智能医疗保健系统接入物联网的安全方法
发布时间：2021-12-28 10:17
如今,由于信息通信的迅速形成,物联网（Internet of Things,IoT）被认为是一种令人振奋的事物,并被认为可能是普适计算的一种阐释。它通过直接的用户沉浸将系统模型替换扩展到不断一致地协作使用的智能设备,例如传感器和执行器,而无需人工干预。此外,自动化设备和计算专业知识被人们广泛地接受也导致了物联网的快速发展。物联网最重要的概念是平台的可访问性,该平台可以通过舒适的方式提供设施或通信,并且不存在任何障碍,可以从最容易访问的站点进行监视和控制,而该站点上遍布世界各地的任何种类事物。目前,许多智能物联网应用程序在智能应用（例如,智能无线多媒体监控网络（SWMSN）、智能医疗系统、射频识别标签（RFID）、智能城市、自动驾驶车辆（SDV）、智能电网、汽车等）中都可作为内置传感器使用,无人机监控系统（DSS）、智能家居设备、农场动物生物芯片远程监控、智能健身鞋,智能工业监控系统（SIMS）和智能交通系统（STS）等。高处理能力的发展源于智能物联网生态,它非常精通与周围环境进行有意义的智能交互。医疗保健系统与物联网环境的集成广泛一致,以便于通过现有疾病对患者进行最佳的患者监测、有效的...
【文章来源】：电子科技大学四川省 211工程院校 985工程院校 教育部直属院校
【文章页数】：134 页
【学位级别】：博士
【文章目录】：
摘要
ABSTRACT
Chapter 1 Introduction
1.1 Internet of Things (IoT)
1.2 Issues with IoT
1.3 Secure Surveillance on Smart Healthcare Model based on Io T
1.4 Issues in Secure Surveillance on Smart Healthcare Model
1.5 Extracted Keyframe Security on Smart Healthcare Model
1.6 Security Challenges in the Smart Healthcare Model based on Io T
1.7 Objectives
1.8 Contributions
1.9 Organization of Thesis
1.10 Summary
Chapter 2 Literature Survey
2.1 What is the Surveillance
2.2 Current Surveillance Approaches
2.3 Deep Learning and Neural Network
2.3.1 Feed Forward Neural Network
2.3.2 Multi-Layer Perceptron
2.4 Convolutional Neural Network
2.5 Neural Network Training Framework
2.6 Deep Neural Network Applications
2.7 What is YOLOv3 Algorithm
2.8 Integration of Secure Surveillance Approach with YOLOv3
2.9 Overview of Digital Images
2.10 Security of Digital Images
2.10.1 Cryptography
2.10.2 Data Encryption Algorithms
2.10.3 Digital Image Encryption
2.10.4 Image Encryption Evaluation Metrics
2.11 Chao Theory and Image Cryptography
2.12 Integration of Secure Surveillance and Image Cryptography
2.13 Usage of the Proposed Prototype System
2.14 Summary
Chapter 3 Surveillance on Smart Healthcare with Keyframe Encryption
3.1 Introduction
3.2 Secure Surveillance Mechanism
3.2.1 Keyframe Extraction Model from Visual Data
3.2.2 Probabilistic and Lightweight Keyframe Encryption Algorithms
3.3 Experimental Results and Discussion
3.4 Security Analysis
3.4.1 Assessment of the Speed Test
3.4.2 Information Entropy Analysis
3.4.3 Resistance to Differential Attack Analysis
3.4.4 Statistical Analysis
3.4.5 Key Analysis
3.4.6 Comparative Analysis with Existing Surveillance Scheme
3.5 Summary
Chapter 4 Cosine-transform Extracted Keyframe Encryption
4.1 Introduction
4.2 Lightweight Cosine-transform-based Keyframe Encryption Algorithms
4.2.1 Cosine-transform-based Chaotic Sequence (CCS)
4.2.2 Sine Tent Cosine Image Encryption System (STC-IES)
4.2.3 Key Structure
4.2.4 Lightweight STC-IES
4.3 Simulation Results and Discussions
4.4 Security Analysis
4.4.1 Computational Overhead and Speed Assessment
4.4.2 Information Entropy Analysis
4.4.3 Differential Attack Analysis
4.4.4 Histogram Analysis
4.4.5 Correlation Analysis
4.4.6 Key Analysis
4.4.7 Comparative Analysis among Surveillance System
4.5 Operational Enhancement in Sine Tent Cosine Image Encryption System(OESTC-IES)
4.5.1 Randomness Test Analysis of the Cipher Keyframe
4.5.2 Deviation Analysis
4.5.3 Chosen-Plaintext Attack
4.6 Summary
Chapter 5 Medical Image Encryption
5.1 Introduction
5.2 Proposed Medical Image Encryption
5.2.1 Key Structure
5.2.2 High Speed Scrambling
5.2.3 Pixel adaptive Diffusion
5.3 Results and Discussion
5.4 Security Analysis
5.4.1 Information Entropy Analysis
5.4.2 Differential Attacks
5.4.3 Statistical Analysis
5.4.4 Key Analysis
5.5 Summary
Chapter 6 Conclusion and Future Research Directions
6.1 Conclusion
6.2 Future Research Directions
Acknowledgement
References
Research Results Achieved During the Study for Doctoral Degree
本文编号：3553881
【文章来源】：电子科技大学四川省 211工程院校 985工程院校 教育部直属院校
【文章页数】：134 页
【学位级别】：博士
【文章目录】：
摘要
ABSTRACT
Chapter 1 Introduction
1.1 Internet of Things (IoT)
1.2 Issues with IoT
1.3 Secure Surveillance on Smart Healthcare Model based on Io T
1.4 Issues in Secure Surveillance on Smart Healthcare Model
1.5 Extracted Keyframe Security on Smart Healthcare Model
1.6 Security Challenges in the Smart Healthcare Model based on Io T
1.7 Objectives
1.8 Contributions
1.9 Organization of Thesis
1.10 Summary
Chapter 2 Literature Survey
2.1 What is the Surveillance
2.2 Current Surveillance Approaches
2.3 Deep Learning and Neural Network
2.3.1 Feed Forward Neural Network
2.3.2 Multi-Layer Perceptron
2.4 Convolutional Neural Network
2.5 Neural Network Training Framework
2.6 Deep Neural Network Applications
2.7 What is YOLOv3 Algorithm
2.8 Integration of Secure Surveillance Approach with YOLOv3
2.9 Overview of Digital Images
2.10 Security of Digital Images
2.10.1 Cryptography
2.10.2 Data Encryption Algorithms
2.10.3 Digital Image Encryption
2.10.4 Image Encryption Evaluation Metrics
2.11 Chao Theory and Image Cryptography
2.12 Integration of Secure Surveillance and Image Cryptography
2.13 Usage of the Proposed Prototype System
2.14 Summary
Chapter 3 Surveillance on Smart Healthcare with Keyframe Encryption
3.1 Introduction
3.2 Secure Surveillance Mechanism
3.2.1 Keyframe Extraction Model from Visual Data
3.2.2 Probabilistic and Lightweight Keyframe Encryption Algorithms
3.3 Experimental Results and Discussion
3.4 Security Analysis
3.4.1 Assessment of the Speed Test
3.4.2 Information Entropy Analysis
3.4.3 Resistance to Differential Attack Analysis
3.4.4 Statistical Analysis
3.4.5 Key Analysis
3.4.6 Comparative Analysis with Existing Surveillance Scheme
3.5 Summary
Chapter 4 Cosine-transform Extracted Keyframe Encryption
4.1 Introduction
4.2 Lightweight Cosine-transform-based Keyframe Encryption Algorithms
4.2.1 Cosine-transform-based Chaotic Sequence (CCS)
4.2.2 Sine Tent Cosine Image Encryption System (STC-IES)
4.2.3 Key Structure
4.2.4 Lightweight STC-IES
4.3 Simulation Results and Discussions
4.4 Security Analysis
4.4.1 Computational Overhead and Speed Assessment
4.4.2 Information Entropy Analysis
4.4.3 Differential Attack Analysis
4.4.4 Histogram Analysis
4.4.5 Correlation Analysis
4.4.6 Key Analysis
4.4.7 Comparative Analysis among Surveillance System
4.5 Operational Enhancement in Sine Tent Cosine Image Encryption System(OESTC-IES)
4.5.1 Randomness Test Analysis of the Cipher Keyframe
4.5.2 Deviation Analysis
4.5.3 Chosen-Plaintext Attack
4.6 Summary
Chapter 5 Medical Image Encryption
5.1 Introduction
5.2 Proposed Medical Image Encryption
5.2.1 Key Structure
5.2.2 High Speed Scrambling
5.2.3 Pixel adaptive Diffusion
5.3 Results and Discussion
5.4 Security Analysis
5.4.1 Information Entropy Analysis
5.4.2 Differential Attacks
5.4.3 Statistical Analysis
5.4.4 Key Analysis
5.5 Summary
Chapter 6 Conclusion and Future Research Directions
6.1 Conclusion
6.2 Future Research Directions
Acknowledgement
References
Research Results Achieved During the Study for Doctoral Degree
本文编号：3553881
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