| Technical Name | Cyber Security Vulnerabilities Alert System Based on Information from TwitterCVE | ||
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| Project Operator | Taiwan Information Security Center at National Chung Hsing University | ||
| Project Host | 廖宜恩 | ||
| Summary | The proposed system uses Convolutional Neural Networks (CNN)Bidirectional Long Short-Term Memory (Bi-LSTM) to analyze the tweets by cyber security expertsthe information from Common VulnerabilitiesExposures (CVE) on an hourly basisautomatically check the system profile including firmware, OS,application software for possible vulnerabilities. It will send alert messages to |
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| Scientific Breakthrough | The proposed system uses CNN-CNN-BiLSTM to analyze the tweets by cyber security expertsthe information from Common VulnerabilitiesExposures (CVE) on an hourly basisautomatically check the system profile including firmware, OS,application software for possible vulnerabilities. It will send alert messages to system administrator for taking appropriate actions to avoid zero-day/N- |
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| Industrial Applicability | Using hourly accesses to the tweets by cyber security expertsthe information from CVE as cyber security information source, the proposed system can automatically check the system profile including firmware, OS,application software for possible vulnerabilities. It will send alert messages to system administrator for taking appropriate actions to avoid zero-day/N-day attacks once potential |
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| Keyword | Deep Neural Network Convolutional Neural Network Bi-LSTM Named Entity Recognition Cyber Security Vulnerability Twitter CVE 0-day attack N-day attack Vulnerabilities Alert System | ||
| Notes | |||
- Contact
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