Application of Rough Sets to Negative Selection Algorithms
- Resource Type
- Authors
- Andrzej Chmielewski
- Source
- Future Data and Security Engineering ISBN: 9783319700038
FDSE
- Subject
- Negative selection algorithm
Artificial immune system
Computer science
Dominance-based rough set approach
computer.software_genre
03 medical and health sciences
Negative selection
0302 clinical medicine
030221 ophthalmology & optometry
Feature (machine learning)
Anomaly detection
030212 general & internal medicine
Data mining
Rough set
computer
- Language
Immune-based algorithms are mainly used for detecting anomalies in datasets from various domains. However, one of the main areas in which they are applied is computer security. Due to increased number of victim connections, a new effective approaches still are needed. Negative Selection Algorithms seem to be very interesting as they have a unique feature which allow for detecting new type of attacks. This paper presents the possibility of applying the rough sets inspirations to improve its efficiency and deal with uncertainty and inconsistency in data.