Machine Learning and Deep Learning-Based Multi-Attribute Physical-Layer Authentication for Spoofing Detection in LoRaWAN

Keyphrases

• Deep Learning Methods 100%
• Deep Machine Learning 100%
• Machine Learning Learning 100%
• Spoofing Detection 100%
• Long Range Wide Area Network (LoRaWAN) 100%
• Physical Layer Authentication 100%
• Multi-attribute 100%
• Machine Learning Models 66%
• Convolutional Neural Network 66%
• Multilayer Perceptron 66%
• Received Signal Strength Indicator 66%
• Battery Level 66%
• Environmental Monitoring 33%
• Deep Learning Model 33%
• Logistic Regression 33%
• Wireless Communication 33%
• Authentication Mechanism 33%
• Smart Agriculture 33%
• Resource Demand 33%
• Physical Attributes 33%
• K-nearest 33%
• Key Risks 33%
• Wireless Sensor Networks 33%
• Indicator Value 33%
• Encryption 33%
• Wireless Security 33%
• Random Forest 33%
• Security Concerns 33%
• Forest Fire Detection 33%
• Regression Forest 33%
• Spoofing 33%
• Competitive Performance 33%
• Industrial Automation 33%
• Data Authenticity 33%
• Authentication Scheme 33%
• Join Procedure 33%
• Smart Industrial Environment 33%
• Text Transmission 33%
• Detection Scenario 33%
• Sensor Behaviour 33%
• Plaintext 33%
• Agricultural Automation 33%
• LoRa 33%

Computer Science

• Machine Learning 100%
• Learning System 100%
• Deep Learning Method 100%
• Authentication 100%
• Physical Layer 100%
• Spoofing 100%
• Random Decision Forest 66%
• Received Signal Strength 66%
• Multilayer Perceptron 66%
• Convolutional Neural Network 66%
• Wireless Sensor Network 66%
• Deep Learning Model 33%
• Wireless Communication 33%
• Authentication Mechanism 33%
• Network Security 33%
• Critical Application 33%
• Logistic Regression 33%
• Security Concern 33%
• Industrial Automation 33%
• Resource Demand 33%
• Indicator Value 33%
• authentication scheme 33%