A lightweight machine learning approach for DDoS detection and classification. [PDF]
Sci RepEbrahem O, Dowaji S, Alhammoud S.
europepmc +1 more source
SH-IDS: a resilient self-healing intrusion detection framework against DoS and DDoS attacks in IoT systems. [PDF]
Sci RepFatima M, Rehman O, Jhanjhi NZ, Ali S.
europepmc +1 more source
Machine learning based approach to intrusion detection in internet of things environments. [PDF]
Front Artif IntellAkinbowale OE +3 more
europepmc +1 more source
Deep learning-based HTTP TRACE flood detection in wireless sensor network using deep spectral multi-layer convolutional neural network. [PDF]
Sci RepTamilselvi S +3 more
europepmc +1 more source
DDoS: Ett evolverande fenomen / DDoS: An evolving phenomenon
, 2012 Internetfenomenet ”Distributed Denial of Service”, förkortat DDoS, beskrivs ofta som ett av destörsta hoten mot Internet idag. Genom att utnyttja den grundläggande strukturen i kommunikationmellan nätverk och datorer kan kriminella blockera och stänga ute webbplatser och -tjänster frånanvändare, samtidigt som det är mycket svårt för offret och ...
openaire +1 more source
Hybrid Ant-Baby Optimizer and BiLSTM framework for high-performance IoT intrusion detection. [PDF]
Front Artif IntellBalakrishnan A, Maddikunta PKR.
europepmc +1 more source
A Survey of Emerging DDoS Threats in New Power Systems. [PDF]
Sensors (Basel)Luo F, Fan S, Shao G.
europepmc +1 more source
Identification and detection of DDoS attack on smart home infrastructure using machine learning models. [PDF]
Sci RepRaja TV +4 more
europepmc +1 more source
An efficient three-tier defense mechanism for mitigation of DDoS attack with port connection analysis in SDN. [PDF]
Sci RepRajper A +5 more
europepmc +1 more source
Retraction Note: Strengthening network DDOS attack detection in heterogeneous IoT environment with federated XAI learning approach. [PDF]
Sci RepAlmadhor A +4 more
europepmc +1 more source