Hiding Intrusions: From the Abnormal to the Normal and Beyond

By Kymie M. C. Tan, John McHugh, Kevin S. Killourhy. 2002

97 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems, Signal Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Blaine Nelson
2. Battista Biggio
3. Fabio Roli
4. Anthony D. Joseph
5. David A. Wagner
6. Marco Barreno
7. Paolo Soto
8. Pavel Laskov

In Information Systems

1. Blaine Nelson
2. Battista Biggio
3. Marco Barreno
4. David A. Wagner
5. Anthony D. Joseph
6. Fabio Roli
7. Xiaojin Zhu
8. Nicolas Papernot

In Signal Processing

1. Blaine Nelson
2. Battista Biggio
3. Fabio Roli
4. David A. Wagner
5. Anthony D. Joseph
6. Nicholas Carlini
7. Marco Barreno
8. Paolo Soto

Citations in the corpus

• The security of machine learning (2010, background): “In subsequent work Tan et al. (2003) characterize their attacks as part of a larger class of information hiding techniques which they demonstrate can make exploits mimic either normal call sequences or the call sequence of another less severe exploit.”
• A framework for the evaluation of intrusion detection systems (2006, unknown): “Several researchers have pointed out the need to include the resistance against attacks as part of the evaluation of an IDS [25, 27, 11, 34, 29, 30, 13].”
• Mimicry attacks on host-based intrusion detection systems (2002, background): “In this sense, the very suc­cess of an approach for intrusion detection may lead to its own downfall, if the approach is not secure against evasion attacks.”