dc.contributor.author | Padmasiri, MAT | |
dc.contributor.author | Ganepola, VVV | |
dc.contributor.author | Herath, RKHMSD | |
dc.contributor.author | Welagedara, LP | |
dc.contributor.author | Ganepola, GANS | |
dc.contributor.author | Vekneswaran, P | |
dc.date.accessioned | 2020-12-31T23:13:07Z | |
dc.date.available | 2020-12-31T23:13:07Z | |
dc.date.issued | 2020 | |
dc.identifier.uri | http://ir.kdu.ac.lk/handle/345/3036 | |
dc.description.abstract | Where world is moving towards
digitalization, it is crucial that network
intrusions detection and prevention is
addresses in ordered to create a secured
network. This paper covers why deep
learning was considered and what are the
deep learning approaches for network
intrusion detection. For each approach the
challenges, missed elements and the unique
features that are found in current domain
state are also highlighted. As a conclusion
this paper highlights why CNN and LSTM
would be successful approach for intrusion
detection and why in the current domain
context it is required to create scalable
solution with both intrusion detection and
prevention involved. | en_US |
dc.language.iso | en | en_US |
dc.subject | Network Intrusion Detection and Prevention System | en_US |
dc.subject | Deep Learning | en_US |
dc.subject | NSLKDD | en_US |
dc.title | Survey on Deep learning based Network Intrusion Detection and Prevention Systems | en_US |
dc.type | Article Full Text | en_US |
dc.identifier.journal | 13th International Research Conference General Sir John Kotelawala Defence University | en_US |
dc.identifier.pgnos | 427-436 | en_US |