Pubbl/distr/stampa |
Cham, Switzerland : , : Springer, , [2022]
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Descrizione fisica |
1 online resource (248 pages)
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Disciplina |
621.38456
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Collana |
EAI/Springer Innovations in Communication and Computing
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Soggetto topico |
5G mobile communication systems - Security measures
Internet of things - Security measures
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ISBN |
3-030-79766-X
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Formato |
Materiale a stampa ![](img/format/mas.png) |
Livello bibliografico |
Monografia |
Lingua di pubblicazione |
eng
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Nota di contenuto |
Intro -- Preface -- Contents -- Chapter 1: Security Challenges in 5G and IoT Networks: A Review -- 1.1 Introduction -- 1.2 Technologies for Securing 5G-Based IoT Networks -- 1.2.1 Authentication and Access Control -- 1.2.2 Blockchain-Based Security -- 1.2.3 Machine Learning and Big Data-Based Security -- 1.2.4 Cryptographic Algorithms-Based Security -- 1.2.5 Security in Software-Defined Framework and Virtualization -- 1.2.6 Adaptive Security Approaches -- 1.3 Securing the 5G-Based IoT Applications -- 1.3.1 Securing the Smart Grid -- 1.3.2 Securing the Smart Home -- 1.3.3 Securing the Intelligent UAV -- 1.3.4 Securing the VANET -- 1.3.5 Securing the Smart City -- 1.3.6 Securing the Smart Factory -- 1.3.7 Securing the Smart Health -- 1.3.8 Security in Other Applications -- Financial Innovation -- Environment -- Smart Agriculture -- 1.4 Research Challenges in Securing 5G-IoT Networks -- 1.4.1 Challenges Related to 5G-IoT Architecture -- 1.4.2 Challenges Related to Blockchain Technologies -- 1.4.3 Challenges Related to Energy -- 1.4.4 Challenges Related to Artificial Intelligence -- 1.4.5 Challenges Related to Software Defined Networks -- 1.5 Conclusion -- References -- Chapter 2: Energy-Efficient Network Routing Protocols for IoT Applications -- 2.1 Introduction -- 2.2 Issues and Challenges in IoT -- 2.3 Classification of Routing Protocols in IoT -- 2.3.1 Packet Forwarding -- 2.3.2 Route Discovery -- 2.3.3 Routing Schemes -- 2.3.4 Routing Operations -- Context-Based Routing -- Content-Based Routing -- Energy-Aware Routing -- Negotiation-Based Routing -- Naive-Based Routing -- Hierarchical Routing -- 2.4 Analysis of Prominent Clustering Routing Protocols -- 2.5 Research Platforms and Tools -- 2.6 Summary and Conclusion -- References -- Chapter 3: Cybersecurity in 5G and IoT Networks -- 3.1 Introduction to 5G and IoT -- 3.1.1 Overview of 5G and IoT.
3.2 Requirements of 5G and IoT -- 3.2.1 Architecture of 5G and IoT -- 3.3 Crowdsourcing Use Cases and Evolution to 5G IoT Cybersecurity -- 3.3.1 Use Case for Commercial Purpose -- 3.3.2 Mitigation of Physical Attacks -- 3.3.3 Collaboration Among End Users -- 3.4 Crowdsourcing for 5G IoT Cybersecurity -- 3.4.1 IoT Devices in 5G-A Capillary Network -- 3.4.2 Dynamic Ran Enablers in 5G IoT -- 3.5 Entity-Based Crowdsourcing Model -- 3.5.1 Applying the End-User Collaboration Crowdsourcing Model -- Users or Service Providers -- D2D Devices for 5G Infrastructure -- Digital Witness-LEA's -- 3.6 Business Model and Cybersecurity -- 3.6.1 Need for Cybersecurity in 5G IoT -- 3.7 Uses and Benefits of 5G IoT in Smart Grid -- 3.7.1 Uses of 5G IoT in Smart Grid -- 3.7.2 Advantages of 5G IoT in Smart Grid -- Advanced Metering Infrastructure (AMI) -- Improved Reliability of Power System -- SMADA (Supervisory Monitoring and Data Acquisition) Improved Functions -- 3.8 Cybersecurity Challenges in 5G IoT -- 3.8.1 Classification of Recent Attacks -- Device Attack -- Data Attack -- Privacy Attack -- Network Attack -- 3.8.2 Classification of Recent Attacks -- Access Control -- Encryption -- Authentication -- Intrusion Detection System (IDS) -- 3.9 Major Challenges Hindering the Growth of 5G and IoT Networks -- 3.9.1 Standardization of 5G IoT Protocols -- 3.9.2 Cognitive Capability in 5G IoT -- 3.9.3 High Speed 5G Networks -- 3.9.4 Privacy Issues -- 3.10 IoT Based Security Management System -- 3.10.1 Cybersecurity Oriented IoT Architecture -- 3.10.2 Cybersecurity Attacks on IoT -- 3.10.3 Attack Taxonomy -- 3.11 Key Applications of 5G and IoT in Industries -- 3.11.1 Smart Grid Applications -- 3.11.2 Tactile Robots -- 3.11.3 Heterogeneous Networks (HtNet) -- 3.11.4 5G and IoT Applications in Smart Cities Deployment -- References -- Chapter 4: 5G and IoT Networks Risk Management.
4.1 Introduction -- 4.2 5G and IoT Risk Administration -- 4.2.1 5G and IoT Security Controls -- Network Security for 5G and IoT -- Protected System Services -- Transport Risk Procedure -- Information and Solitude -- Solitude Anxiety -- Protect Firmware for IoT Devices -- Physical Safety -- Individuality Administration -- 4.3 Healthcare Environment Risk Management -- 4.3.1 IoT Healthcare Components and Its Risks -- 4.3.2 Clinical Technology Risk Factors -- Unconstrained Failures -- Detachment Violations -- Masterminded Trouble -- Customary Disruption -- 4.3.3 5G with IoT Medical Devices Risk Management -- 4.3.4 Thriving, Security, and Usefulness of 5G with IoT Medical Devices Risk Management -- Build Security into Devices from the Outset Rather Than as an Afterthought -- Make 5G and IoT Relationship -- 4.4 IoT Cyber Risk Management -- 4.4.1 IoT Architecture Cyber Risk -- Recognition Layer -- Organization Layer -- Agreement Layer -- Application Layer -- 4.4.2 Cyber Risk Management Review -- Predominance Approaches -- Greatness Approaches -- 4.4.3 IoT Cyber Risk Management Framework -- IoT Cyber Ecosystem Layer -- Foundation Layer -- Assessment Layer -- 4.5 Smart Home Applications Risk Management -- 4.5.1 Appreciate the Smart Home Risks -- Clever Home Technology Precautions -- Three Potential Dangers Related to Clever Home Development Are -- Smart Home Systems Leave You as Unapproved -- Devices Can Leave You as Vulnerability -- Shortcoming Devices Will Leave You as -- 4.5.2 Two or Three Key Ways to Deal with Stay Before Extortion Chances Include -- Remain Safe, Stay Safe... -- Directed Attacks -- Data Fraud -- Secret Word Exploitation -- Area Tracking -- Home Intrusions -- Machine or Property Damage -- Rebel Recordings -- Outsider Flaws -- Information Manipulation -- Obsolete Software -- 4.5.3 Savvy Cities 5G and IoT Risk Management.
Safety Risks in Smart Cities -- Risk Factors -- Advancement Limitations -- Vulnerable Implementation -- 4.5.4 Hazards and Countermeasures -- Man-in-the-Center -- Information and Rebate Deception -- Gadget Getting -- Streamed Denial of Service (DDoS) -- Suffering Denial of Service (PDoS) -- References -- Chapter 5: Machine Learning IDS Models for 5G and IoT -- 5.1 Introduction -- 5.1.1 Internet of Things (IoT) -- 5.1.2 5G Technology -- 5.1.3 Intrusion Detection System (IDS) -- 5.2 Machine Learning and IDS -- 5.3 Literature Review of Algorithmic Approach to IoT and 5G -- 5.4 Conclusion -- References -- Chapter 6: Industrial Automation of IoT in 5G Era -- 6.1 Introduction -- 6.2 Increased Growth in the IoT Market -- 6.3 IOT Market Overview -- 6.3.1 By Platform -- 6.3.2 By Technology -- 6.3.3 By Component -- 6.3.4 By Application -- 6.3.5 By Region -- 6.4 Industry Digitization with IoT -- 6.4.1 Massive IoT -- 6.4.2 Broadband IoT -- 6.4.3 Critical IoT -- 6.4.4 Industrial IoT -- 6.5 Industrial IOT in a Context of Industrial Transformation -- 6.6 Mapping Industrial IoT to 5G Era -- 6.7 Conclusion -- References -- Chapter 7: IoT-Based Ensemble Method on PCG Signal Classification to Predict Heart Diseases -- 7.1 Introduction -- 7.2 Related Work -- 7.3 Proposed Heartbeat Classification Method -- 7.3.1 Dataset -- 7.3.2 Separation of s1 and s2 -- 7.3.3 Denoising -- 7.3.4 Peak Identification -- 7.3.5 Extracting Feature from PCG Signal -- 7.4 Mel-Frequency Cepstral Coefficients -- 7.4.1 MFCC Feature Extraction Algorithm -- 7.4.2 Support Vector Machine (SVM) -- 7.4.3 K Nearest Neighbor (KNN) -- 7.4.4 Ensemble Methods -- 7.4.5 Bootstrap Aggregate (Bagging) -- 7.4.6 Boosting -- 7.4.7 Evaluation Metrics -- 7.5 Result and Discussions -- 7.6 Conclusion -- References.
Chapter 8: IoT-Based Model Predictive Control Architecture for HVAC Systems and a Comprehensive Study of Security Issues of 5G and IoT -- 8.1 Introduction -- 8.2 Historical Perspective -- 8.3 MPC Typologies -- 8.3.1 Classical Model Predictive Control -- 8.3.2 Predictive Control Robust Model (RMPC) -- 8.3.3 Predictive Regulation of the Stochastic Model (SMPC) -- 8.3.4 Nonlinear Model Predictive Control (NMPC) -- 8.3.5 Predictive Management Explicit Model -- 8.4 Model Predictive Control Overview -- 8.5 Model Predictive Control in HVAC Buildings -- 8.6 MPC Models in Building and HVAC Systems -- 8.6.1 Modeling of the HVAC System and the House -- 8.6.2 IoT-Based Architecture for an HVAC System -- 8.7 Advantages and Disadvantages of Model Predictive Control -- 8.8 5G and IoT Security Issues -- 8.9 Conclusion -- References -- Chapter 9: Adaptive Multimode Decision Tree Classification Model Using Effective System Analysis in IDS for 5G and IoT Security Issues -- 9.1 Introduction -- 9.2 Related Works -- 9.3 Materials and Methods -- 9.3.1 Multimode Decision Tree Classification -- 9.3.2 Algorithm: Multimode Decision Tree Classification Model (MDTC) -- 9.3.3 Data Collection -- 9.3.4 Data Monitoring -- 9.3.5 Traffic and Network Management -- 9.3.6 Intrusion Detection System -- 9.4 Result and Discussion -- 9.4.1 Testing Systems -- 9.4.2 Traffic Bags -- 9.4.3 CPU and Memory Performance -- 9.4.4 Storage Performance -- 9.4.5 Threat Perception -- 9.5 Conclusion -- References -- Chapter 10: Enhanced Role-Based Handover Control Algorithm for Efficient Multimedia Data Communication Performance in Vehicular Network Using IoT Security Issues -- 10.1 Introduction -- 10.2 Related Work -- 10.3 Materials and Methods -- 10.3.1 Store-and-Forward (SF) Scheme -- Encryption for Video Broadcasting -- Decryption for the Video Broadcasting.
10.3.2 Vertical Handover Process Based on ERBHC.
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Record Nr. | UNINA-9910522996503321 |