dimitrios Basdekis, Ioannis Koloutsou, Konstantina Gallo, Luigi de Pietro, Giueppe Jardim-Goncalves, Ricardo FCT-Campus Caparica2829-516 Portugal NOVA School of Science and Technology Caparica2829-516 Portugal Secretaria Regional de Saúde e Ptroteção Civil Rua da Carreira nº107 Funchal9000-042 Portugal Unit of Medical Technology and Intelligent Information Systems Dept. of Material Science and Engineering University of Ioannina IoanninaGR45110 Greece National Kapodistrian University of Athens First Department of Otolaryngology-Head and Neck Surgery ‘Hippokrateio’ General Hospital Athens Greece Università degli Studi di Milano Computer Science Department Milan Italy Biomedical Engineering Laboratory Institute of Communication and Computer Systems National Technical University of Athens Heroon Polytechneiou 9 15780 Greece SPHYNX Technology Solutions AG Zug Switzerland National Research Council of Italy Via P. Bucci cubo 8/9C Rende87036 Italy

The ageing of the population creates new heterogeneous challenges for age-friendly living. The progressive decline in physical and cognitive skills tends to prevent elderly people from performing basic instrumental activities of daily living and there is a growing interest in technology for aging support. Digital health today can be exercised by anyone owning a smartphone and parameters such as heart rate, step counts, calorie intake, sleep quality, can be collected and used not only to monitor and improve the individual’s health condition but also to prevent illnesses. However, for the benefits of e-health to take place, digital health data, either Electronic Health Records (EHR) or sensor data from the IoMT, must be shared, maintaining privacy and security requirements but unlocking the potential for research an innovation throughout EU. This paper demonstrates the added value of such interoperability requirements, and a form of accomplishing them through a cross-project pilot. © 2022 CEUR-WS. All rights reserved.

关键词： Interoperability

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Intra-Datacenter Load Balancing in a Federated Cloud with Throttled Algorithm

Intra-Datacenter Load Balancing in a Federated Cloud with Th...

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science, Engineering and Business for Sustainable Development Goals (SEB-SDG), International Conference on

作者： Damola Gideon Akinola Emmanuel Adetiba Abdultaofeek Abayomi Uche Nnaji Surendra Thakur Sibusiso Moyo Department of Electrical and Information Engineering Covenant Applied Informatics and Communications African Center of Excellence Covenant University Ota Nigeria HRA Institute for Systems Science Durban University of Technology Durban South Africa Department of Information and Communication Technology Mangosuthu University of Technology Durban South Africa Dept. of Computer and Information Science Covenant Applied Informatics and Communications African Center of Excellence Covenant University Ota Nigeria KZN e-Skills CoLab Durban University of Technology Durban South Africa School for Data Science and Computational Thinking and Department of Mathematical Sciences Stellenbosch University Stellenbosch South Africa

ISBN: (数字)9798350358155

ISBN: (纸本)9798350358162

The emergence of cloud computing technology has motivated a very high number of users in different organizations to access its services in running and delivering their various operations and services. However, this surge of cloud users has led to the problem of uneven load sharing among the cloud computing infrastructures. As a result, federated cloud infrastructure was initiated to provide more cloud computing resources to accommodate more cloud users’ requests and also to provide equal requests mapping with the available cloud resources. Nevertheless, the issue of unequal allocation of requests within the datacenter(s) that makes up the federated cloud environment still persists. This research work presents an intra-datacenter load balancing algorithm in a federated cloud environment named; the intra-balancer adapted throttled algorithm to evenly distribute requests in each datacenter that formulate the federated cloud infrastructures. The simulation of the intra-balancer was carried out in CloudAnalyst, the results of the implementation showed that the intra-balancer outperformed the Round-Robin and ESCE with 98.93ms and 2.26ms for the response and processing time respectively. The results assert that the intra-balancer algorithm provides a better load balancing solution in a federated cloud environment.

关键词： computers Cloud computing Organizations Load management Resource management Time factors Task analysis

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Zero Trust Management Over Consumer Technology Based IoT Edge Node for SDN communication and Control of Cyber-Physical systems

引用

IEEE Transactions on Consumer Electronics 2025年

作者： Byeon, Haewon Alsaadi, Mahmood Gupta, Sachin Patni, Jagdish Chandra Ahanger, Tariq Ahamed Singh, Brajesh Kumar Srivastava, Ajeet Kumar Abdinabievna, Pardaeva Shakhnoza Boddupalli, Santhosh Korea University of Technology and Education Convergence Department Cheonan Korea Republic of University of Al Maarif College of Sciences Department of Computer Sciences Al Anbar31001 Iraq Maharaja Agrasen Institute of Technology Department of CSE Delhi India Alliance University Bengaluru Dept. of CSE Alliance School of Advance Computing Karnataka India CoBA Prince Sattam Bin Abdulaziz University Department of Management Information Systems Saudi Arabia Galgotia College of Engineering and Technology Department of Electronics and Communication Engineering Greater Noida India Chhatrapati Shahu Ji Maharaj University Department of ECE school of engineering and technology Kanpur India Tashkent State University of Economics The department of Bank Accounting and Audit Tashkent Uzbekistan Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Telangana Hyderabad500075 India

In response to the lack of effective means for detecting and locating malicious exchange nodes in data flow transmission links within the Internet of Things (IoT), this paper proposes a zero-trust management method for data flow between edge nodes based on software defined networking (SDN) communication and control of cyber-physical systems (CPS). To detect and prevent anomalous behaviors like data tampering, forwarding path anomalies, and malicious packet drops through forwarding verification by exchange nodes, SDN-ZTM applies SDN to the data transmission process between IoT edge nodes. This approach applies the SDN architecture to the transmission process of data flows between edge nodes, utilizing a fixed-length header overhead for zero-trust management of data flows, nodes, and paths, thereby enabling lightweight packet forwarding verification and malicious exchange node localization. Simulation studies and theoretical research show that SDN-ZTM offers more extensive security features than similar methods. Additionally, SDN-ZTM is a lightweight, useful solution appropriate for IoT application scenarios since it introduces a fixed-length header and has a smaller performance overhead. Experimental results show that the method introduces less than 10% forwarding delay and less than 8% throughput loss. © 1975-2011 IEEE.

关键词： Cybersecurity

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V-Edge: Virtual edge computing as an enabler for novel microservices and cooperative computing

arXiv

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arXiv 2021年

作者： Dressler, Falko Chiasserini, Carla Fabiana Fitzek, Frank H.P. Karl, Holger Cigno, Renato Lo Capone, Antonio Casetti, Claudio Malandrino, Francesco Mancuso, Vincenzo Klingler, Florian Rizzo, Gianluca The School of Electrical Engineering and Computer Science TU Berlin Berlin Germany The Dept. of Electronics and Telecommunications Politecnico di Torino Torino Italy The School of Engineering Sciences as well as the Excellence Cluster CeTI TU Dresden Dresden Germany The Hasso-Plattner-Institute Potsdam Germany The Dept. of Information Engineering University of Brescia Brescia Italy The Dept. of Electronics Information and Bioengineering Politecnico di Milano Milano Italy The Dept. of Control and Computer Engineering Politecnico di Torino Torino Italy The Institute of Electronics Computer and Communication Engineering of the National Research Council of Italy Torino Italy IMDEA Networks Madrid Spain The Dept. of Computer Science Paderborn University Paderborn Germany The Research Institute of Information Systems HES-SO Valais-Wallis Switzerland University of Foggia Italy

As we move from 5G to 6G, edge computing is one of the concepts that needs revisiting. Its core idea is still intriguing: instead of sending all data and tasks from an end user's device to the cloud, possibly covering thousands of kilometers and introducing delays that are just owed to limited propagation speed, edge servers deployed in close proximity to the user, e.g., at some 5G gNB, serve as proxy for the cloud. Yet this promising idea is hampered by the limited availability of such edge servers. In this paper, we discuss a way forward, namely the virtual edge computing (V-Edge) concept. V-Edge bridges the gap between cloud, edge, and fog by virtualizing all available resources including the end users' devices and making these resources widely available using well-defined interfaces. V-Edge also acts as an enabler for novel microservices as well as cooperative computing solutions. We introduce the general V-Edge architecture and we characterize some of the key research challenges to overcome, in order to enable wide-spread and even more powerful edge services. Copyright © 2021, The Authors. All rights reserved.

关键词： Edge computing

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Computational Approaches to Explainable Artificial Intelligence: Advances Intheory, Applications and Trends

SSRN

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SSRN 2023年

作者： Górriz, Juan Manuel Álvarez-Illán, I. Álvarez-Marquina, A. Arco, J.E. Atzmueller, M. Ballarini, F. Barakova, E. Bologna, G. Bonomini, P. Castellanos-Dominguez, G. Castillo-Barnes, D. Cho, S.B. Contreras, R. Cuadra, J.M. Domínguez, E. Domínguez-Mateos, F. Duro, R.J. Elizondo, D. Fernández-Caballero, A. Fernandez-Jover, E. Formoso, M.A. Gallego-Molina, N.J. Gamazo, J. García González, J. Garcia-Rodriguez, J. Garre, C. Garrigós, J. Gómez-Rodellar, A. Gómez-Vilda, P. Graña, M. Guerrero-Rodriguez, B. Hendrikse, S.C.F. Jimenez-Mesa, C. Jodra-Chuan, M. Julian, V. Kotz, G. Kutt, K. Leming, M. de Lope, J. Macas, B. Marrero-Aguiar, V. Martinez, J.J. Martinez-Murcia, F.J. Martínez-Tomás, R. Mekyska, J. Nalepa, G.J. Novais, P. Orellana, D. Ortiz, A. Palacios-Alonso, D. Palma, J. Pereira, A. Pinacho-Davidson, P. Pinninghoff, M.A. Ponticorvo, M. Psarrou, A. Ramírez, J. Rincón, M. Rodellar-Biarge, V. Rodríguez-Rodríguez, I. Roelofsma, P.H.M.P. Santos, J. Salas-Gonzalez, D. Salcedo-Lagos, P. Segovia, F. Shoeibi, A. Silva, M. Simic, D. Suckling, J. Treur, J. Tsanas, A. Varela, R. Wang, S.H. Wang, W. Zhang, Y.D. Zhu, H. Zhu, Z. Ferrández-Vicente, J.M. SiPBA at Data Science and Computational Intelligence Institute University of Granada Granada Spain University of Granada Granada Spain Dept. of Psychiatry University of Cambridge Cambridge United Kingdom Dept. of Communications Engineering University of Malaga Malaga Spain School of Computing and Mathematical Sciences University of Leicester Leicester United Kingdom Semantic Information Systems Group Osnabrück University Osnabrück Germany Osnabrück Germany Dept. of Electronics Computer Technology and Projects Universidad Politécnica de Cartagena Cartagena Spain Universitat Politècnica de València València Spain Institute of Applied Computer Science Jagiellonian University Kraków Poland Dept. of Information and Communication Engineering University of Murcia Murcia Spain Dept. of Computer Science and Information Technologies University of A Coruña A Coruña Spain Dept. of Computer Science University of Oviedo Oviedo Spain Buenos Aires Argentina Buenos Aires Argentina Eindhoven University of Technology Eindhoven5612 AZ Netherlands Dept. of Computer Science University of Malaga Malaga Spain De Montfort University Leicester United Kingdom Dept. of Computer Science Faculty of Engineering Universidad de Concepción Concepción Chile Neurocognition and Emotion Research Unit Albacete Research Institute of Informatics University of Castilla-La Mancha Albacete Spain Dept. of Educational Informatics Universidad de Concepción Concepción Chile Madrid Spain Dept. of Humanistic Studies University of Naples Federico II Napoli Italy Escuela Técnica Superior de Ingeniería Informática Universidad Rey Juan Carlos Campus de Móstoles Móstoles Madrid28933 Spain Neuromorphic Speech Processing Lab Center for Biomedical Technology Universidad Politécnica de Madrid Campus de Montegancedo Pozuelo de Alarcón Madrid28223 Spain Biomedical Research Networking Center in Mental Health Instituto de Salud Carlos III Madrid28016 Spain Usher Institute Faculty o

Groundbreaking advances in theoretical and applied Artificial Intelligence (AI). DL algorithms are groundedin non-linear and complex artificial neural systems that progressively extract higher-level features from *** is frequently compared with human-level performance in real-world tasks, such as clinical diagnostics. Itis also a turning point in solving otherwise intractable problems in the design of virtual agents or robotics;orin providing novel insight into disease progress in genomics and Neuroimaging (NI), understanding humanbrain function, the automation of industrial processes based on computer vision, and so on. In this paper, themost relevant advances from the last few years in AI and several applications to neuroscience, neuroimaging,computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-ofthe-art in AI methods, models and applications within a collection of works presented at the 9th InternationalConference on the Interplay between Natural and Artificial Computation (IWINAC). The works presentedin this paper are excellent examples of new scientific discoveries made in laboratories that are successfullytransferred to real-life applications. © 2023, The Authors. All rights reserved.

关键词： Neuroimaging

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