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E-raamat: Smart Healthcare System Design - Security and Privacy Aspects: Security and Privacy Aspects [Wiley Online]

Edited by (Indian Institute of Information Technology, Kalyani, India), Edited by (CHRIST (Deemed To Be University), Bangalore, India)
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Smart Healthcare System Design - Security and Privacy Aspects: Security and Privacy AspectsSuurem pilt
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Wiley Online e-raamatudRohkem infot Wiley Online kohta
Raamatu kodulehekülg: https://onlinelibrary.wiley.com/doi/book/10.1002/9781119792253
SMART HEALTHCARE SYSTEM DESIGN This book deeply discusses the major challenges and issues for security and privacy aspects of smart health-care systems.

The Internet-of-Things (IoT) has emerged as a powerful and promising technology, and though it has significant technological, social, and economic impacts, it also poses new security and privacy challenges. Compared with the traditional internet, the IoT has various embedded devices, mobile devices, a server, and the cloud, with different capabilities to support multiple services. The pervasiveness of these devices represents a huge attack surface and, since the IoT connects cyberspace to physical space, known as a cyber-physical system, IoT attacks not only have an impact on information systems, but also affect physical infrastructure, the environment, and even human security.

The purpose of this book is to help achieve a better integration between the work of researchers and practitioners in a single medium for capturing state-of-the-art IoT solutions in healthcare applications, and to address how to improve the proficiency of wireless sensor networks (WSNs) in healthcare. It explores possible automated solutions in everyday life, including the structures of healthcare systems built to handle large amounts of data, thereby improving clinical decisions. The 14 separate chapters address various aspects of the IoT system, such as design challenges, theory, various protocols, implementation issues, as well as several case studies.

Smart Healthcare System Design covers the introduction, development, and applications of smart healthcare models that represent the current state-of-the-art of various domains. The primary focus is on theory, algorithms, and their implementation targeted at real-world problems. It will deal with different applications to give the practitioner a flavor of how IoT architectures are designed and introduced into various situations.

Audience: Researchers and industry engineers in information technology, artificial intelligence, cyber security, as well as designers of healthcare systems, will find this book very valuable.
Preface xvii
Acknowledgments xxiii
1 Machine Learning Technologies in IoT EEG-Based Healthcare Prediction 1(32)
M.P. Karthikeyan
K. Krishnaveni
N. Muthumani
1.1 Introduction
2(5)
1.1.1 Descriptive Analytics
3(1)
1.1.2 Analytical Methods
3(1)
1.1.3 Predictive Analysis
4(1)
1.1.4 Behavioral Analysis
4(1)
1.1.5 Data Interpretation
4(1)
1.1.6 Classification
4(3)
1.2 Related Works
7(2)
1.3 Problem Definition
9(1)
1.4 Research Methodology
9(7)
1.4.1 Components Used
10(1)
1.4.2 Specifications and Description About Components
10(3)
1.4.2.1 Arduino
10(1)
1.4.2.2 EEG Sensor-Mindwave Mobile Headset
11(1)
1.4.2.3 Raspberry pi
12(1)
1.4.2.4 Working
13(1)
1.4.3 Cloud Feature Extraction
13(1)
1.4.4 Feature Optimization
14(1)
1.4.5 Classification and Validation
15(1)
1.5 Result and Discussion
16(11)
1.5.1 Result
16(7)
1.5.2 Discussion
23(4)
1.6 Conclusion
27(1)
1.6.1 Future Scope
27(1)
References
28(5)
2 Smart Health Application for Remote Tracking of Ambulatory Patients 33(24)
Shariq Aziz Butt
Muhammad Waqas Anjum
Syed Areeb Hassan
Arindam Garai
Edeh Michael Onyema
2.1 Introduction
34(1)
2.2 Literature Work
34(1)
2.3 Smart Computing for Smart Health for Ambulatory Patients
35(1)
2.4 Challenges With Smart Health
36(5)
2.4.1 Emergency Support
36(2)
2.4.2 The Issue With Chronic Disease Monitoring
38(1)
2.4.3 An Issue With the Tele-Medication
38(2)
2.4.4 Mobility of Doctor
40(1)
2.4.5 Application User Interface Issue
40(1)
2.5 Security Threats
41(2)
2.5.1 Identity Privacy
41(1)
2.5.2 Query Privacy
42(1)
2.5.3 Location of Privacy
42(1)
2.5.4 Footprint Privacy and Owner Privacy
43(1)
2.6 Applications of Fuzzy Set Theory in Healthcare and Medical Problems
43(8)
2.7 Conclusion
51(1)
References
51(6)
3 Data-Driven Decision Making in IoT Healthcare Systems-COVID-19: A Case Study 57(14)
S. Saroja
S. Haseena
M. Blessa Binolin Pepsi
3.1 Introduction
58(5)
3.1.1 Pre-Processing
59(1)
3.1.2 Classification Algorithms
60(3)
3.1.2.1 Dummy Classifier
60(1)
3.1.2.2 Support Vector Machine (SVM)
60(1)
3.1.2.3 Gradient Boosting
61(1)
3.1.2.4 Random Forest
62(1)
3.1.2.5 Ada Boost
63(1)
3.2 Experimental Analysis
63(1)
3.3 Multi-Criteria Decision Making (MCDM) Procedure
63(6)
3.3.1 Simple Multi Attribute Rating Technique (SMART)
64(2)
3.3.1.1 COVID-19 Disease Classification Using SMART
64(2)
3.3.2 Weighted Product Model (WPM)
66(1)
3.3.2.1 COVID-19 Disease Classification Using WPM
66(1)
3.3.3 Method for Order Preference by Similarity to the Ideal Solution (TOPSIS)
67(5)
3.3.3.1 COVID-19 Disease Classification Using TOPSIS
68(1)
3.4 Conclusion
69(1)
References
69(2)
4 Touch and Voice-Assisted Multilingual Communication Prototype for ICU Patients Specific to COVID-19 71(16)
B. Rajesh Kanna
C. Vijayalakshmi
4.1 Introduction and Motivation
72(3)
4.1.1 Existing Interaction Approaches and Technology
73(1)
4.1.2 Challenges and Gaps
74(1)
4.2 Proposed Prototype of Touch and Voice-Assisted Multilingual Communication
75(7)
4.3 A Sample Case Study
82(1)
4.4 Conclusion
82(2)
References
84(3)
5 Cloud-Assisted IoT System for Epidemic Disease Detection and Spread Monitoring 87(28)
Himadri Nath Saha
Reek Roy
Sumanta Chakraborty
5.1 Introduction
88(4)
5.2 Background & Related Works
92(6)
5.3 Proposed Model
98(5)
5.3.1 ThinkSpeak
100(1)
5.3.2 Blood Oxygen Saturation (SpO2)
100(1)
5.3.3 Blood Pressure (BP)
101(1)
5.3.4 Electrocardiogram (ECG)
101(1)
5.3.5 Body Temperature (BT)
102(1)
5.3.6 Respiration Rate (RR)
102(1)
5.3.7 Environmental Parameters
103(1)
5.4 Methodology
103(7)
5.5 Performance Analysis
110(1)
5.6 Future Research Direction
111(1)
5.7 Conclusion
112(1)
References
113(2)
6 Impact of Healthcare 4.0 Technologies for Future Capacity Building to Control Epidemic Diseases 115(28)
Himadri Nath Saha
Sumanta Chakraborty
Sourav Paul
Rajdeep Ghosh
Dipanwita Chakraborty Bhattacharya
6.1 Introduction
116(4)
6.2 Background and Related Works
120(8)
6.3 System Design and Architecture
128(3)
6.4 Methodology
131(7)
6.5 Performance Analysis
138(1)
6.6 Future Research Direction
138(1)
6.7 Conclusion
139(1)
References
139(4)
7 Security and Privacy of IoT Devices in Healthcare Systems 143(24)
Himadri Nath Saha
Subhradip Debnath
7.1 Introduction
144(1)
7.2 Background and Related Works
145(2)
7.3 Proposed System Design and Architecture
147(4)
7.3.1 Modules
148(29)
7.3.1.1 Wireless Body Area Network
148(1)
7.3.1.2 Centralized Network Coordinator
149(1)
7.3.1.3 Local Server
149(1)
7.3.1.4 Cloud Server
150(1)
7.3.1.5 Dedicated Network Connection
151(1)
7.4 Methodology
151(9)
7.5 Performance Analysis
160(1)
7.6 Future Research Direction
161(2)
7.7 Conclusion
163(1)
References
164(3)
8 An IoT-Based Diet Monitoring Healthcare System for Women 167(36)
S. Suganyadevi
D. Shamia
K. Balasamy
8.1 Introduction
168(9)
8.2 Background
177(4)
8.2.1 Food Consumption
177(1)
8.2.2 Food Consumption Monitoring
178(1)
8.2.3 Health Monitoring Methods Using Physical Methodology
179(1)
8.2.3.1 Traditional Form of Self-Report
179(1)
8.2.3.2 Self-Reporting Methodology Through Smart Phones
179(1)
8.2.3.3 Food Frequency Questionnaire
179(1)
8.2.4 Methods for Health Tracking Using Automated Approach
180(1)
8.2.4.1 Pressure Process
180(1)
8.2.4.2 Surveillance Video Method
180(1)
8.2.4.3 Method of Doppler Sensing
180(1)
8.3 Necessity of Wearable Approach?
181(1)
8.4 Different Approaches for Wearable Sensing
181(3)
8.4.1 Approach of Acoustics
182(3)
8.4.1.1 Detection of Chewing
182(1)
8.4.1.2 Detection of Swallowing
183(1)
8.4.1.3 Shared Chewing/Swallowing Discovery
183(1)
8.5 Description of the Methodology
184(1)
8.6 Description of Various Components Used
185(4)
8.6.1 Sensors
185(18)
8.6.1.1 Sensors for Cardio-Vascular Monitoring
185(1)
8.6.1.2 Sensors for Activity Monitoring
186(1)
8.6.1.3 Sensors for Body Temperature Monitoring
187(1)
8.6.1.4 Sensor for Galvanic Skin Response (GSR) Monitoring
188(1)
8.6.1.5 Sensor for Monitoring the Blood Oxygen Saturation (SpO2)
189(1)
8.7 Strategy of Communication for Wearable Systems
189(3)
8.8 Conclusion
192(2)
References
194(9)
9 A Secure Framework for Protecting Clinical Data in Medical IoT Environment 203(32)
K. Balasamy
N. Krishnaraj
J. Ramprasath
P. Ramprakash
9.1 Introduction
203(6)
9.1.1 Medical IoT Background & Perspective
204(5)
9.1.1.1 Medical IoT Communication Network
204(5)
9.2 Medical IoT Application Domains
209(1)
9.2.1 Smart Doctor
209(1)
9.2.2 Smart Medical Practitioner
209(1)
9.2.3 Smart Technology
209(1)
9.2.4 Smart Receptionist
210(1)
9.2.5 Disaster Response Systems (DRS)
210(1)
9.3 Medical IoT Concerns
210(2)
9.3.1 Security Concerns
211(1)
9.3.2 Privacy Concerns
212(1)
9.3.3 Trust Concerns
212(1)
9.4 Need for Security in Medical IoT
212(2)
9.5 Components for Enhancing Data Security in Medical IoT
214(1)
9.5.1 Confidentiality
214(1)
9.5.2 Integrity
214(1)
9.5.3 Authentication
215(1)
9.5.4 Non-Repudiation
215(1)
9.5.5 Privacy
215(1)
9.6 Vulnerabilities in Medical IoT Environment
215(3)
9.6.1 Patient Privacy Protection
215(1)
9.6.2 Patient Safety
216(1)
9.6.3 Unauthorized Access
216(1)
9.6.4 Medical IoT Security Constraints
217(1)
9.7 Solutions for IoT Healthcare Cyber-Security
218(2)
9.7.1 Architecture of the Smart Healthcare System
218(2)
9.7.1.1 Data Perception Layer
218(1)
9.7.1.2 Data Communication Layer
219(1)
9.7.1.3 Data Storage Layer
219(1)
9.7.1.4 Data Application Layer
219(1)
9.8 Execution of Trusted Environment
220(3)
9.8.1 Root of Trust Security Services
220(2)
9.8.2 Chain of Trust Security Services
222(1)
9.9 Patient Registration Using Medical IoT Devices
223(6)
9.9.1 Encryption
224(1)
9.9.2 Key Generation
225(1)
9.9.3 Security by Isolation
225(1)
9.9.4 Virtualization
225(4)
9.10 Trusted Communication Using Block Chain
229(3)
9.10.1 Record Creation Using IoT Gateways
229(1)
9.10.2 Accessibility to Patient Medical History
230(1)
9.10.3 Patient Enquiry With Hospital Authority
230(1)
9.10.4 Block Chain Based IoT System Architecture
231(5)
9.10.4.1 First Layer
231(1)
9.10.4.2 Second Layer
231(1)
9.10.4.3 Third Layer
232(1)
9.11 Conclusion
232(1)
References
233(2)
10 Efficient Data Transmission and Remote Monitoring System for IoT Applications 235(30)
Laith Farhan
Firas MaanAbdulsattar
Laith Alzubaidi
Mohammed A. Fadhel
Banu Calis Uslu
Muthana Al-Amidie
10.1 Introduction
236(1)
10.2 Network Configuration
236(9)
10.2.1 Message Queuing Telemetry Transport (MQTT) Protocol
238(4)
10.2.2 Embedded Database SQLite
242(1)
10.2.3 Eclipse Paho Library
242(1)
10.2.4 Raspberry Pi Single Board Computer
242(1)
10.2.5 Custard Pi Add-On Board
243(1)
10.2.6 Pressure Transmitter (Type 663)
244(1)
10.3 Data Filtering and Predicting Processes
245(4)
10.3.1 Filtering Process
245(1)
10.3.2 Predicting Process
246(2)
10.3.3 Remote Monitoring Systems
248(1)
10.4 Experimental Setup
249(12)
10.4.1 Implementation Using Python
251(1)
10.4.1.1 Prerequisites
251(1)
10.4.2 Monitoring Data
251(4)
10.4.3 Experimental Results
255(11)
10.4.3.1 IoT Device Results
255(2)
10.4.3.2 Traditional Network Results
257(4)
10.5 Conclusion
261(1)
References
261(4)
11 IoT in Current Times and its Prospective Advancements 265(16)
T. Venkat Narayana Rao
Abhishek Duggirala
Muralidhar Kurni
Syed Tabassum Sultana
11.1 Introduction
266(1)
11.1.1 Introduction to Industry 4.0
266(1)
11.1.2 Introduction to IoT
266(1)
11.1.3 Introduction to IIoT
267(1)
11.2 How IIoT Advances Industrial Engineering in Industry 4.0 Era
267(1)
11.3 IoT and its Current Applications
268(2)
11.3.1 Home Automation
268(1)
11.3.2 Wearables
269(1)
11.3.3 Connected Cars
269(1)
11.3.4 Smart Grid
269(1)
11.4 Application Areas of IIoT
270(2)
11.4.1 IIoT in Healthcare
270(1)
11.4.2 IIoT in Mining
270(1)
11.4.3 IIoT in Agriculture
271(1)
11.4.4 IIoT in Aerospace
271(1)
11.4.5 IIoT in Smart Cities
272(1)
11.4.6 IIoT in Supply Chain Management
272(1)
11.5 Challenges of Existing Systems
272(1)
11.5.1 Security
272(1)
11.5.2 Integration
273(1)
11.5.3 Connectivity Issues
273(1)
11.6 Future Advancements
273(2)
11.6.1 Data Analytics in IoT
274(1)
11.6.2 Edge Computing
274(1)
11.6.3 Secured IoT Through Blockchain
274(1)
11.6.4 A Fusion of AR and IoT
275(1)
11.6.5 Accelerating IoT Through 5G
275(1)
11.7 Case Study of DeWalt
275(1)
11.8 Conclusion
276(1)
References
276(5)
12 Reliance on Artificial Intelligence, Machine Learning and Deep Learning in the Era of Industry 4.0 281(20)
T. Venkat Narayana Rao
Akhila Gaddam
Muralidhar Kurni
K. Saritha
12.1 Introduction to Artificial Intelligence
282(4)
12.1.1 History of AI
282(1)
12.1.2 Views of AI
282(1)
12.1.3 Types of AI
283(1)
12.1.4 Intelligent Agents
284(2)
12.2 AI and its Related Fields
286(3)
12.3 What is Industry 4.0?
289(1)
12.4 Industrial Revolutions
289(2)
12.4.1 First Industrial Revolution (1765)
290(1)
12.4.2 Second Industrial Revolution (1870)
290(1)
12.4.3 Third Industrial Revolution (1969)
290(1)
12.4.4 Fourth Industrial Revolution
291(1)
12.5 Reasons for Shifting Towards Industry 4.0
291(1)
12.6 Role of AI in Industry 4.0
292(1)
12.7 Role of ML in Industry 4.0
292(1)
12.8 Role of Deep Learning in Industry 4.0
293(1)
12.9 Applications of AI, ML, and DL in Industry 4.0
294(1)
12.10 Challenges
295(1)
12.11 Top Companies That Use AI to Augment Manufacturing Processes in the Era of Industry 4.0
296(1)
12.12 Conclusion
297(1)
References
297(4)
13 The Implementation of AI and AI-Empowered Imaging System to Fight Against COVID-19-A Review 301(12)
Sanjay Chakraborty
Lopamudra Dey
13.1 Introduction
302(2)
13.2 AI-Assisted Methods
304(3)
13.2.1 AI-Driven Tools to Diagnose COVID-19 and Drug Discovery
304(2)
13.2.2 AI-Empowered Image Processing to Diagnosis
306(1)
13.3 Optimistic Treatments and Cures
307(1)
13.4 Challenges and Future Research Issues
308(1)
13.5 Conclusion
308(1)
References
309(4)
14 Implementation of Machine Learning Techniques for the Analysis of Transmission Dynamics of COVID-19 313(38)
C. Vijayalakshmi
S. Bangusha Devi
14.1 Introduction
314(1)
14.2 Data Analysis
315(1)
14.3 Methodology
315(5)
14.3.1 Linear Regression Model
315(3)
14.3.2 Time Series Model
318(2)
14.4 Results and Discussions
320(28)
14.4.1 Model Estimation and Studying its Adequacy
323(7)
14.4.2 Regression Model for Daily New Cases and New Deaths
330(18)
14.5 Conclusions
348(1)
References
348(3)
Index 351
SK Hafizul Islam received his PhD degree in Computer Science and Engineering in 2013 from the Indian Institute of Technology [ IIT (ISM)] Dhanbad, Jharkhand, India. He is an assistant professor in the Department of Computer Science and Engineering, Indian Institute of Information Technology Kalyani (IIIT Kalyani), West Bengal, India. He has authored or coauthored 110 research papers in journals and conference proceedings.

Debabrata Samanta is an assistant professor in the Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India. He obtained his PhD in Computer Science and Engg. from the National Institute of Technology, Durgapur, India, in the area of SAR Image Processing. He is the owner of 17 Indian patents and has authored and coauthored more than 135 research papers in international journals.
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