I agree that this site is using cookies. You can find further informations
here
.
X
Login
Merkliste (
0
)
Home
About us
Home About us
Our history
Profile
Press & public relations
Friends
The library in figures
Exhibitions
Projects
Training, internships, careers
Films
Services & Information
Home Services & Information
Lending and interlibrary loans
Returns and renewals
Training and library tours
My Account
Library cards
New to the library?
Download Information
Opening hours
Learning spaces
PC, WLAN, copy, scan and print
Catalogs and collections
Home Catalogs and Collections
Rare books and manuscripts
Digital collections
Subject Areas
Our sites
Home Our sites
Central Library
Law Library (Juridicum)
BB Business and Economics (BB11)
BB Physics and Electrical Engineering
TB Engineering and Social Sciences
TB Economics and Nautical Sciences
TB Music
TB Art & Design
TB Bremerhaven
Contact the library
Home Contact the library
Staff Directory
Open access & publishing
Home Open access & publishing
Reference management: Citavi & RefWorks
Publishing documents
Open Access in Bremen
zur Desktop-Version
Toggle navigation
Merkliste
1 Ergebnisse
1
Deep Learning Approaches for Intrusion Detection with Emerg..:
, In:
2023 International Conference on Sustainable Communication Networks and Application (ICSCNA)
,
Hemalatha, S.
;
Mahalakshmi, M.
;
Vignesh, V.
... - p. 1522-1529 , 2023
Link:
https://doi.org/10.1109/ICSCNA58489.2023.10370556
RT T1 <cTitle>2023 International Conference on Sustainable Communication Networks and Application (ICSCNA)</cTitle>: T1 <Title>Deep Learning Approaches for Intrusion Detection with Emerging Cybersecurity Challenges</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10370556&Exemplar=1&LAN=DE A1 Hemalatha, S. A1 Mahalakshmi, M. A1 Vignesh, V. A1 Geethalakshmi, M. A1 Balasubramanian, D. A1 Anand A., Jose YR 2023 K1 Deep learning K1 Recurrent neural networks K1 Intrusion detection K1 Network security K1 Denial-of-service attack K1 Computer networks K1 Convolutional neural networks K1 Intrusion detection system K1 DDoS attacks K1 Machine Learning K1 Distributed denial-of-service (DDoS) SP 1522 OP 1529 LK http://dx.doi.org/https://doi.org/10.1109/ICSCNA58489.2023.10370556 DO https://doi.org/10.1109/ICSCNA58489.2023.10370556 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
