An Efficient system to stumble on and Mitigate DDoS attack in cloud Environment

2018 ◽  
Author(s):  
K Manju Mohan
Keyword(s):  
Cloud Environment ◽  
Efficient System ◽  
Ddos Attack

Survey on DDoS Attacks and Defense Mechanisms in Cloud and Fog Computing

2018 ◽  
Vol 10 (3) ◽  
pp. 61-83 ◽  
Author(s):  
Deepali Chaudhary ◽  
Kriti Bhushan ◽  
B.B. Gupta
Keyword(s):  
Cloud Computing ◽  
Defense Mechanisms ◽  
Low Cost ◽  
Fog Computing ◽  
Smart Devices ◽  
Cloud Environment ◽  
Security Issue ◽  
Process Data ◽  
Ddos Attack ◽  
Iot Devices

This article describes how cloud computing has emerged as a strong competitor against traditional IT platforms by offering low-cost and “pay-as-you-go” computing potential and on-demand provisioning of services. Governments, as well as organizations, have migrated their entire or most of the IT infrastructure to the cloud. With the emergence of IoT devices and big data, the amount of data forwarded to the cloud has increased to a huge extent. Therefore, the paradigm of cloud computing is no longer sufficient. Furthermore, with the growth of demand for IoT solutions in organizations, it has become essential to process data quickly, substantially and on-site. Hence, Fog computing is introduced to overcome these drawbacks of cloud computing by bringing intelligence to the edge of the network using smart devices. One major security issue related to the cloud is the DDoS attack. This article discusses in detail about the DDoS attack, cloud computing, fog computing, how DDoS affect cloud environment and how fog computing can be used in a cloud environment to solve a variety of problems.

DdoS Attack Detection on Cloud Environment in Wireless Sensor Network: A Review

2018 ◽  
Vol 8 (5) ◽  
pp. 33
Author(s):  
Amarjeet Kaur ◽  
Gagandeep Kaur ◽  
Gagandeep Kaur
Keyword(s):  
Research Work ◽  
Attack Detection ◽  
Wireless Sensor ◽  
Cloud Environment ◽  
Due Date ◽  
General Control ◽  
Ddos Attack ◽  
The Common ◽  
The Government ◽  
Ddos Attack Detection

In this sense, DoS, particularly DDoS, undermines the Internet, as well as debilitates the common security, because of its predominant utilization in digital wrongdoings. Accordingly to see well the attributes of DDoS issues and examine comparing protection instruments have noteworthy commitments for the scholarly world and industry, as well as for the government disability and crisis administration organizations, since they can utilize such learning to upgrade their capacities of hazard appraisals and help the partners to settle on suitable choices when confronting DDoS dangers. In the current research work the diverse sorts of issues, such viewpoint as far as distinguishing DoS assaults is to see the issue as that of a grouping issue on arrange state (and not on singular bundles or different units) by demonstrating ordinary and assault activity and characterizing the momentum condition of the system as great or terrible, in this way identifying assaults when they happen. Another is the Transmission disappointments or due date misses may bring about unsettling influences to the procedure, debasement of the general control execution. In future All these are settled with the assistance of a DDoS assault location and DSR Algorithm with Cryptography on Wireless Sensor organize and the WSN with BS, CH

A Review on DDOS Attack, TCP Flood Attack in Cloud Environment

2020 ◽  
Author(s):  
Ashish Mishra ◽  
Saurabh Sharma ◽  
Archana Pandey
Keyword(s):  
Cloud Environment ◽  
Ddos Attack

Survey on DDoS Attacks and Defense Mechanisms in Cloud and Fog Computing

2019 ◽  
pp. 1927-1951
Author(s):  
Deepali Chaudhary ◽  
Kriti Bhushan ◽  
B.B. Gupta
Keyword(s):  
Cloud Computing ◽  
Defense Mechanisms ◽  
Low Cost ◽  
Fog Computing ◽  
Smart Devices ◽  
Cloud Environment ◽  
Security Issue ◽  
Process Data ◽  
Ddos Attack ◽  
Iot Devices

This article describes how cloud computing has emerged as a strong competitor against traditional IT platforms by offering low-cost and “pay-as-you-go” computing potential and on-demand provisioning of services. Governments, as well as organizations, have migrated their entire or most of the IT infrastructure to the cloud. With the emergence of IoT devices and big data, the amount of data forwarded to the cloud has increased to a huge extent. Therefore, the paradigm of cloud computing is no longer sufficient. Furthermore, with the growth of demand for IoT solutions in organizations, it has become essential to process data quickly, substantially and on-site. Hence, Fog computing is introduced to overcome these drawbacks of cloud computing by bringing intelligence to the edge of the network using smart devices. One major security issue related to the cloud is the DDoS attack. This article discusses in detail about the DDoS attack, cloud computing, fog computing, how DDoS affect cloud environment and how fog computing can be used in a cloud environment to solve a variety of problems.

scholarly journals Flow Correlation Degree Optimization Driven Random Forest for Detecting DDoS Attacks in Cloud Computing

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Jieren Cheng ◽  
Mengyang Li ◽  
Xiangyan Tang ◽  
Victor S. Sheng ◽  
Yifu Liu ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Cloud Computing ◽  
Random Forest ◽  
Decision Tree ◽  
Attack Detection ◽  
Detection Methods ◽  
Cloud Environment ◽  
Ddos Attack ◽  
Correlation Degree ◽  
Ddos Attack Detection

Distributed denial-of-service (DDoS) has caused major damage to cloud computing, and the false- and missing-alarm rates of existing DDoS attack-detection methods are relatively high in cloud environment. In this paper, we propose a DDoS attack-detection method with enhanced random forest (RF) optimized by genetic algorithm based on flow correlation degree (FCD) feature. We define the FCD feature according to the asymmetric and semidirectivity interaction characteristics and use the two-tuples FCD feature consisting of packet-statistical degree (PSD) and semidirectivity interaction abnormality (SDIA) to describe the features of attack flow and normal flow. Then we use a genetic algorithm based on the FCD feature sequences to optimize two key parameters of the decision tree in the RF: the maximum number of decision trees and the maximum depth of every single decision tree. We apply the trained RF model with optimized parameters to generate the classifier to be used for DDoS attack-detection. The experiment shows that the proposed method can effectively detect DDoS attacks in cloud environment with a higher accuracy rate and lower false- and missing-alarm rates compared to existing DDoS attack-detection methods.

Sign in / Sign up

Export Citation Format

Share Document