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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Yu, Philip S. (Επιμελητής έκδοσης), Tsai, Jeffrey J. P. (Επιμελητής έκδοσης)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Boston, MA : Springer US, 2009.
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.