Title
AL-DDoS attack detection optimized with genetic algorithms
Date Issued
01 January 2018
Access level
metadata only access
Resource Type
conference paper
Publisher(s)
Springer Verlag
Abstract
Application Layer DDoS (AL-DDoS) is a major danger for Internet information services, because these attacks are easily performed and implemented by attackers and are difficult to detect and stop using traditional firewalls. Managing to saturate physically and computationally the information services offered on the network. Directly harming legitimate users, to deal with this type of attacks in the network layer previous approaches propose to use a configurable statistical model and observed that when being optimized in various configuration parameters Using Genetic Algorithms was able to optimize the effectiveness to detect Network Layer DDoS (NL-DDoS), however this method is not enough to stop DDoS at the level of application because this level presents different characteristics, that is why we propose a new method Configurable and optimized for different scenarios of Attacks that effectively detect AL-DDoS.
Start page
107
End page
117
Volume
10632 LNAI
Language
English
OCDE Knowledge area
Ciencias de la computación Ciencias de la información
Scopus EID
2-s2.0-85059943641
Source
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Resource of which it is part
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN of the container
03029743
ISBN of the container
9783030028367
Conference
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Sources of information: Directorio de Producción Científica Scopus