- author = "Sergio Pastrana Portillo",
- title = "Attacks Against Intrusion Detection Networks: Evasion, Reverse Engineering and Optimal Countermeasures",
- school = "Computer Science and Technology, University of Carlos III de Madrid",
- year = "2014",
- address = "Spain",
- month = jun,
- note = "UC3M Outstanding Thesis Award 2013/2014",
- keywords = "genetic algorithms, genetic programming, Intrusion detection networks, Security, Privacy, Anomaly detection, Machine learning, Evasion, Reverse engineering",
-
URL = "
http://hdl.handle.net/10016/20020",
-
URL = "https://e-archivo.uc3m.es/handle/10016/20020",
-
URL = "
http://www.seg.inf.uc3m.es/~spastran/phd/PhD_Thesis_Sergio_Pastrana.pdf",
- size = "216 pages",
- abstract = "Intrusion Detection Networks (IDNs) constitute a primary element in current cyberdefense systems. IDNs are composed of different nodes distributed among a network infrastructure, performing functions such as local detection --mostly by Intrusion Detection Syst",
- abstract = "Las Redes de Deteccion de Intrusiones (IDNs, por sus siglas en ingles) constituyen un elemento primordial de los actuales sistemas de ciberdefensa. Una IDN esta compuesta por diferentes nodos distribuidos a lo largo de una infraestructura de red que realizan",
-
notes = "In English.
p57 'we use Genetic Programming (GP) [Koza, 1992] to obtain an approximation of the decision surface of the actual detection model at the core of the IDS'
Supervised by Agustin Orfila and Juan E. Tapiador",
