Survey on DDoS Attack Techniques and Solutions in Software-Defined Network

Ubale, Tushar; Jain, Ankit Kumar

doi:10.1007/978-3-030-22277-2_15

Cited by 23 publications

(11 citation statements)

References 29 publications

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“…Subsequently, it performs suitable countermeasures. Simulation outcomes represent that the introduced defending method might effectively deal with DDoS attacks in downstream servers and SDN [7]. The DDoS attack detection in SDN is shown in Fig.…”

Section: Introductionmentioning

confidence: 90%

An SDN-based Decision Tree Detection (DTD) Model for Detecting DDoS Attacks in Cloud Environment

J¹,

Sridaran²

2022

IJACSA

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Detecting Distributed Denial of Service (DDoS) attacks has become a significant security issue for various network technologies. This attack has to be detected to increase the system's reliability. Though various traditional studies are present, they suffer from data shift issues and accuracy. Hence, this study intends to detect DDoS attacks by classifying the normal and malicious traffic. The study aims to solve the data shift issues by using the introduced Decision Tree Detection (DTD) model encompassing of Greedy Feature Selection (GFS) algorithm and Decision Tree Algorithm (DTA). It also attempts to enhance the proposed model's detection rate (accuracy) above 90%. Various processes are involved in DDoS attack detection. Initially, the gureKddcup dataset is loaded to perform preprocessing. This process is essential for removing noisy data. After this, feature selection is performed to select only the relevant features, removing the irrelevant data. This is then fed into the train and test split. Following this, Software Defined Networking (SDN) based DTA is used to classify the normal and malicious traffic, then given to the trained model for predicting this attack. Performance analysis is undertaken by comparing the proposed model with existing systems in terms of accuracy, MCC (Matthew's Correlation Coefficient), sensitivity, specificity, error rate, FAR (False Alarm Rate), and AUC (Area under Curve). This analysis is carried out to evaluate the efficacy of the proposed model, which is verified through the results.

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Section: Introductionmentioning

confidence: 90%

An SDN-based Decision Tree Detection (DTD) Model for Detecting DDoS Attacks in Cloud Environment

J¹,

Sridaran²

2022

IJACSA

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“…Since then, botnets have become one of the most significant threats to the internet especially in web-based business transactions. DDoS attacks aim to interrupt the supply of services by crippling network and storage capacity of the authorized users [13]- [15]. The main challenge in network security is how to ensure safety from the attacks; moreover, several types of attacks prevent legitimate users from using the services provided to them, and these types of attacks are called DDoS.…”

Section: A Brief History Of Ddos Attacksmentioning

confidence: 99%

Distributed reflection denial of service attack: A critical review

Nuiaa

Manickam

Alsaeedi

2021

IJECE

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As the world becomes increasingly connected and the number of users grows exponentially and “things” go online, the prospect of cyberspace becoming a significant target for cybercriminals is a reality. Any host or device that is exposed on the internet is a prime target for cyberattacks. A denial-of-service (DoS) attack is accountable for the majority of these cyberattacks. Although various solutions have been proposed by researchers to mitigate this issue, cybercriminals always adapt their attack approach to circumvent countermeasures. One of the modified DoS attacks is known as distributed reflection denial-of-service attack (DRDoS). This type of attack is considered to be a more severe variant of the DoS attack and can be conducted in transmission control protocol (TCP) and user datagram protocol (UDP). However, this attack is not effective in the TCP protocol due to the three-way handshake approach that prevents this type of attack from passing through the network layer to the upper layers in the network stack. On the other hand, UDP is a connectionless protocol, so most of these DRDoS attacks pass through UDP. This study aims to examine and identify the differences between TCP-based and UDP-based DRDoS attacks.

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“…In addition, even without detecting DoS attack the prevention scenario can also stop the user from accessing the cloud resources. The prevention techniques may install different protection components on all the cloud sites such as the user system, the network controllers, the internet routers, and track the attacker site [14].…”

Section: Defense Against Ddos Attacksmentioning

confidence: 99%

“…There are also other classifications of the DDoS attacks on the cloud and the detection or prevention techniques used for these types of attacks as summarized below [14].…”

Section: After the Ddos Attackmentioning

confidence: 99%

Distributed Denial of Service Attacks in Cloud Computing

Abusaimeh¹

2020

IJACSA

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The Cloud Computing attacks have been increased since the expanded use of the cloud computing. One of the famous attacks that targets the cloud computing is the distributed denial of service (DDoS) attack. The common features and component of the cloud structure make it more reachable from this kind of attack. The DDOS is targeting the large number of devices connected in any cloud service provider based on its scalability and reliability features that make the cloud available from anywhere and anytime. This attack mainly generate a large number of malicious packets to make the targeted server busy dealing with these huge number of packets. There many techniques to defend the DDOS attack in the regular networks, while in the cloud computing this task is more complicated regarding the various characteristics of the cloud that make the defending process not an easy task. This paper will investigate most of the method used in detecting and preventing and then recover from the DDoS in the cloud computing environment.

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Survey on DDoS Attack Techniques and Solutions in Software-Defined Network

Cited by 23 publications

References 29 publications

An SDN-based Decision Tree Detection (DTD) Model for Detecting DDoS Attacks in Cloud Environment

An SDN-based Decision Tree Detection (DTD) Model for Detecting DDoS Attacks in Cloud Environment

Distributed reflection denial of service attack: A critical review

Distributed Denial of Service Attacks in Cloud Computing

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