检索结果-内蒙古大学图书馆

On the design of an AI-driven secure communication scheme for internet of medical things environment

Digital Communications and Networks 2023年第5期9卷 1080-1089页

作者： Neha Garg Rajat Petwal Mohammad Wazid D.P.Singh Ashok Kumar Das Joel J.P.C.Rodrigues Department of Computer Science and Engineering Graphic Era Deemed to be UniversityDehradun248002India Center for Security Theory and Algorithmic ResearchInternational Institute of Information TechnologyHyderabad500032India College of Computer Science and Technology China University of Petroleum(East China)Qingdao266555China Instituto de Telecomunicaçoes 6201-001CovilhaPortugal

The Internet of Medical Things(IoMT)is a collection of smart healthcare devices,hardware infrastructure,and related software applications,that facilitate the connection of healthcare information technology system via the *** is also called IoT in healthcare,facilitating secure communication of remote healthcare devices over the Internet for quick and flexible analysis of healthcare *** other words,IoMT is an amalgam of medical devices and applications,which improves overall healthcare ***,this system is prone to securityand privacy-related attacks on healthcare ***,providing a robust security mechanism to prevent the attacks and vulnerability of IoMT is *** mitigate this,we proposed a new Artificial-Intelligence envisioned secure communication scheme for *** discussed network and threat models provide details of the associated network arrangement of the IoMT devices and attacks relevant to ***,we provide the security analysis of the proposed scheme to show its security against different possible ***,a comparative study of the proposed scheme with other similar schemes is *** results show that the proposed scheme outperforms other similar schemes in terms of communication and computation costs,and security and functionality ***,we provide a pragmatic study of the proposed scheme to observe its impact on various network performance parameters.

关键词： Internet of Medical Things(IoMT) Security Authentication and key agreement Artificial Intelligence(AI) Big data analytics

来源：评论

学校读者我要写书评

暂无评论

IoT-Enabled Remote-Controlled Raft for Enhanced Water Quality Assessment 20

IoT-Enabled Remote-Controlled Raft for Enhanced Water Qualit...

引用

20th IEEE International Colloquium on Signal Processing and Its Applications, CSPA 2024

作者： Surasak, Thattapon Kitchat, Kotcharat Jiteurtragool, Nattagit King Mongkut's University Of Technology North Bangkok Faculty Of Applied Science Dept. Of Computer And Information Science Bangkok Thailand National Central University Dept. Of Computer Science And Information Engineering Taoyuan Taiwan

ISBN: (纸本)9798350382310

Water is vital for all life, serving as the foundation for plants and aquatic creatures and promoting abundance among all living beings. This study introduces an innovative approach by combining the Internet of Things (IoT) with advanced sensing techniques to assess water quality. The IoT-powered water quality testing raft has been developed to significantly enhance the monitoring capabilities. Equipped with sensors measuring key parameters such as turbidity, pH, and temperature, the raft provides a comprehensive understanding of water quality. Its GPS module enables real-time tracking and maintains location history, ensuring precise sampling. The collected data undergoes robust processing by a Raspberry Pi, ensuring integrity before being showcased on the Thingsboard. The system's uniqueness lies in its capacity to promptly issue alerts via LINE Notify upon detecting water quality abnormalities, ensuring timely intervention. This IoT-powered raft represents a paradigm shift in water quality assessment, characterised by its precision, remote capabilities, and user-focused approach. Practical applications have been demonstrated through real-world testing in a private lake in Cha-choengsao province, Thailand. The seamless integration of IoT into environmental monitoring marks a significant advancement in ensuring water quality and ecosystem health. © 2024 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Generative AI-Powered Aerial Access Networks: Recent Studies and Future Outlook 15

Generative AI-Powered Aerial Access Networks: Recent Studies...

引用

15th International Conference on information and Communication technology Convergence, ICTC 2024

作者： Nguyen, Tri-Hai Nguyen, Truong Khang Bao, Vo Nguyen Quoc Park, Heejae Park, Laihyuk School of Technology Van Lang University Faculty of Information Technology Ho Chi Minh City70000 Viet Nam Seoul National University of Science and Technology Department of Computer Science and Engineering Seoul01811 Korea Republic of

ISBN: (纸本)9798350364637

Aerial access networks (AANs), comprising un-manned aerial vehicles (UAV), high-altitude platforms (HAPs), and low-earth orbit (LEO) satellites, are rapidly emerging as a critical component of next-generation communication systems. Their dynamic nature, heterogeneous composition, and vast coverage area pose significant challenges for network management and optimization. Generative artificial intelligence (GenAI), renowned for its ability to generate new content, offers a promising solution to these challenges. In this paper, we explore the applications of GenAI in AANs in recent studies. We also identify key challenges and outline promising research directions. © 2024 IEEE.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Detection of Low Rate DDoS with Adversarial Attacks by Enhanced Generative Adversarial Networks

Detection of Low Rate DDoS with Adversarial Attacks by Enhan...

引用

2024 IEEE International Conference on systems, Man, and Cybernetics, SMC 2024

作者： Hsiao, Tzu-Yi Yang, Shih-Hsuan National Taipei University of Technology Taipei Taiwan National Taipei University of Technology Computer Science and Information Engineering Department Taipei Taiwan

ISBN: (纸本)9781665410205

The Internet of Things is vulnerable to cybersecurity attacks because it is typically designed with minimal security considerations. The Low-Rate Distributed Denial-of-Service (LR-DDoS) attacks evade detection by injecting a small portion of malicious packets that persistently lurk within the IoT network. Recently, adversarial LR-DDoS attacks further complicate machine learning based security protection. In this study, an improved detection algorithm based on a generative adversarial network is proposed against LR-DDoS. To learn the temporal characteristics, LR-DDoS time-series features are taken as a part of the generator's input and Long Short-Term Memory modules are incorporated. Two discriminators with adaptive weighting are employed, one for conventional LR-DDoS attacks and the other for the adversarial attacks, to generate plausible LR-DDoS samples. The generated packets are used to train the detection algorithm of an Intrusion Detection system. Simulation results show that the proposed method achieves an accuracy of 94% in detecting adversarial LR-DDoS packets, which outperforms the state-of-the-art methods by at least 10%. © 2024 IEEE.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

High-Performance Video Retrieval by Combining Contrastive Language Image Pre-Training and Cross-Modal Attention

High-Performance Video Retrieval by Combining Contrastive La...

引用

2024 IEEE International Conference on systems, Man, and Cybernetics, SMC 2024

作者： Ou, Jun-Jie Yang, Shih-Hsuan National Taipei University of Technology Taipei Taiwan National Taipei University of Technology Computer Science and Information Engineering Department Taipei Taiwan

ISBN: (纸本)9781665410205

Video retrieval is a task that locates the video segments that best match the query text. Although joint language-image models have recently achieved great success, training a video retrieval model typically requires a large data set and leads to long training time. This paper aims for a high-performance video retrieval method by combining pre-trained encoders and cross-modal attention. We first leverage the pre-trained CLIP (Contrastive Language-Image Pre-Training) ViT-B/16 encoders to extract the feature vectors for videos and texts. Next, the X-Pool, a recent cross-modal language-video attention model is incorporated into the system, where three layers of X-Pool are used to enhance retrieval accuracy. We also suggest using sparse sampling on video frames to further reduce training time. The effectiveness of the proposed method is evaluated using the MSRVTT and MSVD benchmark datasets. The proposed method achieves the best retrieval performance (recall@k, median rank, and mean rank) among the state-of-the-art methods with comparable computational complexity. © 2024 IEEE.

关键词： Query languages

来源：评论

学校读者我要写书评

暂无评论

Leveraging AI to Unlock the Potential of Data science 15

Leveraging AI to Unlock the Potential of Data Science

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Yadav, Rakesh Kumar Sudhamsu, Gadug Goyal, Manish Kumar Yuvaraj, S. Deshpande, Leena A. Maharishi University of Information Technology Maharishi School of Engineering and Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Computer Science and Engineering Karnataka Bangalore India Vivekananda Global University Department of Computer Science & Application Jaipur India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Chennai127 India Vishwakarma Institute of Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350370249

The application of synthetic Intelligence (AI) to records science has spread out a massive array of new possibilities. Via the combination of advanced evaluation strategies, effective understanding-pushed system gaining knowledge of algorithms, and modern computing architectures, AI is allowing researchers to quick and as it should be discover insights from huge and complicated datasets. Furthermore, AI tools are offering corporations with the ability to make higher and more knowledgeable choices from the evaluation of hundreds of thousands of statistics points. The skills of information technology powered by means of AI are revolutionizing industries which includes healthcare, finance, and manufacturing-producing savings, uncovering efficiencies, and identifying new opportunities. As AI-driven records technology maintains to strengthen, organizations that capitalize on its ability stand to gain precious insights and unlock new degrees of overall performance. © 2024 IEEE.

关键词： Smart manufacturing

来源：评论

学校读者我要写书评

暂无评论

Intelligent Anti-tamper systems: Safeguarding Critical Infrastructure in the Era of Proliferating Interconnected Devices and IoBT 6th

Intelligent Anti-tamper Systems: Safeguarding Critical Infra...

引用

6th International Conference on Computational Intelligence in Pattern Recognition, CIPR 2024

作者： Jena, Shubhashish Behera, H.S. Jena, Gunamani Department of Information Technology VSSUT Odisha Burla India Department of Computer Science and Engineering BVCE Andhra Pradesh Odalarevu India

ISBN: (纸本)9789819780891

By 2025, the expected 50 billion connected devices worldwide will heighten risks of physical and direct attacks on critical systems. The Internet of Battlefield Things (IoBT) and embedded devices in industrial controls and infrastructure further amplify the threat. Traditional anti-tamper systems, limited by deterministic responses to specific attack types, are becoming inadequate due to advanced stealthier attacks. Intelligent defenses are essential for extended operational life and keeping pace with evolving threats. This study advocates for sophisticated anti-tamper solutions using machine learning to bolster physical security. The proposed system can detect various activities, discern normal operations from anomalies and known attacks, and has a stratified response and recovery mechanism, enhancing longevity and minimizing false positives. The growing IoBT usage necessitates better anti-tamper designs, and this research also explores the system’s resilience against adversarial learning attacks. We applied decision tree, SVM, and bagging classifiers and found that bagging classifier achieves 100% accuracy, outperforming the other used algorithms. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Critical infrastructures

来源：评论

学校读者我要写书评

暂无评论

Optimal Load Forecasting Model for Peer-to-Peer Energy Trading in Smart Grids

引用

computers, Materials & Continua 2022年第1期70卷 1053-1067页

作者： Lijo Jacob Varghese K.Dhayalini Suma Sira Jacob Ihsan Ali Abdelzahir Abdelmaboud Taiseer Abdalla Elfadil Eisa Department of Electrical and Electronics Engineering Christian College of Engineering and TechnologyOddanchatram624619India Department of Electrical and Electronics Engineering K.Ramakrishnan College of EngineeringTiruchirappalli621112India Department of Computer Science and Engineering Christian College of Engineering and TechnologyOddanchatram624619India Department of Computer System and Technology Faculty of Computer Science and Information TechnologyUniversity of Malaya50603Kuala LumpurMalaysia Department of Information Systems King Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Information Systems-Girls Section King Khalid UniversityMahayil62529Saudi Arabia

Peer-to-Peer(P2P)electricity trading is a significant research area that offers maximum fulfilment for both prosumer and *** also decreases the quantity of line loss incurred in Smart Grid(SG).But,uncertainities in demand and supply of the electricity might lead to instability in P2P market for both prosumer and *** recent times,numerous Machine Learning(ML)-enabled load predictive techniques have been developed,while most of the existing studies did not consider its implicit features,optimal parameter selection,and prediction *** order to overcome fulfill this research gap,the current research paper presents a new Multi-Objective Grasshopper Optimisation Algorithm(MOGOA)with Deep Extreme Learning Machine(DELM)-based short-term load predictive technique i.e.,MOGOA-DELM model for P2P Energy Trading(ET)in *** proposed MOGOA-DELM model involves four distinct stages of operations namely,data cleaning,Feature Selection(FS),prediction,and parameter *** addition,MOGOA-based FS technique is utilized in the selection of optimum subset of ***,DELM-based predictive model is also applied in forecasting the load *** proposed MOGOA model is also applied in FS and the selection of optimalDELM parameters to improve the predictive *** inspect the effectual outcome of the proposed MOGOA-DELM model,a series of simulations was performed using UK Smart Meter *** the experimentation procedure,the proposed model achieved the highest accuracy of 85.80%and the results established the superiority of the proposed model in predicting the testing data.

关键词： Peer to Peer energy trade smart grid load forecasting machine learning feature selection

来源：评论

学校读者我要写书评

暂无评论

Disease Diagnosis system Using IoT Empowered with Fuzzy Inference system

引用

computers, Materials & Continua 2022年第3期70卷 5305-5319页

作者： Talha Mahboob Alam Kamran Shaukat Adel Khelifi Wasim Ahmad Khan Hafiz Muhammad Ehtisham Raza Muhammad Idrees Suhuai Luo Ibrahim A.Hameed Department of Computer Science and Information Technology Virtual University of PakistanLahorePakistan School of Information and Physical Sciences The University of NewcastleAustralia Department of Computer Science and Information Technology Abu Dhabi UniversityAbu DhabiUnited Arab Emirates School of Computer Science National College of Business Administration&EconomicsLahorePakistan Sir Syed College of Computer Science University of Engineering and TechnologyLahorePakistan Department of Data Science University of the PunjabLahorePakistan Department of ICT and Natural Sciences Norwegian University of Science and TechnologyTrondheimNorway

Disease diagnosis is a challenging task due to a large number of associated *** in the diagnosis process arises frominaccuracy in patient attributes,missing data,and limitation in the medical expert’s ability to define cause and effect relationships when there are multiple interrelated *** paper aims to demonstrate an integrated view of deploying smart disease diagnosis using the Internet of Things(IoT)empowered by the fuzzy inference system(FIS)to diagnose various *** Fuzzy systemis one of the best systems to diagnose medical conditions because every disease diagnosis involves many uncertainties,and fuzzy logic is the best way to handle *** proposed system differentiates new cases provided symptoms of the ***,it becomes a time-sensitive task to discriminate symptomatic *** proposed system can track symptoms firmly to diagnose diseases through IoT and FIS smartly and *** coefficients have been employed to predict and compute the identified disease’s severity for each sign of *** study aims to differentiate and diagnose COVID-19,Typhoid,Malaria,and *** study used the FIS method to figure out the disease over the use of given data related to correlating with input *** tool is utilised for the implementation of *** procedure on the aforementioned given data presents that affectionate disease can derive from the *** results of our proposed method proved that FIS could be utilised for the diagnosis of other *** study may assist doctors,patients,medical practitioners,and other healthcare professionals in early diagnosis and better treat diseases.

关键词： Disease diagnosis system COVID-19 healthcare biomedical rules extraction

来源：评论

学校读者我要写书评

暂无评论

The Implied Volatility Surface Analysis Based Trading system 2

The Implied Volatility Surface Analysis Based Trading System

引用

2nd IEEE International Conference on Data science and computer Application, ICDSCA 2022

作者： Guo, Guoxiang Qi, Yuanyuan Lai, Sirui Yen, Jerome University of Macau Department of Computer and Information Science Faculty of Science Technology China

ISBN: (数字)9781665472005

ISBN: (纸本)9781665472005

Volatility is a crucial factor in option pricing models. The implied volatility is the estimated volatility from market trades and represents market sentiment in recent research. The implied volatility surface (IVS) based market analysis is also gathering more attention for its satisfying regression performance in risk management and related tasks. In this research, we develop an industrial application of the market trading system based on Support Vector Regression (SVR) and implement simulated trading through backtesting. According to the SPY option historical data experiment results, considering appropriate transaction cost, the system reaches satisfying performance in the fluctuating market. © 2022 IEEE.

关键词： Surface analysis

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：