Refined LSTM Based Intrusion Detection for Denial-of-Service Attack in Internet of Things

Keyphrases

• Benchmark Dataset 25%
• CICIDS2017 25%
• Classification Metrics 25%
• Connected Devices 50%
• Cyber-attacks 25%
• Data Injection 50%
• Data Poisoning Attack 25%
• Deep Learning 25%
• Dimensionality Reduction 25%
• Distributed Denial of Service (DDoS) 100%
• Domain Expertise 25%
• Ease of Communication 25%
• Feature Extraction 50%
• Internet of Things 100%
• Internet of Things Networks 100%
• Intrusion Detection 100%
• Intrusion Detection System 100%
• Intrusion Prevention System 25%
• Long Short-term Memory 25%
• Machine Learning Techniques 25%
• Poor Performance 25%
• Preprocessing Techniques 25%
• Promising Technology 25%
• Security Issues 50%
• Security Measures 25%
• Security Solutions 25%
• Security Vulnerabilities 25%
• Smart Devices 25%
• Smart Objects 25%
• Systems-based 25%
• Traditional Machine Learning 25%

Computer Science

• Connected Device 25%
• Cyber Attack 12%
• Deep Learning Method 12%
• Denial-of-Service 100%
• Denial-of-Service Attack 37%
• Dimensionality Reduction 12%
• Domain Expertise 12%
• Experimental Result 12%
• Feature Extraction 25%
• Internet-Of-Things 100%
• Intrusion Detection 100%
• Intrusion Detection System 50%
• Intrusion Prevention Systems 12%
• Learning Approach 12%
• Learning System 12%
• Long Short-Term Memory Network 100%
• Machine Learning 12%
• Preprocessing 12%
• Security Challenge 25%
• Security Measure 12%
• Security Solution 12%
• Security Vulnerability 12%