Semi-supervised K-means DDoS detection method using hybrid feature selection algorithm
Y Gu, K Li, Z Guo, Y Wang - IEEE Access, 2019 - ieeexplore.ieee.org
Distributed denial of service (DDoS) attack is an attempt to make an online service
unavailable by overwhelming it with traffic from multiple sources. Therefore, it is necessary to …
unavailable by overwhelming it with traffic from multiple sources. Therefore, it is necessary to …
Advanced support vector machine‐(ASVM‐) based detection for distributed denial of service (DDoS) attack on software defined networking (SDN)
M Myint Oo, S Kamolphiwong… - Journal of Computer …, 2019 - Wiley Online Library
Software Defined Networking (SDN) has many advantages over a traditional network. The
great advantage of SDN is that the network control is physically separated from forwarding …
great advantage of SDN is that the network control is physically separated from forwarding …
Privacy-preserving DDoS attack detection using cross-domain traffic in software defined networks
Existing distributed denial-of-service attack detection in software defined networks (SDNs)
typically perform detection in a single domain. In reality, abnormal traffic usually affects …
typically perform detection in a single domain. In reality, abnormal traffic usually affects …
DDoS attack detection with feature engineering and machine learning: the framework and performance evaluation
M Aamir, SMA Zaidi - International Journal of Information Security, 2019 - Springer
This paper applies an organized flow of feature engineering and machine learning to detect
distributed denial-of-service (DDoS) attacks. Feature engineering has a focus to obtain the …
distributed denial-of-service (DDoS) attacks. Feature engineering has a focus to obtain the …
An efficient multilevel probabilistic model for abnormal traffic detection in wireless sensor networks
Wireless sensor networks (WSNs) are low-cost, special-purpose networks introduced to
resolve various daily life domestic, industrial, and strategic problems. These networks are …
resolve various daily life domestic, industrial, and strategic problems. These networks are …
DDoS attack detection in smart grid network using reconstructive machine learning models
SSA Naqvi, Y Li, M Uzair - PeerJ Computer Science, 2024 - peerj.com
Network attacks pose a significant challenge for smart grid networks, mainly due to the
existence of several multi-directional communication devices coupling consumers to the …
existence of several multi-directional communication devices coupling consumers to the …
Xatu: Boosting existing DDoS detection systems using auxiliary signals
Traditional DDoS attack detection monitors volumetric traffic features to detect attack onset.
To reduce false positives, such detection is often conservative---raising an alert only after a …
To reduce false positives, such detection is often conservative---raising an alert only after a …
A secure framework to prevent three-tier cloud architecture from malicious malware injection attacks
The concept of cloud computing makes it possible to have a shared pool of reconfigurable
computing resources that can be deployed and released with little involvement from …
computing resources that can be deployed and released with little involvement from …
[PDF][PDF] Seleksi Fitur Dengan Information Gain Untuk Meningkatkan Deteksi Serangan DDoS menggunakan Random Forest
Tantangan deteksi serangan saat ini adalah jumlah trafik yang besar dan beragam serta
hadir jenis serangan baru. Disisi lain, pesatnya pertumbuhan teknologi layanan komunikasi …
hadir jenis serangan baru. Disisi lain, pesatnya pertumbuhan teknologi layanan komunikasi …
An efficient fog-based attack detection using ensemble of MOA-WMA for Internet of Medical Things
Smart healthcare applications such as smart fitness, smart watches, and elderly remote
monitoring devices have reduced the load on traditional healthcare organizations and led to …
monitoring devices have reduced the load on traditional healthcare organizations and led to …