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Navigating IoT Security:Insights into Architecture,Key Security Features,Attacks,Current Challenges and AI-Driven Solutions Shaping the Future of Connectivity

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computers, Materials & Continua 2024年第12期81卷 3499-3559页

作者： Ali Hassan N.Nizam-Uddin Asim Quddus Syed Rizwan Hassan Ateeq Ur Rehman Salil Bharany Department of Electrical Engineering HITEC UniversityTaxila47080Pakistan Department of Biomedical Engineering HITEC UniversityTaxila47080Pakistan Department of Electronics Engineering University of ChakwalChakwal48800Pakistan Department of Computer Science NFC Institute of Engineering and Fertilizer ResearchFaisalabad38000Pakistan School of Computing Gachon UniversitySeongnam-si13120Republic of Korea Chitkara University Institute of Engineering and Technology Chitkara UniversityRajpura140401PunjabIndia

Enhancing the interconnection of devices and systems,the Internet of Things(IoT)is a paradigm-shifting *** security concerns are still a substantial concern despite its extraordinary *** paper offers an extensive review of IoT security,emphasizing the technology’s architecture,important security elements,and common *** highlights how important artificial intelligence(AI)is to bolstering IoT security,especially when it comes to addressing risks at different IoT architecture *** systematically examined current mitigation strategies and their effectiveness,highlighting contemporary challenges with practical solutions and case studies from a range of industries,such as healthcare,smart homes,and industrial *** results highlight the importance of AI methods that are lightweight and improve security without compromising the limited resources of devices and computational *** networks can ensure operational efficiency and resilience by proactively identifying and countering security risks by utilizing machine learning *** study provides a comprehensive guide for practitioners and researchers aiming to understand the intricate connection between IoT,security challenges,and AI-driven solutions.

关键词： Internet of Things(IoT) artificial intelligence(AI) IoT architecture security attacks in IoT

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Integrating the Internet of Things to Protect Electric Vehicle Control Systems from Cyber Attacks

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IAENG International Journal of Applied Mathematics 2024年第3期54卷 433-440页

作者： Bhukya, Baddu Naik Venkataiah, V. Kuchibhatla, S. Mani Koteswari, S. Kumari, R.V.S. Lakshmi Raju, Yallapragada Ravi Department of Electrical and Electronics Engineering Prasad V. Potluri Siddhartha Institute of Technology Andhra Pradesh Vijayawada India Department of Computer Science Engineering CMR College of Engineering & Technology Telangana Hyderabad India Department of Electrical and Electronics Engineering ACE Engineering College Telangana Hyderabad India Department of Electronics and Communication Engineering Pragati Engineering College Kakinada India Andhra Pradesh Surampalem India Department of Electrical and Electronics Engineering Gayatri Vidya Parishad College of Engineering for Women Andhra Pradesh Visakhapatnam India Department of Computer Science and Technology Madanapalle Institute of Technology and Science Andhra Pradesh India

The Internet of Things (IoT) facilitates the delivery of intelligent services by sensing, gathering, processing, and exchanging data from millions of linked smart devices. The Internet of Things (IoT), which is based on communication infrastructure, provides real-time cyber-physical device monitoring, control, and sensing, such as electric autos. Traditional communication infrastructure's vulnerability to cyberattacks hampered IoT's capacity to investigate these potential applications. This study proposes an algorithm for monitoring and controlling electric vehicles through the Internet of Things communication network to prevent fake data injection attacks. A state-space model depicts a fully autonomous electric car equipped with a vision system. Intelligent sensors and actuators from the Internet of Things are utilized to monitor and change system conditions, compensating for the large distance between the electric car and the control center. Sensing data is delivered from the vehicle to the central command center via an insecure, attack-prone communication path. The mean square error approach is used to derive states in the most effective state estimation system for comprehending and showing autos. A semi-definite programming approach is used to create an optimal control algorithm to manage the vehicle states. The simulation results show how precisely and successfully the proposed algorithms can foresee and regulate a vehicle's state. © (2024), (International Association of Engineers). All Rights Reserved.

关键词： Internet of things

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W-Shaped Eight-Port Wideband MIMO Antenna

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Progress In Electromagnetics Research C 2023年 134卷 211-222页

作者： Naser, Hussein Mohammed Al-Ani, Oras A. Mosleh, Mahmood F. Department of Computer Engineering Techniques Electrical Engineering Technical College Middle Technical University Baghdad Iraq

The main challenges of designing an antenna for modern wireless communication are size reduction and mutual coupling. An ultra-wideband (UWB) multiple input multiple outputs (MIMO) antennae with four elements is suggested by this paper. Each element has two ports with dual-polarized patches to reduce the result of reciprocal coupling, increase the capacity, and keep a proper size. A circular geometric shape is in front of the patch of the proposed antenna to reduce the impact of mutual coupling. The CST STUDIO 2019 program simulates the single antenna element and MIMO antenna using four integrated elements, eight integrated ports, and an Fr-4 insulating layer in an area of (70 × 70) mm2. The MIMO antenna’s operating frequency, which has a band of 2.85 (3.15–6) GHz at −10 dB, is 3.67 GHz while the operating frequency of a single antenna element, which has a band of 2.8 (3.1–5.9) GHz at −10 dB and a resonance return loss of 36 dB, is 3.64 GHz. The MIMO antennas obtained a diversity gain (DG) of about 10 with a good gain of about 8 dB while the envelope correlation coefficient (ECC) was equal to or less than 0.0001. © 2023, Electromagnetics Academy. All rights reserved.

关键词： Slot antennas

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Reinforcement Learning-based Receding Horizon Control using Adaptive Control Barrier Functions for Safety-Critical Systems 63

Reinforcement Learning-based Receding Horizon Control using ...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Sabouni, Ehsan Sabbir Ahmad, H.M. Giammarino, Vittorio Cassandras, Christos G. Paschalidis, Ioannis Ch. Li, Wenchao Boston University Division of Systems Engineering BostonMA02215 United States Boston University Department of Electrical and Computer Engineering The Division of Systems Engineering BostonMA02215 United States Boston University Department of Electrical and Computer Engineering Division of Systems Engineering Department of Biomedical Engineering BostonMA02215 United States

ISBN: (纸本)9798350316339

Optimal control methods provide solutions to safety-critical problems but easily become intractable. Control Barrier Functions (CBFs) have emerged as a popular technique that facilitates their solution by provably guaranteeing safety, through their forward invariance property, at the expense of some performance loss. This approach involves defining a performance objective alongside CBF-based safety constraints that must always be enforced with both performance and solution feasibility significantly impacted by two key factors: (i) the selection of the cost function and associated parameters, and (ii) the calibration of parameters within the CBF-based constraints, which capture the trade-off between performance and conservativeness. To address these challenges, we propose a Reinforcement Learning (RL)-based Receding Horizon Control (RHC) approach leveraging Model Predictive Control (MPC) with CBFs (MPC-CBF). In particular, we parameterize our controller and use bilevel optimization, where RL is used to learn the optimal parameters while MPC computes the optimal control input. We validate our method by applying it to the challenging automated merging control problem for Connected and Automated Vehicles (CAVs) at conflicting roadways. Results demonstrate improved performance and a significant reduction in the number of infeasible cases compared to traditional heuristic approaches used for tuning CBF-based controllers, showcasing the effectiveness of the proposed method. In order to guarantee reproducibility, our code is provided here: ***/EhsanSabouni/CDC2024_RL_adpative_MPC_CBF/tree/main © 2024 IEEE.

关键词： Adaptive control systems

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engineering Quantum Dots: Overcoming Challenges in Telecommunications and Human-Machine Interaction 22

Engineering Quantum Dots: Overcoming Challenges in Telecommu...

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22nd International Learning and Technology Conference, L and T 2025

作者： Majid, M.A. Effat University College of Engineering Electrical and Computer Engineering Department Saudi Arabia

ISBN: (纸本)9798331532215

engineering the inhomogeneity, density, composition, and aspect ratio of self-assembled quantum dots (SAQDs) is essential for various applications, from broadband technologies to telecommunications. This paper investigates the optimization of molecular beam epitaxy (MBE) grown quantum dots in the intrinsic region of optoelectronic devices, such as lasers, highlighting the need for tailored approaches based on specific applications. For instance, superluminescent diodes used for imaging require highly inhomogeneous dots, while inhomogeneity can pose challenges for SAQD lasers in telecommunications, as non-homogeneous QDs may become parasitic and hinder lasing efficiency. This study explores quantum dot lasers by adjusting the thickness of the GaAs spacer layers, which are grown at low temperatures and situated between the dot layers. Our findings reveal enhanced performance in SAQD laser structures, achieving "no blue shift"in peak emission wavelengths - critical for human-machine interaction and photonic integrated circuit applications. Maintaining stable emission wavelengths significantly boosts the efficiency of communication systems and quantum computing platforms, facilitating rapid data processing and interaction between machines and users. © 2025 IEEE.

关键词： Quantum dot lasers

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Enhancing voltage stability and load shedding optimization through a fusion of gravitational search algorithm and particle swarm optimization with deep learning

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Soft Computing 2025年第2期29卷 701-721页

作者： Ahmadipour, Masoud Ali, Zaipatimah Ridha, Hussein Mohammed School of Electrical Engineering College of Engineering Universiti Teknologi MARA Selangor Shah Alam40450 Malaysia Selangor Kajang43000 Malaysia Department of Computer Engineering University of Al-Mustansiriyah Baghdad14022 Iraq Department of Electrical and Electronic Engineering Faculty of Engineering Universiti Putra Malaysia Selangor Serdang43400 Malaysia

In this research, A novel approach for optimizing load shedding during power system stress conditions is introduced by combining gravitational search and particle swarm optimization (GSA-PSO) with Deep Learning. This approach aims to determine the most effective load-shedding strategy for specific buses, to prevent revenue loss and voltage instability in power systems. The smallest eigenvalue sensitivity of the load flow Jacobian matrix as an indicator is used to identify the buses for load shedding. Furthermore, inequality constraints are calculated for the current operational state and the anticipated load in the next interval. To evaluate the performance of the proposed approach, experiments were conducted on two different power systems: the IEEE 30-bus and 14-bus systems. The GSAPSO-Deep Learning approach was implemented in the Python environment. The results obtained using the proposed method were compared with those of other models, as well as their variants, using statistical inference. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Eigenvalues and eigenfunctions

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SMART: Self-Morphing Adaptive Replanning Tree

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IEEE Robotics and Automation Letters 2023年第11期8卷 7312-7319页

作者： Shen, Zongyuan Wilson, James P. Gupta, Shalabh Harvey, Ryan University of Connecticut School of Engineering Department of Electrical and Computer Engineering StorrsCT06269 United States

The letter presents an algorithm, called Self-Morphing Adaptive Replanning Tree (SMART), that facilitates fast replanning in dynamic environments. SMART performs risk-based tree-pruning if the current path is obstructed by nearby moving obstacle(s), resulting in multiple disjoint subtrees. Then, for speedy recovery, it exploits these subtrees and performs informed tree-repair at hot-spots that lie at the intersection of subtrees to find a new path. The performance of SMART is comparatively evaluated with eight existing algorithms through extensive simulations. Two scenarios are considered with: 1) dynamic obstacles and 2) both static and dynamic obstacles. The results show that SMART yields significant improvements in replanning time, success rate, and travel time. Finally, the performance of SMART is validated by a real laboratory experiment. © 2016 IEEE.

关键词： Real time systems

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A machining center selection study using neural networks

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Neural Computing and Applications 2025年 1-38页

作者： Ic, Yusuf Tansel Yıldız, Burak Kececi, Barış Sert, Mustafa Department of Industrial Engineering Baskent University Ankara06970 Turkey Department of Computer Engineering Baskent University Ankara06970 Turkey Department of Electrical Engineering and Computer Science University of California IrvineCA92697 United States

Machining centers (MCs) are crucial high-technology machine tools that are widely used in the manufacturing industry. Since their high investment necessities, the selection of the appropriate MC for a company is an important task so that the company’s competitive advantages can be continued in the future. In the literature, there are many studies for MC selection using multi-criteria decision-making (MCDM) models and their fuzzy versions. This type of selection model must use selection criteria weighting procedures that are mainly based on subjective preferences. On the other hand, some attempts are provided in the literature to set objective decision-making models, such as the design of an experiment (DoE)-based Technique for Order Preferences by Similarity to the Ideal Solution (TOPSIS) model. In this study, we improved the DoE-based TOPSIS approach using neural network-based solutions and compared their capability of the MC selection studies against the classical MCDM and DoE-TOPSIS models. The proposed model can handle the newly generated scenarios using the Neural Networks. The feedforward neural network (FFNN)-based model utilizes machine learning techniques to overcome some of the challenges by modeling the complex relationships among various decision criteria without relying on human judgment for weighting. As a form of artificial neural network, FFNNs learned from large datasets and captured non-linear patterns, making them well-suited for the MC selection problem. Their capability to process high-dimensional inputs with numerous variables and interactions aligns effectively with the complexities of the MC selection problem. Therefore, the proposed FFNN model is very competitive against the DoE-TOPSIS and classical TOPSIS models. © The Author(s) 2025.

关键词： Cutting

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Robust Iterative Permittivity Inversion with Projection-Based Reduced Order Models

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IEEE Transactions on Antennas and Propagation 2025年第6期73卷 3928-3942页

作者： Shao, Tianchen Jia, Zekui Li, Maokun Xu, Shenheng Yang, Fan Department of Electronic Engineering Beijing100084 China Purdue University Elmore Family School of Electrical and Computer Engineering West LafayetteIN47907 United States

In this paper, we study the application of using reduced order models (ROMs) for permittivity inversion to address the high nonlinearity and cycle-skipping effects in inverse scattering problems (ISPs). In this approach, ROMs are constructed through the Galerkin approximation of wave operators. The ROM-based Data to Born (DtB) process generates Born data and can be incorporated with a back projection (BP) inversion scheme. We implement an iterative BP inversion scheme integrated with the layer-peeling (LP) strategy to ensure stable convergence. Additionally, we incorporate regularization techniques to enhance the algorithm's robustness, especially in noisy environments. The performance of the proposed approach are demonstrated through numerical examples. © 1963-2012 IEEE.

关键词： Permittivity

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Security in smart home environment: issues, challenges, and countermeasures - a survey

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International Journal of Security and Networks 2023年第1期18卷 1-9页

作者： Saad, Redhwan M.A. Al Soufy, Khaled A.M. Shaheen, Samir I. Department of Electrical Engineering Faculty of Engineering Ibb University Ibb70270 Yemen Department of Computer Engineering Faculty of Engineering Cairo University Giza12613 Egypt

The accelerated spread of the IoT and rapid development of modern communication networks and technologies have connected the physical world with computational elements in the smart home environment. The smart home is based on IoT technology which facilitates device observing in order to increase the availability of various tools for securing home automation. Thus, it has been used as a feature of the future wireless sensor network to be able to operate without human intervention. However, it is vulnerable to vulnerabilities and security threats. Due to interconnected, heterogeneous, and dynamic nature of the smart home, challenges related to security, authentication, and confidentiality are created. In this paper attacks on the security of smart homes are investigated to assess their impact on the security of the system as a whole. The technologies and security solutions in such environment are also identified. Therefore, current security measures are discussed to counter such security attacks. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Internet of things

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