scholarly journals DETECTION AND MITIGATION OF DISTRIBUTED DENIAL OF SERVICE ATTACKS ON NETWORK ARCHITECTURE SOFTWARE DEFINED NETWORKING USING THE NAIVE BAYES ALGORITHM

2022 ◽  
Vol 3 (2) ◽  
pp. 51-55
Author(s):  
Misbachul Munir ◽  
Ipung Ardiansyah ◽  
Joko Dwi Santoso ◽  
Ali Mustopa ◽  
Sri Mulyatun
Keyword(s):  
Network Architecture ◽  
Naive Bayes ◽  
Denial Of Service ◽  
Naïve Bayes ◽  
Software Defined Network ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Dos Attacks ◽  
Network Resources ◽  
Bayes Algorithm

DDoS attacks are a form of attack carried out by sending packets continuously to machines and even computer networks. This attack will result in a machine or network resources that cannot be accessed or used by users. DDoS attacks usually originate from several machines operated by users or by bots, whereas Dos attacks are carried out by one person or one system. In this study, the term to be used is the term DDoS to represent a DoS or DDoS attack. In the network world, Software Defined Network (SDN) is a promising paradigm. SDN separates the control plane from forwarding plane to improve network programmability and network management. As part of the network, SDN is not spared from DDoS attacks. In this study, we use the naïve Bayes algorithm as a method to detect DDoS attacks on the Software Defined Network network architecture

Taxonomy of Distributed Denial of Service (DDoS) Attacks and Defense Mechanisms in Present Era of Smartphone Devices

2018 ◽  
Vol 10 (2) ◽  
pp. 58-74 ◽  
Author(s):  
Kavita Sharma ◽  
B. B. Gupta
Keyword(s):  
Defense Mechanisms ◽  
Computer Network ◽  
Denial Of Service ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Dos Attacks ◽  
Network Resources ◽  
Common People ◽  
Ddos Attack ◽  
Legitimate User

This article describes how in the summer of 1999, the Computer Incident Advisory Capability first reported about Distributed Denial of Service (DDoS) attack incidents and the nature of Denial of Service (DoS) attacks in a distributed environment that eliminates the availability of resources or data on a computer network. DDoS attack exhausts the network resources and disturbs the legitimate user. This article provides an explanation on DDoS attacks and nature of these attacks against Smartphones and Wi-Fi Technology and presents a taxonomy of various defense mechanisms. The smartphone is chosen for this study, as they have now become a necessity rather than a luxury item for the common people.

scholarly journals SVM Implementation for Ddos Attacks in Software Defined Networks

2020 ◽  
Vol 10 (1) ◽  
pp. 205-212
Keyword(s):  
Detection Rate ◽  
Denial Of Service ◽  
Support Vector ◽  
Software Defined Network ◽  
Software Defined Networks ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Network Resources ◽  
Elapsed Time ◽  
Classification Technique

Software Defined Network (SDN) is making software interaction with the network. SDN has made the network flexible and dynamic and also enabled the abstraction feature of applications and services. As the network is independent of any of the devices like in traditional networks there exist routers, hubs, and switches that is why it is preferable these days. Being more preferably used it has become more vulnerable in terms of security. The more common attacks that corrupt the network and hinders the efficiency are distributed denial-of-service (DDOS) attacks. DDOS is an attack that in general leads to exhaust of the network resources in turn stopping the controller. Detection of DDOS attacks requires a classification technique that provides accurate and efficient decision making. As per the analysis Support Vector Machine (SVM), the classifier technique detects more accurately and precisely the attacks. This paper produces a better approach to detecting attacks using SVM classifiers in terms of detection rate and elapsed time of the attack and it also predicts the various types of distributed denial of service attacks that have corrupted the network.

scholarly journals A Review of Anomaly Detection Techniques and Distributed Denial of Service (DDoS) on Software Defined Network (SDN)

2018 ◽  
Vol 8 (2) ◽  
pp. 2724-2730 ◽  
Author(s):  
M. H. H. Khairi ◽  
S. H. S. Ariffin ◽  
N. M. Abdul Latiff ◽  
A. S. Abdullah ◽  
M. K. Hassan
Keyword(s):  
Anomaly Detection ◽  
Network Architecture ◽  
Denial Of Service ◽  
Software Defined Network ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Detection Techniques ◽  
And Control ◽  
Entire Network

Software defined network (SDN) is a network architecture in which the network traffic may be operated and managed dynamically according to user requirements and demands. Issue of security is one of the big challenges of SDN because different attacks may affect performance and these attacks can be classified into different types. One of the famous attacks is distributed denial of service (DDoS). SDN is a new networking approach that is introduced with the goal to simplify the network management by separating the data and control planes. However, the separation leads to the emergence of new types of distributed denial-of-service (DDOS) attacks on SDN networks. The centralized role of the controller in SDN makes it a perfect target for the attackers. Such attacks can easily bring down the entire network by bringing down the controller. This research explains DDoS attacks and the anomaly detection as one of the famous detection techniques for intelligent networks.

scholarly journals Distributed Denial of Service (DDoS) Attacks and Defence Mechanism

2021 ◽  
Vol 10 (3) ◽  
pp. 83-88
Author(s):  
Akhil K.M ◽  
Rahul C.T ◽  
Athira V.B
Keyword(s):  
Defense Mechanisms ◽  
Denial Of Service ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Dos Attacks ◽  
Network Resources ◽  
Advantages And Disadvantages ◽  
Self Defense ◽  
Short Period ◽  
Attack And Defense

Denial of Service (DoS) attacks is one of the major threats to Internet sites and one of the major security problems Internet faces today. The nature of threats caused by Distributed Denial of Service (DDoS) attacks on networks. With little or no warning, a DDoS attack could easily destroy its victim's communication and network resources in a short period of time. This paper outlines the problem of DDoS attacks and developing a classification of DDoS attacks and DDoS defense mechanisms. Important features of each attack and defense system category are described and advantages and disadvantages of each proposed scheme are outlined. The goal of the paper is to set a certain order of existence methods of attack and defense mechanisms, for the better understanding DDoS attacks can be achieved with more effective methods and means of self-defense can be developed.

Taxonomy of Distributed Denial of Service (DDoS) Attacks and Defense Mechanisms in Present Era of Smartphone Devices

2021 ◽  
pp. 415-434
Author(s):  
Kavita Sharma ◽  
B. B. Gupta
Keyword(s):  
Defense Mechanisms ◽  
Computer Network ◽  
Denial Of Service ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Dos Attacks ◽  
Network Resources ◽  
Common People ◽  
Ddos Attack ◽  
Legitimate User

This article describes how in the summer of 1999, the Computer Incident Advisory Capability first reported about Distributed Denial of Service (DDoS) attack incidents and the nature of Denial of Service (DoS) attacks in a distributed environment that eliminates the availability of resources or data on a computer network. DDoS attack exhausts the network resources and disturbs the legitimate user. This article provides an explanation on DDoS attacks and nature of these attacks against Smartphones and Wi-Fi Technology and presents a taxonomy of various defense mechanisms. The smartphone is chosen for this study, as they have now become a necessity rather than a luxury item for the common people.

scholarly journals AntibIoTic: Protecting IoT Devices Against DDoS Attacks

2017 ◽  
Author(s):  
Michele De Donno ◽  
Nicola Dragoni ◽  
Alberto Giaretta ◽  
Manuel Mazzara
Keyword(s):  
Denial Of Service ◽  
Main Idea ◽  
Denial Of Service Attacks ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Dos Attacks ◽  
The World ◽  
Iot Devices

The 2016 is remembered as the year that showed to the world how dangerous distributed Denial of Service attacks can be. Gauge of the disruptiveness of DDoS attacks is the number of bots involved: the bigger the botnet, the more powerful the attack. This character, along with the increasing availability of connected and insecure IoT devices, makes DDoS and IoT the perfect pair for the malware industry. In this paper we present the main idea behind AntibIoTic, a palliative solution to prevent DoS attacks perpetrated through IoT devices.

DeepDetect: Detection of Distributed Denial of Service Attacks Using Deep Learning

2019 ◽  
Vol 63 (7) ◽  
pp. 983-994 ◽  
Author(s):  
Muhammad Asad ◽  
Muhammad Asim ◽  
Talha Javed ◽  
Mirza O Beg ◽  
Hasan Mujtaba ◽  
...  
Keyword(s):  
Neural Network ◽  
Network Architecture ◽  
Denial Of Service ◽  
Smart Devices ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Application Layer ◽  
Tangible Computing ◽  
Network Bandwidth ◽  
Feed Forward Back Propagation

Abstract At the advent of advanced wireless technology and contemporary computing paradigms, Distributed Denial of Service (DDoS) attacks on Web-based services have not only increased exponentially in number, but also in the degree of sophistication; hence the need for detecting these attacks within the ocean of communication packets is extremely important. DDoS attacks were initially projected toward the network and transport layers. Over the years, attackers have shifted their offensive strategies toward the application layer. The application layer attacks are potentially more detrimental and stealthier because of the attack traffic and the benign traffic flows being indistinguishable. The distributed nature of these attacks is difficult to combat as they may affect tangible computing resources apart from network bandwidth consumption. In addition, smart devices connected to the Internet can be infected and used as botnets to launch DDoS attacks. In this paper, we propose a novel deep neural network-based detection mechanism that uses feed-forward back-propagation for accurately discovering multiple application layer DDoS attacks. The proposed neural network architecture can identify and use the most relevant high level features of packet flows with an accuracy of 98% on the state-of-the-art dataset containing various forms of DDoS attacks.

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