检索结果-内蒙古大学图书馆

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

Ship Detection in Satellite Images using You Only Look Once-Neural Architecture Search 9

Ship Detection in Satellite Images using You Only Look Once-...

引用

9th International Conference on Signal Processing and Communication, ICSC 2023

作者： Anand, R.N. Singh, Rimjhim Padam Gupta, Deepa Palaniappan, Kannappan Department of Computer Science Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India Department of Electrical Engineering and Computer Science University of Missouri Missouri United States

ISBN: (纸本)9798350383201

Ship Detection in remotely sensed satellite imagery is a challenging task due to tiny size of the objects and low resolution of the images. Several object detection methods that perform very well for medium-sized and large-sized objects, miserable fail to perform decently in such applications. From the vast variety of the models available, few You only look once (YOLO) have proven to yield decent efficiency and accuracy in ship detection in satellite images. Hence, the paper proposes to detect and classify ships in remotely sensed satellite images by applying transfer learning to fine-tune the latest YOLO-Neural Architecture Search (YOLO-NAS) model. To the best of our knowledge this paper is the first attempt to test YOLO-NAS model for ship detection in satellite imagery. To demonstrate the strength of the YOLO NAS model, the paper also trains YOLOv5 and YOLOv8 on the same dataset allowing to comprehensively compare the efficiency of the proposed model against previous state-of-art versions. The findings demonstrate high mean average precision scores for the proposed model, indicating the effectiveness of the YOLO-NAS algorithm in accurately locating ships in satellite images. © 2023 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

OblivTime: Oblivious and Efficient Interval Skyline Query Processing Over Encrypted Time-Series Data

引用

IEEE Transactions on Services computing 2025年第3期18卷 1602-1617页

作者： Ouyang, Huajie Zheng, Yifeng Wang, Songlei Hua, Zhongyun Harbin Institute of Technology School of Computer Science and Technology Guangdong Shenzhen518055 China The Hong Kong Polytechnic University Department of Electrical and Electronic Engineering Hong Kong Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen518055 China

Time-series data is prevalent in many applications like smart homes, smart grids, and healthcare. And it is now increasingly common to store and query time-series data in the cloud. Despite the benefits, data privacy concerns in such outsourced services are pressing, making it imperative to embed privacy assurance mechanisms from the outset. Most existing related works have been focused on querying for different types of aggregate statistics. In this paper, we instead focus on the secure support for advanced interval skyline queries, which allow to identify time series that are not dominated by any other time series within a query time interval. This is valuable for time-series data analytics in applications like remote health monitoring (e.g., identifying patients with high heart rates in a certain week). We present OblivTime, a new system framework for oblivious and efficient interval skyline query processing over encrypted time-series data. OblivTime is built from a synergy of time-series data analytics, lightweight cryptography, and GPU parallel computing, achieving stronger security guarantees and lower online query latency over the state-of-the-art prior work. Extensive experiments demonstrate that OblivTime can achieve up to 666\times speedup in online query latency over the state-of-the-art prior work. © 2008-2012 IEEE.

关键词： Structured Query Language

来源：评论

学校读者我要写书评

暂无评论

4K Video Coding Efficiency in UAV Systems 45

4K Video Coding Efficiency in UAV Systems

引用

45th Jubilee International Convention on Information, Communication and Electronic Technology, MIPRO 2022

作者： Benjak, J. Hofman, D. Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering Zagreb Croatia

ISBN: (纸本)9789532331035

With increasing requirements for high quality, low bandwidth video transmission systems, comes a demand for more ad hoc video encoders. Unmanned Aerial Vehicles (UAVs), or just drones, have recently grown in popularity and use. Therefore, in this paper, we provide an efficiency comparison of the two most popular video encoders in a First-person view (FPV) drone piloting system. We film all the test sequences ourselves, using a drone with an attached 4K camera. Each sequence captures a scene with different spatiotemporal characteristics. Because video encoders are sensitive to video content or scene complexity, instead of doing a comprehensive comparison of all sequences at once, we first classify all the sequences into four groups. Finally, we examine the compression efficiency by varying the parameters with the highest impact on encoder operation. The quality of compressed footage is determined using four objective video quality measures. Due to high computational complexity, tests were performed on several nodes of a supercomputer and the relative encoding times were also considered. © 2022 Croatian Society MIPRO.

关键词： Antennas

来源：评论

学校读者我要写书评

暂无评论

Enhanced Lightweight Facial Emotion Recognition Systems for Visually Impaired People 12

Enhanced Lightweight Facial Emotion Recognition Systems for ...

引用

12th IEEE Conference on Systems, Process and Control, ICSPC 2024

作者： Shehada, Dina Turky, Ayad Rabie, Tamer Hussain, Abir University of Dubai College of Engineering and IT Dubai United Arab Emirates University of Sharjah College of Engineering Department of Electrical Engineering Sharjah United Arab Emirates University of Sharjah College of Computing & Informatics Department of Computer Science Sharjah United Arab Emirates University of Sharjah College of Computing & Informatics Department of Computer Engineering Sharjah United Arab Emirates

ISBN: (纸本)9798350391398

Facial expressions are a vital component of human communication, conveying emotional information that enhances the social experience. However, for individuals with visual impairments, perceiving and interpreting facial expressions can be challenging, hindering their ability to engage fully in social interactions. This paper presents an enhanced facial emotion recognition system specifically designed to aid visually impaired individuals. Two enhanced approaches for facial emotion recognition systems are proposed. The first approach consolidates negative emotions (anger, fear, sadness, disgust) into a single class, while the second approach incorporates diverse training datasets from real-world environments. The negative emotion consolidation approach achieved 90.9% and 94.7% accuracy on the FER2013 and CK+ datasets, respectively. While, the diverse dataset integration approach achieved 84.9% and 70.6% accuracy on FER2013 and CK+ datasets, respectively. This is a significant improvement when benchmarked with other approaches available in the literature. The feasibility of the enhanced proposed systems as assistive technology for the visually impaired indicated its ability to be applied in real-world applications. © 2024 IEEE.

关键词： Assistive technology

来源：评论

学校读者我要写书评

暂无评论

Blockchain Technology for Land Registry Management in Developing Countries 2

Blockchain Technology for Land Registry Management in Develo...

引用

2nd International Conference on Emerging Trends in electrical, Control, and Telecommunication engineering, ETECTE 2023

作者： Mansoor, Mohammad Abdullah Ali, Mohsin Mateen, Abdul Kaleem, Mohammad Nazir, Sajid COMSATS University Electrical and Computer Engineering Department Islamabad Pakistan Glasgow Caledonian University Department of Computing Glasgow United Kingdom

ISBN: (纸本)9798350305654

Blockchain technology provides a secure framework for dealing with digital assets, conducting financial transactions, and managing property information. The traditional process of land registration often suffers from inefficiency and complexity, primarily due to the involvement of multiple intermediaries, which increases the risk of fraudulent land transfers. In developing countries, property records are often not easily accessible, relevant processes are susceptible to corruption, and have a lengthy turn-around time. This not only leads to disputes over land ownership but hinders the economic activity, such as, disused land, legal complications for agricultural loans and mortgages. By leveraging blockchain technologies, land ownerships can be transparent, supporting accessible and trustworthy land transfers with a reduced risk of fraud and corruption. We propose a blockchain based solution to facilitate access to land documents for verifying land ownership prior to transferring funds from a buyer to the seller. The transparent and unalterable public ledger can thus validate and preserve the land transactions. © 2023 IEEE.

关键词： Smart contract

来源：评论

学校读者我要写书评

暂无评论

Blockchain based Secure Data Management for Healthcare Applications 3

Blockchain based Secure Data Management for Healthcare Appli...

引用

3rd International Conference on Communication, computing and Digital Systems, C-CODE 2023

作者： Khan, Muhammad Zalkifal Nadeem, Maham Kaleem, Mohammad Nazir, Sajid Comsats University Department of Electrical and Computer Engineering Islamabad Pakistan Glasgow Caledonian University Department of Computing Glasgow United Kingdom

ISBN: (纸本)9798350332391

Blockchain technology is poised to transform the data storage and data interchange models. A blockchain is a distributed ledger of transactions stored across a network of nodes. This decentralized model provides immutability and traceability of the records and is known as Distributed Ledger Technology (DLT). In the implemented healthcare system, we used a decentralized blockchain based peer to peer architecture ensuring data security, availability, and reliability. We leverage the Substrate framework, part of Polkadot ecosystem for building blockchains. Once the patient logs into their profile, they are able to view their medical history along with any doctor's prescriptions and laboratory reports. When the doctor accesses a patient's profile, they can make new entries to the medical records and prescriptions. In addition, we show that a tamper-proof record of the healthcare assets can be securely maintained, and accessible to the authorized entities. © 2023 IEEE.

关键词： Distributed ledger

来源：评论

学校读者我要写书评

暂无评论

FacialEmoNet: A Novel Facial Expression Recognition Technique 18

FacialEmoNet: A Novel Facial Expression Recognition Techniqu...

引用

18th INDIAcom;11th International Conference on computing for Sustainable Global Development, INDIACom 2024

作者： Govindarajan, Priya Sadhika, C. Sunil, Gopika Tesfahun, Abebe School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science Mysuru India Debre Markos University School of Electrical and Computer Engineering Debre Markos Institue of Technology Ethiopia

ISBN: (纸本)9789380544519

Facial emotion recognition plays a crucial role in human-computer interaction and artificial intelligence applications, serving as a cornerstone for understanding user emotions. The accurate interpretation of facial expressions is particularly vital in domains such as virtual assistants, human-computer interfaces, and emotion-aware technologies, allowing systems to respond precisely and tailor interactions based on the user's emotional state. In order to overcome challenges associated with conventional approaches, this study introduces the FacialEmoNet technique, an innovative algorithm that seamlessly integrates deep learning and machine learning methods for the efficient classification of facial expression datasets. The primary focus is on capturing and interpreting facial expressions, marking its efficacy and significant advancement in emotion recognition systems. This work investigates the utilization of existing classifiers to classify the dataset effectively. FacialEmoNet utilizes a dynamic methodology to improve recognition accuracy by implementing pioneering feature extraction techniques, resulting in an impressive accuracy of 97.56% and an exceptionally low error rate of 2.44%. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Classifiers Facial Emotion FacialEmoNet Recognization

来源：评论

学校读者我要写书评

暂无评论

An Ensemble Approach using Self-attention based MobileNetV2 for SAR classification 2

An Ensemble Approach using Self-attention based MobileNetV2 ...

引用

2nd International Conference on Machine Learning and Data engineering, ICMLDE 2023

作者： Anjali, K.S. Singh, Rimjhim Padam Panda, Manoj Kumar Palaniappan, Kannappan Department of Electronics and Communication Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru India Department of Computer Science & Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India Department of Electrical Engineering and Computer Science University of Missouri Columbia United States

The Synthetic Aperture Radar (SAR) image classification has become an essential task in numerous applications. Despite its significance, SAR image classification remains challenging due to the inherent complexity and speckle noise characteristics of SAR data. To address this, an innovative approach is proposed in this study, combining the power of ensemble learning and the efficiency of MobileNetV2 architecture to achieve robust and accurate SAR image classification. The proposed deep learning model consists of two main components: an ensemble learning approach that combines multiple binary classifiers, and the employment of MobilenetV2 architecture with self-attention mechanism as a binary classifier. The ensemble approach uses a max-value selector for predicting final class from the individual classifier output. The MobileNetV2 architecture is finetuned by freezing weights and removing the last four layers. The inclusion of the attention layer within the architecture aids in refining the learning process by focusing on crucial features while disregarding irrelevant background elements in the images. The effectiveness of the model is evaluated using Moving and Stationary Target Acquisition and Recognition (MSTAR) benchmark dataset with accuracy of classification as performance *** model is trained and tested with images captured at various aspect angles. This approach enhances the robustness of the results, making them more applicable to real-world scenarios when compared to prior methods. This study also compares the performance of the ensemble method using MobileNetV2 with state-of-art individual classifiers and different CNN architectures. The proposed ensemble method OVA-MbNN achieves an impressive classification accuracy of 76.63%, surpassing the performance of state-of-the-art classifiers while maintaining robustness. © 2024 Elsevier B.V.. All rights reserved.

关键词： Synthetic aperture radar

来源：评论

学校读者我要写书评

暂无评论

Towards Accurate RPM Detection Using Primary Ignition Pulses 49

Towards Accurate RPM Detection Using Primary Ignition Pulses

引用

49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Wijayaraja, Jaliya L. Abhayasinghe, Nimsiri Wellalage, Sasini Sliit Faculty of Computing Department of Computer Systems Engineering Malabe Sri Lanka Sliit Faculty of Engineering Department of Electrical and Electronic Engineering Malabe Sri Lanka

ISBN: (纸本)9798350331820

Enhancing the performance and extending the life-cycle of older vehicles through retrofitting with improved systems presents an alluring opportunity. However, achieving accurate sensing of crucial parameters, such as engine revolutions per minute (RPM), poses challenges due to the need for mechanical manipulation and some designs, which may result in diminished accuracy in adverse settings. This study proposes using the primary ignition pulse signal to accurately determine engine speed without mechanical manipulation. We investigate the effectiveness of signal processing methods, including the RC filter, 2nd and 6th order Butterworth filter, to improve the accuracy of the readings. Our proposed method successfully collects data from conventional internal combustion engines, with simulated signal processing methods producing accurate detection of RPM and reduced fluctuations. The proposed method eliminated the noise, leading to accurate RPM measurements, while the maximum standard deviation observed for the RC filter implementation was 38.74. By accurately sensing key parameters, older vehicles can be retrofitted with improved systems, leading to enhanced performance and an extended lifecycle. The introduced methods can be practically implemented using custom electronics or embedded systems and can contribute to future research on automotive retrofitting. © 2023 IEEE.

关键词： Life cycle

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：