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the Internet of things’ (IOT) Dynamic Evolution

The Internet of Things’ (IOT) Dynamic Evolution

引用

IEEE International conference on Emerging & Sustainable Technologies for Power & ICT in a Developing Society (NIGERCON)

作者： Ifeoma B. Asianuba Ugochukwu Nnamdi Electrical and Electronic Engineering University of Port Harcourt Port Harcourt Nigeria Center for Information and Telecommunication Engineering Uniport Port Harcourt Nigeria

ISBN: (数字)9798331542559

ISBN: (纸本)9798331542566

the Internet of things (IoT) has revolutionized the way physical devices, appliances, vehicles, and objects interact and exchange data over the Internet. this paper provides a comprehensive overview of IoT, covering its architectural development, deployment, and various application domains such as healthcare, agriculture, industry 4.0, and smart cities. the integration of machine learning (ML) and artificial intelligence (AI) in IoT is also discussed, highlighting the benefits of enhanced data analysis, improved efficiency, and autonomy. the challenges in IoT architecture, including scalability, interoperability, security, privacy, reliability, and low latency concerns are addressed, alongside future trends such as blockchain technology, augmented reality (AR) and virtual reality (VR) integration, quantum computing, and the Internet of Everything (IoE). Overall, this paper provides valuable insights into the current state and future prospects of IoT, making it a valuable resource to gain meaningful insights.

关键词： privacy Quantum computing Smart cities Scalability Machine learning Medical services Internet of things security Reliability Vehicle dynamics

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27th Nordic conference on Secure IT Systems, NordSec 2022

27th Nordic Conference on Secure IT Systems, NordSec 2022

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27th Nordic conference on Secure IT Systems, NordSec 2022

ISBN: (纸本)9783031222948

the proceedings contain 20 papers. the special focus in this conference is on Secure IT Systems. the topics include: GPU-FAN: Leaking Sensitive data from Air-Gapped Machines via Covert Noise from GPU Fans;simplex: Repurposing Intel Memory Protection Extensions for Secure Storage;automatic Implementations Synthesis of Secure Protocols and Attacks from Abstract Models;how to Avoid Repetitions in Lattice-Based Deniable Zero-Knowledge Proofs;obfuscation-Resilient Semantic Functionality Identification through Program Simulation;malware Analysis with Symbolic Execution and Graph Kernel;wearSec: Towards Automated security Evaluation of Wireless Wearable Devices;Maraudrone’s Map: An Interactive Web application for Forensic Analysis and Visualization of DJI Drone Log data;vinciDecoder: Automatically Interpreting Provenance Graphs into Textual Forensic Reports with application to OpenStack;data privacy in Ride-Sharing Services: From an Analysis of Common Practices to Improvement of User Awareness;actionable Cyber threat Intelligence for Automated Incident Response;Location privacy, 5G AKA, and Enhancements;local Differential privacy for Private Construction of Classification Algorithms;IMSI Probing: Possibilities and Limitations;honeysweeper: Towards Stealthy Honeytoken Fingerprinting Techniques;towards Self-monitoring Enclaves: Side-Channel Detection Using Performance Counters;DeCrypto: Finding Cryptocurrency Miners on ISP Networks;detection of Voice Conversion Spoofing Attacks Using Voiced Speech.

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A Review on the Integration of Artificial Intelligence in Healthcare

A Review on the Integration of Artificial Intelligence in He...

引用

Electronics and Sustainable Communication Systems (ICESC), 2020 International conference on

作者： Amrita Verma Pargaien Saurabh Pargaien Akbar Nawaz Tushar Kumar Graphic Era Hill University Bhimtal India Graphic Era Hill University Bhimtal Uttarakhand Graphic Era Deemed to be University Dehradun

ISBN: (数字)9798350379945

ISBN: (纸本)9798350379952

Artificial Intelligence (AI) is increasingly influential in health care, offering potential enhancements in diagnosis, patient care, and treatment therapies. By utilizing large datasets and sophisticated algorithms, AI assists healthcare professionals in making informed decisions, including resource allocation. For effective and safe use, professionals require adequate training and education in these technologies. AI also allows patients by improving their understanding of health conditions and providing customized solutions for diagnosis and treatment. However, concerns about data privacy, security, and ethical use are dominant. Companies must ensure that patient data is protected from breaches and misuse and is not exploited for identification or control purposes. Additionally, there are ongoing debates about the transparency, and accountability of AI systems in healthcare. this study highlights the necessity for enabling stringent regulatory frameworks to ensure these technologies are used ethically and responsibly, increasing the trust and reliability in their application within the healthcare sector.

关键词： Training Surveys Ethics privacy Reviews Medical services Companies Regulation security Artificial intelligence

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HOPPy: Holistic ontology for privacy-preserving in smart healthcare environment 5

HOPPy: Holistic ontology for privacy-preserving in smart hea...

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5th World conference on Smart Trends in Systems security and Sustainability, WorldS4 2021

作者： El Majdoubi, Driss El Bakkali, Hanan Sadki, Souad Leghmid, Asmae Maqour, Zaina Mohammed v University in Rabat Smart Systems Laboratory-Rabat IT Center

ISBN: (纸本)9781665400961

Nowadays, the Internet of things (IoT) have a great impact on improving the quality of patients' lives and offering advanced healthcare services. In this context, Smart Healthcare (S-healthcare) is an important domain with a massive knowledge base, to perform continuous health monitoring, and to provide hopeful solutions that can effectively give perfect and innovative health-related services to patients. However, due to the diversity of stakeholders involved in patients' care and the huge amount of health data collected by Medical IoT devices, the use of s-healthcare applications raises significant issues and risks in terms of privacy. In this paper, we propose a holistic privacy ontology for privacy-preserving in a S-healthcare environment. Our proposed ontology aims at defining a common privacy vocabulary in order to meet the privacy needs of the different stakeholders especially the accordance of privacy policies with patients' preferences and with the main privacy laws and regulations. Experimental results show that the proposed ontology is feasible for S-healthcare environment. © 2021 IEEE.

关键词： Ontology

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application of GBDT Integrated Algorithm in Financial data security Risk Prediction

Application of GBDT Integrated Algorithm in Financial Data S...

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5th International conference on Machine Learning and Big data Analytics for IoT security and privacy, SPIoT 2024

作者： Zeng, Jieqian Hainan Polytechnic Hainan Haikou570216 China

Financial data is usually high-dimensional and contains a large amount of information such as financial indicators, transaction records, and personnel permissions. Traditional machine learning models are susceptible to the "dimensionality disaster"when processing these high-dimensional data, resulting in a decline in model performance. To this end, this paper proposes an application method based on the GBDT (gradient boosting decision tree) algorithm for financial data security risk prediction. First, through data preprocessing steps, including missing value processing, outlier detection, and feature engineering, the original financial data is cleaned and optimized to provide high-quality data input for model training. In the feature selection stage, GBDT automatically evaluates the contribution of each feature to the prediction result through the built-in feature importance evaluation function, helping to screen the most important features. During the training process, the GBDT algorithm trains multiple decision trees through multiple iterations, gradually minimizing the prediction error and improving the prediction accuracy of the model. After completing the model training, the GBDT model can output the prediction results and judge the security risks of the data by setting thresholds. Finally, in the experiment, the prediction accuracy of the model is significantly higher than that of traditional statistical methods, and it has strong robustness to outliers and noise data. By setting the risk threshold, the model can better judge whether there are potential security risks in financial data and meet the needs of practical applications. © 2025 the Authors. Published by Elsevier B.V.

关键词： Network security

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5th International conference on Big data and security, ICBDS 2023

5th International Conference on Big Data and Security, ICBDS...

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5th International conference on Big data and security, ICBDS 2023

ISBN: (纸本)9789819743865

the proceedings contain 18 papers. the special focus in this conference is on Big data and security. the topics include: Development of U-net Neural Network for Biomedical Images with Big data;Research on Implementation of BADGE Active Learning to Increase Defect Detection Effectiveness;stationary Multi-scale Hierarchical Dilated Graph Convolution for Multivariate Time Series Anomaly Detection;design of Human Resource Optimal Allocation Model for Electric Power Construction Enterprises Based on Machine Learning;research on the Construction of Digital Education Cloud Resource database Based on Ant Colony Algorithm;simulation of Short-Term Prediction Model of Real Estate Price Index Based on Neural Network Algorithm;PLMR: An Efficient Pre-trained Model for Aircraft Maneuver Recognition;blockchain-Based WeChat Small Program Platform: A New Type of data security and Management Solution;a Survey of Edge Computing Resource Allocation and Task Scheduling Optimization;an Algorithm for Analyzing Psychological Characteristics in Music Education Based on Markov Model;enhancing privacy Strategy in New Power Systems: Problem Assessment, Comparative Analysis and Suggestions;internet Public Opinion Evolution Model and Simulation Based on Big data and Grey Clustering Algorithm Under New Media Environment;simulation of Regional Financial and Economic Development Decision Model Based on Decision Tree Algorithm;simulation Research on Pre-alarm Model of Enterprise Shared Financial Crisis Based on Genetic Algorithm;research on Accurate Poverty Alleviation Algorithm of Rural Industry Based on Association Rules Mining;preface.

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A Robust medical data sharing application with a collaborative hypothesis and Elastic net regression model 5

A Robust medical data sharing application with a collaborati...

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5th International conference on Electronics, Communication and Aerospace Technology, ICECA 2021

作者： Naidu, J.N.S.S. Janardhana Ganesh, E.N. Reddy, Nagaraj Doddam Sankaran, Mahesh Chennai India

ISBN: (纸本)9781665435246

Clinical data and records are the main data to help various customized applications like clinical proof, protection, digital data and criminal personality. Different blockchain and conventional methodology have been created, which are obsolete in this example. Progressed clinical information imparting to security and protection are along these lines required in saving related procedures. this study develops an adaptive blockchain approach and a machine-learning model based on elastic net regression. the preceding two ways give the classified data of brain cancer in the general hospital of Sowjanya greater safety and privacy. this is better than previous mechanisms, with precision 98.56%, detection rate 97.34%, error rate 0.023, sensitivity 98.38% and output 97.28% competing with existing approaches. © 2021 IEEE.

关键词： Blockchain

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SteemOps: Extracting and Analyzing Key Operations in Steemit Blockchain-based Social Media Platform 21

SteemOps: Extracting and Analyzing Key Operations in Steemit...

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11th acm conference on data and application security and privacy (CODASPY)

作者： Li, Chao Palanisamy, Balaji Xu, Runhua Xu, Jinlai Wang, Jingzhe Beijing Jiaotong Univ Beijing Key Lab Secur & Privacy Intelligent Trans Beijing Peoples R China Univ Pittsburgh Sch Comp & Informat Pittsburgh PA USA IBM Almaden Res Ctr San Jose CA USA

ISBN: (纸本)9781450381437

Advancements in distributed ledger technologies are driving the rise of blockchain-based social media platforms such as Steemit, where users interact with each other in similar ways as conventional social networks. these platforms are autonomously managed by users using decentralized consensus protocols in a cryptocurrency ecosystem. the deep integration of social networks and blockchains in these platforms provides potential for numerous cross-domain research studies that are of interest to both the research communities. However, it is challenging to process and analyze large volumes of raw Steemit data as it requires specialized skills in both software engineering and blockchain systems and involves substantial efforts in extracting and filtering various types of operations. To tackle this challenge, we collect over 38 million blocks generated in Steemit during a 45 month time period from 2016/03 to 2019/11 and extract ten key types of operations performed by the users. the results generate SteemOps, a new dataset that organizes more than 900 million operations from Steemit into three sub-datasets namely (i) social-network operation dataset (SOD), (ii) witness-election operation dataset (WOD) and (iii) value-transfer operation dataset (VOD). We describe the dataset schema and its usage in detail and outline possible future research studies using SteemOps. SteemOps is designed to facilitate future research aimed at providing deeper insights on emerging blockchain-based social media platforms.

关键词： blockchain social network Steem dataset

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5th International conference on Big data and security, ICBDS 2023

5th International Conference on Big Data and Security, ICBDS...

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5th International conference on Big data and security, ICBDS 2023

ISBN: (纸本)9789819743896

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Research on Setting of Two Firewall Rules Based on Ubuntu Linux System 5

Research on Setting of Two Firewall Rules Based on Ubuntu Li...

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5th International conference on Computer Network, Electronic and Automation, ICCNEA 2022

作者： Ma, Limei Zhao, Dongmei Hebei Normal University College of Computer and Cyber Security Shijiazhuang China Key Laboratory of Network and Information Security in Hebei Province Shijiazhuang China

ISBN: (数字)9781665491099

ISBN: (纸本)9781665491099

'security first' is the most concerned issue of Linux administrators. security refers to the integrity of data. the authentication security and integrity of data are higher than the privacy security of data. Firewall is used to realize the function of access control under Linux. It is divided into hardware or software firewall. No matter in which network, the firewall must work at the edge of the network. Our task is to define how the firewall works. this is the firewall's policies and rules, so that it can detect the IP and data in and out of the network. At present, there are three or four layers of firewalls on the market, which are called network layer firewalls, and seven layers of firewalls, which are actually the gateway of the agent layer. But for the seven layer firewall, no matter what your source port or target port, source address or target address is, it will check all your things. therefore, the seven layer firewall is more secure, but it brings lower efficiency. therefore, the usual firewall schemes on the market are a combination of the two. And because we all need to access from the port controlled by the firewall, the work efficiency of the firewall has become the most important control of how much data users can access. this paper introduces two types of firewalls iptables and TCP_Wrappers. What are the differences between the use policies, rules and structures of the two firewalls? this is the problem to be discussed in this paper. © 2022 IEEE.

关键词： Network layers

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