… issues in cloud computing and attacks on cloud. The major security concern in cloud is …
using a profiling system based on supervised learning. In future a profiling system based on …

… Meanwhile, the unsupervised learning for NIDS often fails to give the satisfactory … supervised
learning approach via ensemble learning (FSSLEL) for network intrusion detection on cloud…

… With our observations made from the network traffic analysis, … that the established supervised
learning model based on the … four widely used supervised learning techniques including …

… new learning paradigm, that is, cross-supervised learning, and explore its use for cloud
detection… Based on the cross-supervised learning and the Intensive Net, we propose In-extensive …

… and/or clouds, operating in different conditions. Hence we conclude that, supervised ML
techniques need significant rework to perform better in the context of cloud security. More …

… -class tunnel point cloud segmentation for practical applications, this research proposes
a deep learning method named semi-supervised learning-based point cloud network (SPCNet) …

… in the extreme can result in the cloud infrastructure being unable to allocate … a supervised
learning model that leverages primitive information (eg, running process, login history, network …

… In this research we present two supervised machine learning algorithms implementing
Logistic Regression and Linear Discriminant Analysis of Algorithms, respectively, to predict UAV …

… The network traffic analysis data provides useful information to the network administrator for
… With the convergence of networking technologies such as cloud computing, IoT data growth …

… to cloud … learning models to handle the dynamic nature of the cloud infrastructure. This
prediction is then used for resource provisioning. Diverse scheduling scenarios over the cloud are …