scholarly journals A Review on Distributed Denial of Service (DDoS) Mitigation Techniques in Cloud Computing Environment

2016 ◽  
Vol 10 (8) ◽  
pp. 277-294
Author(s):  
Junath Naseer Ahamed ◽  
N. Ch. S. N. Iyengar
Keyword(s):  
Cloud Computing ◽  
Denial Of Service ◽  
Distributed Denial Of Service ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Mitigation Techniques

scholarly journals Adaptive Learning and Automatic Filtering of Distributed Denial of Service (DDoS) Attacks in Cloud Computing Environment

2019 ◽  
Vol 9 (1S3) ◽  
pp. 200-205
Keyword(s):  
Cloud Computing ◽  
Adaptive Learning ◽  
Denial Of Service ◽  
Cloud Services ◽  
Detection Accuracy ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Automatic Filtering

Distributed Denial of Service (DDoS) attacks has become the most powerful cyber weapon to target the businesses that operate on the cloud computing environment. The sophisticated DDoS attack affects the functionalities of the cloud services and affects its core capabilities of cloud such as availability and reliability. The current intrusion detection system (IDS) must cope with the dynamicity and intensity of immense traffic at the cloud hosted applications and the security attack must be inspected based on the attack flow characteristics. Hence, the proposed Adaptive Learning and Automatic Filtering of Distributed Denial of Service (DDoS) Attacks in Cloud Computing Environment is designed to adapt with varying kind of protocol attacks using misuse detection. The system is equipped with custom and threshold techniques that satisfies security requirements and can identify the different DDoS security attacks. The proposed system provides promising results in detecting the DDoS attacks in cloud environment with high detection accuracy and good alert reduction. Threshold method provides 98% detection accuracy with 99.91%, 99.92% and 99.94% alert reduction for ICMP, UDP and TCP SYN flood attack. The defense system filters the attack sources at the target virtual instance and protects the cloud applications from DDoS attacks.

scholarly journals A Reliable Friedman Hypothesis-Based Detection and Adaptive Load Balancing Scheme for Mitigating Reduction of Quality DDoS Attacks in Cloud Computing

2019 ◽  
Vol 9 (1) ◽  
pp. 360-366
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Denial Of Service ◽  
Distributed Denial Of Service ◽  
Cloud Environment ◽  
Cloud Infrastructure ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
On Demand ◽  
Demand Service

The computing resource availability in a cloud computing environment is considered as the vital attribute among the security essentialities due to the consequence of on its on demand service. The class of adversaries related to the Distributed Denial of Service (DDoS) attack is prevalent in the cloud infrastructure for exploiting the vulnerabilities during the implementation of their attack that still make the process of providing security and availability at the same time as a challenging objective. In specific, The in cloud computing is the major threat during the process of balancing security and availability at the same time. In this paper, A Reliable Friedman Hypothesis-based Detection and Adaptive Load Balancing Scheme (RFALBS-RoQ-DDOS) is contributed for effective detection of RoQDDoS attacks through Friedman hypothesis testing. It also inherited an adaptive load balancing approach that prevents the degree of imbalance in the cloud environment. The simulation results of the proposed RFALBS-RoQ-DDoS technique confirmed a superior detection rate and a adaptive load balancing rate of nearly 23% and 28% predominant to the baseline DDoS mitigation schemes considered for investigation.

scholarly journals A Novel Model for Securing Mobile-based Systems against DDoS Attacks in Cloud Computing Environment

2019 ◽  
Vol 13 (01) ◽  
pp. 85 ◽  
Author(s):  
Hosam El-Sofany ◽  
Samir Abou El-Seoud
Keyword(s):  
Cloud Computing ◽  
Mobile Computing ◽  
Mobile Cloud Computing ◽  
Denial Of Service ◽  
Mobile Cloud ◽  
Ddos Attacks ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Authorized User ◽  
Novel Model

the increasing growth of mobile devices technology and Mobile-based systems with the emerging of cloud computing technology, created a Mobile Cloud Computing field to be the recent future technology for different wireless services. The development of Mobile-based system under cloud computing environment solve some performance and environment related issues include: bandwidth, storage capacity, availability, scalability and heterogeneity. The Mobile-based cloud computing apps are different comparing to mobile computing apps, since in the first model the devices run cloud based web applications not as mobile computing native apps. Services of Mobile-based systems via cloud are accessing and sharing through internet connection thus they are open for attacker to attack on its security. Distributed Denial of Service (DDoS) attacks can cause a big problem in mobile cloud computing security. The main objective of DDoS attacks is to infect wireless devises resources (e.g., software applications, wireless network, etc.) and make them unavailable to the authorized user. In DDoS, the attacker tries to overload the Mobile-based service with traffic. The main objective of this research paper is to introduce novel model for securing Mobile-based systems against DDoS attacks. Efficiency and performance analysis evaluations of the proposed model are presented.  The feedbacks of the experimental results were highly promising, for protecting mobile-based cloud computing systems against DDoS attacks.

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