Secure Industrial IoT Systems via RF Fingerprinting Under Impaired Channels With Interference and Noise

Keyphrases

• Signal-to-interference Ratio 100%
• Radio Frequency Fingerprinting 100%
• Industrial IoT Systems 100%
• Augmentation Approach 100%
• Transmitter 75%
• Learning Performance 75%
• Deep Learning Model 50%
• Ratio Level 50%
• Signal-to-noise Ratio 50%
• Sensitivity Analysis 50%
• Critical Infrastructure 50%
• Training Data 25%
• Cyber-attacks 25%
• Environmental Conditions 25%
• Channel Condition 25%
• Deep Learning Methods 25%
• Industrial Internet of Things (IIoT) 25%
• Frequency-based Approach 25%
• Deep Machine Learning 25%
• Radio Frequency 25%
• Unseen 25%
• Mission-critical 25%
• Clustered Delay Line 25%
• Security Design 25%
• Tapped Delay Line 25%
• Propagation Channel 25%
• Radio Frequency Identification 25%
• Radio Frequency Data 25%
• Wi-Fi Data 25%
• Identification Accuracy 25%
• Wirelessly 25%
• Delay-line-based 25%
• User Device 25%

Computer Science

• Learning Performance 100%
• Industrial Internet of Things 100%
• Signal-to-Noise plus Interference Ratio 66%
• Deep Learning Model 66%
• Noise-to-Signal Ratio 66%
• Signal to Interference Ratio 66%
• Critical Infrastructure 66%
• Data Instance 33%
• Cyber Attack 33%
• Classifier Structure 33%
• Gathering Data 33%
• Radio Frequency Identification 33%
• Learning Approach 33%
• Channel Condition 33%
• Training Data 33%
• Propagation Channel 33%
• Deep Learning Method 33%

Engineering

• Radio Frequency 100%
• Deep Learning Method 50%
• Interference Ratio 33%
• Electric Delay Lines 33%
• Critical Infrastructure 33%
• Signal-to-Interference-Plus-Noise Ratio 33%
• Signal-to-Noise Ratio 33%
• Learning Approach 16%
• Test Data 16%
• Conducted Experiment 16%
• Cyber Attack 16%
• Channel Condition 16%
• Previously Published Work 16%
• Propagation Channel 16%
• Radio Frequency Identification 16%
• Data Sample 16%