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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Tsai, Jeffrey J. P. (Editor ), Yu, Philip S. (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York, NY : Springer US : Imprint: Springer, 2009.
Edición:1st ed. 2009.
Temas:
Data protection.
Data mining.
Artificial intelligence.
Data and Information Security.
Data Mining and Knowledge Discovery.
Artificial Intelligence.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • 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.

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