检索结果-内蒙古大学图书馆

Deep Learning Based Side-Channel Attack Detection for Mobile Devices Security in 5G Networks

清华大学学报自然科学版（英文版） 2025年第3期30卷 1012-1026页

作者： Amjed A.Ahmed Mohammad Kamrul Hasan Ali Alqahtani Shayla Islam Bishwajeet Pandey Leila Rzayeva Huda Saleh Abbas Azana Hafizah Mohd Aman Nayef Alqahtani Center for Cyber Security Faculty of Information Science and TechnologyUniversiti Kebangsaan MalaysiaBangi 43600Malaysia Imam Alkadhim University College Department of Computer Techniques EngineeringBaghdad 10066Iraq Center for Cyber Security Faculty of Information Science and TechnologyUniversiti Kebangsaan MalaysiaBangi 43600Malaysia Department of Networks and Communications Engineering College of Computer Science and Information SystemsNajran UniversityNajran 61441Saudi Arabia Institute of Computer Science and Digital Innovation UCSI UniversityKuala Lumpur 56000Malaysia Department of Intelligent Systems and Cyber Security Astana IT UniversityAstana 20000Kazakstan Department of Computer Science College of Computer Science and EngineeringTaibah UniversityMadinah 42353Saudi Arabia Department of Electrical Engineering College of EngineeringKing Faisal UniversityAl-Hofuf 31982Saudi Arabia

Mobile devices within Fifth Generation(5G)networks,typically equipped with Android systems,serve as a bridge to connect digital gadgets such as global positioning system,mobile devices,and wireless routers,which are vital in facilitating end-user communication ***,the security of Android systems has been challenged by the sensitive data involved,leading to vulnerabilities in mobile devices used in 5G *** vulnerabilities expose mobile devices to cyber-attacks,primarily resulting from security ***-permission apps in Android can exploit these channels to access sensitive information,including user identities,login credentials,and geolocation *** such attack leverages"zero-permission"sensors like accelerometers and gyroscopes,enabling attackers to gather information about the smartphone's *** underscores the importance of fortifying mobile devices against potential future *** research focuses on a new recurrent neural network prediction model,which has proved highly effective for detecting side-channel attacks in mobile devices in 5G *** conducted state-of-the-art comparative studies to validate our experimental *** results demonstrate that even a small amount of training data can accurately recognize 37.5％of previously unseen user-typed ***,our tap detection mechanism achieves a 92％accuracy rate,a crucial factor for text *** findings have significant practical implications,as they reinforce mobile device security in 5G networks,enhancing user privacy,and data protection.

关键词： Fifth Generation(5G)networks smartphone information leakage Side-Channel Attack(SCA) deep learning

来源：评论

学校读者我要写书评

暂无评论

Combination of Interleaved Single-input Multiple-output DC-DC Converters

引用

CSEE Journal of Power and Energy systems 2022年第1期8卷 132-142页

作者： Eladio Dur´an Aranda Salvador P´erez Litr´an Mar´ıa Bella Ferrera Prieto Electronic Engineering Computer Systems and Automation DepartmentUniversity of HuelvaHuelvaSpain Electrical and Thermal Engineering Design and Projects DepartmentUniversity of HuelvaHuelvaSpain

This paper analyses,simulates and verifies an experimental prototype of a four-phase interleaved DC-DC *** is based on a SEPIC-Cuk *** developed prototype has been used in single-input multiple-output(SIMO)*** combined converter allows obtaining dual output voltages of the same value,from a single input DC voltage and with only a power *** interleaved DC-DC converters achieve a better dynamic response and low ripple,maintaining their *** converter is connected in parallel,thereby managing their losses by distributing them between more components,which facilitates the thermal management of the multiphase converter and allows handling high power values in small sizes with respect to solutions for a single *** control strategies were applied:synchronous operation mode(SOM)and interleaved operation mode(IOM).The simulation results allow the comparison of both operational modes,verifying that the IOM presents advantages with respect to the ripple at the input and output *** experimental prototype was designed for a distributed power architecture and bipolar DC microgrid(MG).

关键词： Bipolar DC DC-DC converter interleaved

来源：评论

学校读者我要写书评

暂无评论

Enhanced PTE and Throughput in Wireless Capacitive Power and Data Transfer via Biocompatible Dielectric Shielding 46

Enhanced PTE and Throughput in Wireless Capacitive Power and...

引用

46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Hossain, A. N. M. Shahriyar Mohseni, Pedram Lavasani, H.M. Case Western Reserve University Department of Electrical Computer and Systems Engineering ClevelandOH United States

ISBN: (纸本)9798350371499

This study explores the use of biocompatible dielectric shielding to enhance the power transfer efficiency (PTE) and improve the data rates in capacitive links designed for biomedical applications. A dielectric shielding structure that surrounds the capacitive patches on all sides except the main signal path is used to minimize the energy leakage, ensuring high PTE and improved signal-to-noise ratio (SNR). Ex vivo measurements align well with the simulations, showing maximum PTE > 74% for the capacitive link. The link is also capable of supporting data transfer rate exceeding 10 Mbps using a quadrature phase shift keying modulation (QPSK) scheme. These performance metrics represent the highest reported values among tuned capacitive links intended for implantable medical devices. © 2024 IEEE.

关键词： Quadrature phase shift keying

来源：评论

学校读者我要写书评

暂无评论

Deep Learning for Fault Detection of Digital VLSI Circuits 21

Deep Learning for Fault Detection of Digital VLSI Circuits

引用

21st International Learning and Technology Conference, L and T 2024

作者： Gaber, Lamya Hussein, Aziza I. Minia University Computers and Systems Engineering Department Minia Egypt Effat University Electrical and Computer Engineering Department Jeddah Saudi Arabia

ISBN: (纸本)9798350393569

With the increasing complexity and scale of digital VLSI designs, ensuring reliability in IC design necessitates effective fault detection processes during the pre-silicon stage. Many fault detection algorithms lead to significant computational time due to the problem of search space explosion. To handle the ever-growing volume of data, deep learning algorithms, a subset of machine learning techniques, can be employed. In this paper, we propose two novel approaches for fault detection (FD) of digital VLSI circuits, specifically targeting stuck-at faults. The first proposed model is semi-supervised FD model that aims to mitigate the search space explosion issue by leveraging both unsupervised and supervised learning processes. The second presented model is based on an optimizer for finding the appropriate configurations for detecting stuck-at faults in digital circuits. The initial proposed model achieves maximum validation accuracy of approximately 98% applied to circuits from ISCAS'85. This model yields a higher accuracy compared to the second approach that achieves maximum accuracy of around 95% when applied to the same circuits from the ISCAS'85 benchmark. © 2024 IEEE.

关键词： Fault detection

来源：评论

学校读者我要写书评

暂无评论

Fault-tolerant visual servo control for a robotic arm with actuator faults

引用

Neural Computing and Applications 2024年第25期36卷 15815-15828页

作者： Li, Jiashuai Peng, Xiuyan Li, Bing Sreeram, Victor Wu, Jiawei College of Intelligent Systems Science and Engineering Harbin Engineering University Heilongjiang Nantong Harbin150001 China Department of Electrical Electronic and Computer Engineering The University of Western Australia Stirling Highway PerthWA6009 Australia

The study targets uncertain coupling faults in robotic arm actuators and proposes a new fault-tolerant visual servo control strategy. Specifically, it considers both multiplicative and additive actuator faults within the dynamic of the robotic arm, treating the coupling faults and time-varying disturbances as an aggregate of concentrated uncertainties. A radial basis function neural network-based state observer is introduced to online approximate these concentrated uncertainties, which include fault information, eliminating the need for prior knowledge of faults. Furthermore, a fault-tolerant controller based on a non-singular fast terminal sliding mode is proposed, which separately decouples the nominal quantities and concentrated uncertainties and develops individual adaptive control laws for each. This effectively reduces the detrimental impact of coupled faults and disturbances on the system’s performance, facilitating image feature trajectory tracking control with minimal jitter, high precision, and strong transient response capabilities. The stability of the state observer and the fault-tolerant controller has been substantiated through Lyapunov’s theory. Lastly, numerical simulations validate the efficacy and robustness of the proposed fault-tolerant visual servo control approach. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Robotic arms

来源：评论

学校读者我要写书评

暂无评论

Developing Multi-Agent Wide Area Damping Controller to Mitigate False Data Injection Attacks 24

Developing Multi-Agent Wide Area Damping Controller to Mitig...

引用

24th EEEIC International Conference on Environment and electrical engineering and 8th I and CPS Industrial and Commercial Power systems Europe, EEEIC/I and CPS Europe 2024

作者： Vavdareh, Masoud Babaei Ghafouri, Mohsen Ameli, Amir Concordia University Department of Information and Systems Engineering Montreal Canada Lakehead University Department of Electrical and Computer Engineering Thunder BayON Canada

ISBN: (纸本)9798350355185

The effectiveness of wide-area damping controllers (WADCs) is significantly influenced by the integrity of the measurement data collected from phasor measurement units (PMUs). These damping controllers utilize PMU data to make decisions and transmit control commands to system actuators, such as synchronous generators. However, the incorporation of communication links for transmitting these signals exposes the power system to various cyber threats, such as false data injection attacks (FDIAs). On this basis, this study proposes two methods for defending against FDIAs: (i) the utilization of a neural network-based autoencoder as an effective attack detector for FDIAs, and (ii) the development of a multi-agent control strategy to mitigate these attacks. The performance of these proposed methods is analyzied using a two-area Kundur test system, compared against conventional data-driven attack detection methods and a global WADC technique. The findings indicate that the implementation of these methods significantly enhances defense capabilities against FDIA targeting wide-area measurement signals. © 2024 IEEE.

关键词： Phasor measurement units

来源：评论

学校读者我要写书评

暂无评论

Classifying Bicycle Infrastructure Using On-Bike Street-Level Images 27

Classifying Bicycle Infrastructure Using On-Bike Street-Leve...

引用

27th IEEE International Conference on Intelligent Transportation systems, ITSC 2024

作者： Backman, Kal Beck, Ben Kulic, Dana School of Public Health and Preventive Medicine Monash University Department of Electrical and Computer Systems Engineering Australia

ISBN: (纸本)9798331505929

While cycling offers an attractive option for sus-tainable transportation, many potential cyclists are discouraged from taking up cycling due to the lack of suitable and safe infrastructure. Efficiently mapping cycling infrastructure across entire cities is necessary to advance our understanding of how to provide connected networks of high-quality infrastructure. Therefore we propose a system capable of classifying available cycling infrastructure from on-bike smartphone camera data. The system receives an image sequence as input, temporally analyzing the sequence to account for sparsity of signage. The model outputs cycling infrastructure class labels defined by a hi-erarchical classification system. Data is collected via participant cyclists covering 7,006Km across the Greater Melbourne region that is automatically labeled via a GPS and OpenStreetMap database matching algorithm. The proposed model achieved an accuracy of 95.38%, an increase in performance of 7.55% compared to the non-temporal model. The model demonstrated robustness to extreme absence of image features where the model lost only 6.6% in accuracy after 90% of images being replaced with blank images. This work is the first to classify cycling infrastructure using only street-level imagery collected from bike-mounted mobile phone cameras, while demonstrating robustness to feature sparsity via long temporal sequence analysis. © 2024 IEEE.

关键词： Bicycles

来源：评论

学校读者我要写书评

暂无评论

Speed Harmonic based Saturation Free Inductance Modeling and Estimation of Interior PMSM Using Measurements Under One Load Condition

引用

CES Transactions on electrical Machines and systems 2025年第1期9卷 91-99页

作者： Guodong Feng Yuting Lu Zhe Tong Beichen Ding Guishan Yan Chunyan Lai the School of Intelligent Systems Engineering Sun Yat-sen UniversityShenzhenChina the School of Advanced Manufacturing Sun Yat-sen University the Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) China the Department of Electrical and Computer Engineering Concordia UniversityQCCanada

For permanent magnet synchronous machines(PMSMs),accurate inductance is critical for control design and condition *** to magnetic saturation,existing methods require nonlinear saturation model and measurements from multiple load/current conditions,and the estimation is relying on the accuracy of saturation model and other machine parameters in the *** harmonic produced by harmonic currents is inductance-dependent,and thus this paper explores the use of magnitude and phase angle of the speed harmonic for accurate inductance *** estimation models are built based on either the magnitude or phase angle,and the inductances can be from d-axis voltage and the magnitude or phase angle,in which the filter influence in harmonic extraction is considered to ensure the estimation *** inductances can be estimated from the measurements under one load condition,which is free of saturation ***,the inductance estimation is robust to the change of other machine *** proposed approach can effectively improve estimation accuracy especially under the condition with low current *** and comparisons are conducted on a test PMSM to validate the proposed approach.

关键词： PMSM Inductance estimation Speed harmonic High frequency signal injection

来源：评论

学校读者我要写书评

暂无评论

Dynamical Casimir effects: The need for nonlocality in time-varying dispersive nanophotonics

引用

Physical Review A 2024年第4期110卷 L041502页

作者： S. Ali Hassani Gangaraj George W. Hanson Francesco Monticone Optical Physics Division Department of Electrical Engineering School of Electrical and Computer Engineering

We study the role of material nonlocality (spatial dispersion) in dynamical Casimir effects in time-varying frequency-dispersive nanophotonic systems. We first show that local models may lead to nonphysical predictions, such as diverging emission rates of entangled polariton pairs. We then theoretically demonstrate that nonlocality regularizes this behavior by correcting the asymptotic response of the system for large wave vectors and leads to physical effects missed by local models, including a significant broadening of the emission rate distribution, which are relevant for future experimental observations. Our work sheds light on the importance of nonlocal effects in this new frontier of nanophotonics.

关键词： Casimir effect & related phenomena Nanophotonics Quantum optics

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Applications for Online Partial Discharge Detection, Classification, and Localization in Power Transformers: A Review 4

Machine Learning Applications for Online Partial Discharge D...

引用

4th International Conference on Smart Grid and Renewable Energy, SGRE 2024

作者： Tag, Ameera Refaat, Shady S. Kameli, Sayed Mohammad Saleh, Mohammad Alshaikh Texas A&M University at Qatar Electrical and Computer Engineering Department Doha Qatar University of Hertfordshire School of Physics Engineering and Computer Science Department of Engineering United Kingdom Texas A&M University Department of Electrical and Computer Engineering College Station United States

ISBN: (纸本)9798350306262

The power transformer is a crucial asset and a fundamental component of the power grid. Assets undergo aging due to the stresses present in insulation materials. Partial discharges (PDs) are the most common fault source in power transformers and an excellent indicator of aging. The detection, classification, and localization of PD activities in power transformers are persisting challenges, while techniques utilizing machine learning (ML) are widely sought to deal with those challenges. Existing ML techniques show promising results with an elevated level of accuracy and precision. However, there is a lack of conventional ML-based real-time monitoring capability. Therefore, this paper presents a comprehensive review of the application of ML techniques for online PD activity detection, classification, and localization in power transformers, focusing on supervised, unsupervised, semi-supervised, and reinforcement learning techniques. In addition, this paper explores the challenges, future trends, perspectives, and outlook of machine learning for online transformer fault analysis. © 2024 IEEE.

关键词： Partial discharges

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：