TY - GEN
T1 - Detection of traffic volume anomalies by evolution of negative classifiers in Artificial Immune Systems
AU - Azzini, Antonia
AU - Damiani, Ernesto
AU - Gianini, Gabriele
AU - Marrara, Stefania
PY - 2008
Y1 - 2008
N2 - Traffic volume anomalies can take a wide range of different forms, each characterized in principle by a different traffic profile, but all the forms having in common the overall surge in traffic at a particular site. Often anomalies, at the onset, appear up as innovations, an unprecedented experience for the network system. For this reason it is appropriate to face them with a negative selection approach that can detect foreign patterns in the complement space. In this work we propose to detect the onset of traffic anomalies within the paradigmatic approach of Evolutionary Artificial Immune Systems, through the use of classifiers evolved on the basis of normal traffic profile (the complementary space corresponds to the immune system non-self): the overall architecture can provide robustness and adaptability. The approach discussed here could apply not only to volume anomalies but to traffic anomalies in general
AB - Traffic volume anomalies can take a wide range of different forms, each characterized in principle by a different traffic profile, but all the forms having in common the overall surge in traffic at a particular site. Often anomalies, at the onset, appear up as innovations, an unprecedented experience for the network system. For this reason it is appropriate to face them with a negative selection approach that can detect foreign patterns in the complement space. In this work we propose to detect the onset of traffic anomalies within the paradigmatic approach of Evolutionary Artificial Immune Systems, through the use of classifiers evolved on the basis of normal traffic profile (the complementary space corresponds to the immune system non-self): the overall architecture can provide robustness and adaptability. The approach discussed here could apply not only to volume anomalies but to traffic anomalies in general
KW - Anomaly detection
KW - Artificial immune systems (AIS)
KW - Artificial neural networks (ANNs)
KW - Evolutionary ANN (EANNs)
KW - Negative selection
UR - http://www.scopus.com/inward/record.url?scp=56749102191&partnerID=8YFLogxK
U2 - 10.1109/DEST.2008.4635190
DO - 10.1109/DEST.2008.4635190
M3 - Conference contribution
AN - SCOPUS:56749102191
SN - 1424414903
SN - 9781424414901
T3 - 2008 2nd IEEE International Conference on Digital Ecosystems and Technologies, IEEE-DEST 2008
SP - 270
EP - 273
BT - 2008 2nd IEEE International Conference on Digital Ecosystems and Technologies, IEEE-DEST 2008
T2 - 2008 2nd IEEE International Conference on Digital Ecosystems and Technologies, IEEE-DEST 2008
Y2 - 26 February 2008 through 29 February 2008
ER -