Machine Learning in Cyber Trust Security, Privacy, and Reliability /
Many networked computer systems are far too vulnerable to cyber attacks that can inhibit their functioning, corrupt important data, or expose private information. Not surprisingly, the field of cyber-based systems turns out to be a fertile ground where many tasks can be formulated as learning proble...
Συγγραφή απο Οργανισμό/Αρχή: | |
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Άλλοι συγγραφείς: | , |
Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
Γλώσσα: | English |
Έκδοση: |
Boston, MA :
Springer US,
2009.
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Θέματα: | |
Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- Cyber System
- Cyber-Physical Systems: A New Frontier
- Security
- Misleading Learners: Co-opting Your Spam Filter
- Survey of Machine Learning Methods for Database Security
- Identifying Threats Using Graph-based Anomaly Detection
- On the Performance of Online Learning Methods for Detecting Malicious Executables
- Efficient Mining and Detection of Sequential Intrusion Patterns for Network Intrusion Detection Systems
- A Non-Intrusive Approach to Enhance Legacy Embedded Control Systems with Cyber Protection Features
- Image Encryption and Chaotic Cellular Neural Network
- Privacy
- From Data Privacy to Location Privacy
- Privacy Preserving Nearest Neighbor Search
- Reliability
- High-Confidence Compositional Reliability Assessment of SOA-Based Systems Using Machine Learning Techniques
- Model, Properties, and Applications of Context-Aware Web Services.