An efficient IDS in cloud environment using feature selection based on DM algorithm

2022 ◽  
Author(s):  
Partha Ghosh ◽  
Shashwat Sinha ◽  
Ritu Raj Sharma ◽  
Santanu Phadikar
Keyword(s):  
Feature Selection ◽  
Cloud Environment

scholarly journals DLMNN: A Deep Learning Modified Neural Network for Balancing the Load of Cloudlets on Cloud

2019 ◽  
Vol 9 (1) ◽  
pp. 6524-6532
Keyword(s):  
Neural Network ◽  
Cloud Computing ◽  
Feature Selection ◽  
Cloud Services ◽  
Second Step ◽  
Cloud Environment ◽  
Cloud Platform ◽  
Cloud Architecture ◽  
Load Balancing Algorithm ◽  
Cloud Servers

Cloud Computing a revolution in the computing world, has enabled the users to utilize the services on the Cloud platform from anywhere at any time. As there is an increase in the demand for the utilization of a cloud environment, there are several challenges to be addressed by the companies or organizations to provide uninterrupted cloud services. To make the cloud services available without interruption, the challenge of balancing the load on cloud servers is a must. Proper allocation of load on the servers optimize the performance of the cloud and improves the efficiency to offer uninterrupted services. Recent studies have shown, cloud always needs to have a capable algorithm to distribute the load on servers of cloud architecture to be available to process cloudlets submitted by the customers. Our paper looks for a new load balancing algorithm that uses the concepts of neural network and is used to allocate the tasks in the cloud. The proposed algorithm consists of two steps. First, Features of tasks and cloud servers are extracted, and the necessary features are selected. The feature selection can be done by using MPCA. In the second step, the selected features are sent as input to the DLMNN algorithm to schedule the task in the cloud. Finally, the experimental results of the proposed DLMNN are compared with some existing algorithms.

scholarly journals A Many Objective-Based Feature Selection Model for Anomaly Detection in Cloud Environment

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 60218-60231 ◽  
Author(s):  
Zhixia Zhang ◽  
Jie Wen ◽  
Jiangjiang Zhang ◽  
Xingjuan Cai ◽  
Liping Xie
Keyword(s):  
Feature Selection ◽  
Anomaly Detection ◽  
Selection Model ◽  
Cloud Environment

Feature Selection Strategies and Perceptual Expertise in Configuration Search Tasks

2011 ◽  
Author(s):  
Lindsey M. Kitchell ◽  
Francisco J. Parada ◽  
Brandi L. Emerick ◽  
Tom A. Busey
Keyword(s):  
Feature Selection ◽  
Perceptual Expertise ◽  
Search Tasks ◽  
Selection Strategies

Task Scheduling Algorithm based on Resources Segregation in Cloud Environment

2018 ◽  
pp. 96-101
Author(s):  
Shailendra Raghuvanshi ◽  
Priyanka Dubey
Keyword(s):  
Load Balancing ◽  
Task Scheduling ◽  
Waiting Time ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Cloud Environment ◽  
Task Scheduling Algorithm ◽  
Machine Utilization ◽  
Independent Tasks ◽  
Optimal Machine

Load balancing of non-preemptive independent tasks on virtual machines (VMs) is an important aspect of task scheduling in clouds. Whenever certain VMs are overloaded and remaining VMs are under loaded with tasks for processing, the load has to be balanced to achieve optimal machine utilization. In this paper, we propose an algorithm named honey bee behavior inspired load balancing, which aims to achieve well balanced load across virtual machines for maximizing the throughput. The proposed algorithm also balances the priorities of tasks on the machines in such a way that the amount of waiting time of the tasks in the queue is minimal. We have compared the proposed algorithm with existing load balancing and scheduling algorithms. The experimental results show that the algorithm is effective when compared with existing algorithms. Our approach illustrates that there is a significant improvement in average execution time and reduction in waiting time of tasks on queue using workflowsim simulator in JAVA.

BLIND FEATURE SELECTION AND EXTRACTION IN A 3D IMAGE CUBE

2012 ◽  
Vol 19 (2) ◽  
pp. 97-111 ◽  
Author(s):  
Muhammad Ahmad ◽  
Syungyoung Lee ◽  
Ihsan Ul Haq ◽  
Qaisar Mushtaq
Keyword(s):  
Feature Selection ◽  
3D Image ◽  
Image Cube
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