A Distributed Denial of Service (DDoS) attack is an attempt to make a service unavailable by overwhelming the server with malicious traffic. DDoS attacks have become the most tedious and cumbersome issue in recent past. The number and magnitude of attacks have increased from few megabytes of data to 100s of terabytes of data these days.
null Dhananjay Tangtode +4 more
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The subject matter of this article is the methods to detect distributed denial-of-service (DDoS) attacks at the Hypertext Transfer Protocol (HTTP) level with the purpose of justifying the requirements for creating software capable of identifying ...
Arkadii Kravchuk, Mykola Onai
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Vietnēm katra cilvēka mūsdienu dzīvē ir liela nozīme. Internetā ir iespējams atrast jebkuru informāciju un saņemt jebkuru pakalpojumu. Tagad tiešsaistē ir daudz darījumu: piemēram, pārtikas pārdošana, tiešsaistes izglītība, izklaide utt. Taču, tāpat kā jebkurā biznesā, arī internetā valda liela konkurence.
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Deep learning-based HTTP TRACE flood detection in wireless sensor network using deep spectral multi-layer convolutional neural network. [PDF]
Tamilselvi S +3 more
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Retraction Note: Strengthening network DDOS attack detection in heterogeneous IoT environment with federated XAI learning approach. [PDF]
Almadhor A +4 more
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An efficient three-tier defense mechanism for mitigation of DDoS attack with port connection analysis in SDN. [PDF]
Rajper A +5 more
europepmc +1 more source
Identification and detection of DDoS attack on smart home infrastructure using machine learning models. [PDF]
Raja TV +4 more
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A hybrid machine learning approach for detecting DDoS attacks in software-defined networks. [PDF]
Mahar IA +5 more
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DDoS Detection using Deep Learning
Deepak Kumar +4 more
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Optimized CatBoost machine learning (OCML) for DDoS detection in cloud virtual machines with time-series and adversarial robustness. [PDF]
Samy H, Bahaa-Eldin AM, Sobh MA, Taha A.
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