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» Intrusion Detection with Neural Networks
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KDD
2003
ACM
155views Data Mining» more  KDD 2003»
14 years 8 months ago
Graph-based anomaly detection
Anomaly detection is an area that has received much attention in recent years. It has a wide variety of applications, including fraud detection and network intrusion detection. A ...
Caleb C. Noble, Diane J. Cook
NDSS
2003
IEEE
14 years 1 months ago
A Virtual Machine Introspection Based Architecture for Intrusion Detection
Today’s architectures for intrusion detection force the IDS designer to make a difficult choice. If the IDS resides on the host, it has an excellent view of what is happening i...
Tal Garfinkel, Mendel Rosenblum
ISCC
2006
IEEE
256views Communications» more  ISCC 2006»
14 years 2 months ago
A Wireless Distributed Intrusion Detection System and a New Attack Model
Denial-of-Service attacks, and jamming in particular, are a threat to wireless networks because they are at the same time easy to mount and difficult to detect and stop. We propo...
Marco Domenico Aime, Giorgio Calandriello, Antonio...
CHI
2007
ACM
14 years 7 days ago
Command line or pretty lines?: comparing textual and visual interfaces for intrusion detection
Intrusion detection (ID) is one of network security engineers' most important tasks. Textual (command-line) and visual interfaces are two common modalities used to support en...
Ramona Su Thompson, Esa M. Rantanen, William Yurci...
FCCM
2004
IEEE
133views VLSI» more  FCCM 2004»
13 years 12 months ago
A Methodology for Synthesis of Efficient Intrusion Detection Systems on FPGAs
Intrusion detection for network security is a computation intensive application demanding high system performance. System level design, a relatively unexplored field in this area,...
Zachary K. Baker, Viktor K. Prasanna