scholarly journals Application Layer Distributed Denial of Service Attacks Defense Techniques : A review

2018 ◽  
Vol 7 (4) ◽  
pp. 113 ◽  
Author(s):  
Subhi R. M. Zeebaree ◽  
Karzan H. Sharif ◽  
Roshna M. Mohammed Amin
Keyword(s):  
Denial Of Service ◽  
The Internet ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Application Layer ◽  
Detection Techniques ◽  
Clear View ◽  
Methods And Techniques ◽  
Experimental Approaches ◽  
Detection Mechanisms

Currently distributed denial of service (DDoS) is the most sever attack that effect on the internet convenience. The main goal of these attacks is to prevent normal users from accessing the internet services such as web servers. However the more challenge and difficult types to detect is application layer DDoS attacks because of using legitimate client to create connection with victims. In this paper we give a review on application layer DDoS attacks defense or detection mechanisms. Furthermore, we summarize several experimental approaches on detection techniques of application layer DDoS attacks. The main goal of this paper is to get a clear view and detailed summary of the recent algorithms, methods and techniques presented to tackle these serious types of attacks.

HULK and DDoS Attacks in Web Applications with Detection Mechanism

2018 ◽  
Vol 6 (6) ◽  
pp. 192
Author(s):  
Amit Sharma
Keyword(s):  
Web Applications ◽  
Denial Of Service ◽  
Single Server ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Application Layer ◽  
Detection Mechanism ◽  
Plan Execution ◽  
Social Affair ◽  
Server Application

Distributed Denial of Service attacks are significant dangers these days over web applications and web administrations. These assaults pushing ahead towards application layer to procure furthermore, squander most extreme CPU cycles. By asking for assets from web benefits in gigantic sum utilizing quick fire of solicitations, assailant robotized programs use all the capacity of handling of single server application or circulated environment application. The periods of the plan execution is client conduct checking and identification. In to beginning with stage by social affair the data of client conduct and computing individual user’s trust score will happen and Entropy of a similar client will be ascertained. HTTP Unbearable Load King (HULK) attacks are also evaluated. In light of first stage, in recognition stage, variety in entropy will be watched and malevolent clients will be recognized. Rate limiter is additionally acquainted with stop or downsize serving the noxious clients. This paper introduces the FAÇADE layer for discovery also, hindering the unapproved client from assaulting the framework.

Booters: can anything justify distributed denial-of-service (DDoS) attacks for hire?

2017 ◽  
Vol 15 (01) ◽  
pp. 90-104 ◽  
Author(s):  
David Douglas ◽  
José Jair Santanna ◽  
Ricardo de Oliveira Schmidt ◽  
Lisandro Zambenedetti Granville ◽  
Aiko Pras
Keyword(s):  
Heavy Traffic ◽  
Denial Of Service ◽  
Civil Disobedience ◽  
Third Party ◽  
The Internet ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Law Enforcement Agencies ◽  
Content Type ◽  
Testing Tools

Purpose This paper aims to examine whether there are morally defensible reasons for using or operating websites (called ‘booters’) that offer distributed denial-of-service (DDoS) attacks on a specified target to users for a price. Booters have been linked to some of the most powerful DDoS attacks in recent years. Design/methodology/approach The authors identify the various parties associated with booter websites and the means through which booters operate. Then, the authors present and evaluate the two arguments that they claim may be used to justify operating and using booters: that they are a useful tool for testing the ability of networks and servers to handle heavy traffic, and that they may be used to perform DDoS attacks as a form of civil disobedience on the internet. Findings The authors argue that the characteristics of existing booters disqualify them from being morally justified as network stress testing tools or as a means of performing civil disobedience. The use of botnets that include systems without the permission of their owners undermines the legitimacy of both justifications. While a booter that does not use any third-party systems without permission might in principle be justified under certain conditions, the authors argue that it is unlikely that any existing booters meet these requirements. Practical/implications Law enforcement agencies may use the arguments presented here to justify shutting down the operation of booters, and so reduce the number of DDoS attacks on the internet. Originality/value The value of this work is in critically examining the potential justifications for using and operating booter websites and in further exploring the ethical aspects of using DDoS attacks as a form of civil disobedience.

scholarly journals DDoS-Capable IoT Malwares: Comparative Analysis and Mirai Investigation

2018 ◽  
Vol 2018 ◽  
pp. 1-30 ◽  
Author(s):  
Michele De Donno ◽  
Nicola Dragoni ◽  
Alberto Giaretta ◽  
Angelo Spognardi
Keyword(s):  
Comparative Analysis ◽  
Internet Of Things ◽  
Detailed Analysis ◽  
Real World ◽  
General Framework ◽  
Denial Of Service ◽  
The Internet ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
The Internet Of Things

The Internet of Things (IoT) revolution has not only carried the astonishing promise to interconnect a whole generation of traditionally “dumb” devices, but also brought to the Internet the menace of billions of badly protected and easily hackable objects. Not surprisingly, this sudden flooding of fresh and insecure devices fueled older threats, such as Distributed Denial of Service (DDoS) attacks. In this paper, we first propose an updated and comprehensive taxonomy of DDoS attacks, together with a number of examples on how this classification maps to real-world attacks. Then, we outline the current situation of DDoS-enabled malwares in IoT networks, highlighting how recent data support our concerns about the growing in popularity of these malwares. Finally, we give a detailed analysis of the general framework and the operating principles of Mirai, the most disruptive DDoS-capable IoT malware seen so far.

scholarly journals Preventing & Isolating Distributed Denial of Service (DDOS) attack in Wireless Mesh Networks (WMN's)

2019 ◽  
Vol 8 (9S) ◽  
pp. 447-454
Keyword(s):  
Wireless Mesh Networks ◽  
Shortest Path ◽  
Mesh Networks ◽  
Denial Of Service ◽  
The Internet ◽  
Covert Channel ◽  
Distributed Denial Of Service ◽  
Application Layer ◽  
Ddos Attack ◽  
Wireless Mesh

Wireless Mesh networks (WMN’s) are prone to a number of attacks & these attacks compromise the security of these networks. Attaining security in these networks is a challenging task. It is logical to consider that there are many types of scripts in the internet. The virus can either be a key logger or somebody else's mischief. With this script we can steal any information. Since the existence of virus cannot be ignored, therefore the authors have tried to present their work on first detecting it and later on fixing it. With the help of different protocols present in the Application Layer, a hacker takes information out of the script. The authors have used Covert Channel, which has been mentioned in many essays. Now with the help of this channel, the information will go to all and it will not go to any of the informatics. This research proposal envisions a methodology to first detect the selfish node in the network & later on provides a technique for mitigation of the same.NS2 simulator has been used to simulate & analyze the performance of our proposed methodology for Open Shortest Path First (OSPF) protocol in WMN’s.

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.

Data Mining Techniques for Distributed Denial of Service Attacks Detection in the Internet of Things

2016 ◽  
pp. 275-334 ◽  
Author(s):  
Pheeha Machaka ◽  
Fulufhelo Nelwamondo
Keyword(s):  
Data Mining ◽  
Internet Of Things ◽  
Denial Of Service ◽  
Current Data ◽  
The Internet ◽  
Denial Of Service Attacks ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Data Mining Techniques ◽  
The Internet Of Things

This chapter reviews the evolution of the traditional internet into the Internet of Things (IoT). The characteristics and application of the IoT are also reviewed, together with its security concerns in terms of distributed denial of service attacks. The chapter further investigates the state-of-the-art in data mining techniques for Distributed Denial of Service (DDoS) attacks targeting the various infrastructures. The chapter explores the characteristics and pervasiveness of DDoS attacks. It also explores the motives, mechanisms and techniques used to execute a DDoS attack. The chapter further investigates the current data mining techniques that are used to combat and detect these attacks, their advantages and disadvantages are explored. Future direction of the research is also provided.

Cyber-Physical System and Internet of Things Security

2021 ◽  
pp. 328-357
Author(s):  
Thomas Ulz ◽  
Sarah Haas ◽  
Christian Steger
Keyword(s):  
Internet Of Things ◽  
Public Awareness ◽  
Denial Of Service ◽  
The Internet ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Industrial Iot ◽  
Confidential Data ◽  
Iot Devices ◽  
The Internet Of Things

An increase of distributed denial-of-service (DDoS) attacks launched by botnets such as Mirai has raised public awareness regarding potential security weaknesses in the Internet of Things (IoT). Devices are an attractive target for attackers because of their large number and due to most devices being online 24/7. In addition, many traditional security mechanisms are not applicable for resource constraint IoT devices. The importance of security for cyber-physical systems (CPS) is even higher, as most systems process confidential data or control a physical process that could be harmed by attackers. While industrial IoT is a hot topic in research, not much focus is put on ensuring information security. Therefore, this paper intends to give an overview of current research regarding the security of data in industrial CPS. In contrast to other surveys, this work will provide an overview of the big CPS security picture and not focus on special aspects.

scholarly journals USING GRAPHIC NETWORK SIMULATOR 3 FOR DDOS ATTACKS SIMULATION

2017 ◽  
pp. 219-225
Author(s):  
Anatoliy Balyk ◽  
Mikolaj Karpinski ◽  
Artur Naglik ◽  
Gulmira Shangytbayeva ◽  
Ihor Romanets
Keyword(s):  
Denial Of Service ◽  
Discrete Event ◽  
Network Simulator ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Easy Task ◽  
Detection Techniques ◽  
Ddos Attack ◽  
Network Simulators ◽  
Attack Mitigation

Distributed Denial of Service (DDoS) attacks are still one of the major cybersecurity threats and the focus of much research on developing DDoS attack mitigation and detection techniques. Being able to model DDoS attacks can help researchers develop effective countermeasures. Modeling DDoS attacks, however, is not an easy task because modern DDoS attacks are huge and simulating them would be impossible in most cases. That’s why researchers use tools like network simulators for modeling DDoS attacks. Simulation is a widely used technique in networking research, but it has suffered a loss of credibility in recent years because of doubts about its reliability. In our previous works we used discrete event simulators to simulate DDoS attacks, but our results were often different from real results. In this paper, we apply our approach and use Graphical Network Simulator-3(GNS3) to simulate an HTTP server’s performance in a typical enterprise network under DDoS attack. Also, we provide references to related work.

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 An New Efficient Cluster Based Detection Mechanisms for Distributed Denial of Services (DDoS) Attacks

2021 ◽  
Vol 15 ◽  
pp. 147-152
Author(s):  
K. Saravanan ◽  
R. Asokan
Keyword(s):  
Denial Of Service ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Host System ◽  
Denial Of Service Attack ◽  
Cluster Aggregation ◽  
The Core ◽  
Service Attack ◽  
Detection Mechanisms ◽  
Statistical Anomaly Detection

Cluster aggregation of statistical anomaly detection is a mechanism for defending against denial of service attack (dos) and distributed denial-of-service (DDoS) attacks. DDoS attacks are treated as a congestioncontrol problem; because most of the congestion is occurred in the malicious hosts not follow the normal endto- end congestion control. Upstream routers are also notified to drop such packets in order that the router’s resources are used to route legitimate traffic hence term cluster aggregation. If the victim suspects that the cluster aggregations are solved by most of the clients, it increases the complexity of the cluster aggregation. This aggregation solving technique allows the traversal of the attack traffic throughout the intermediate routers before reaching the destination. In this proposal, the aggregation solving mechanism is cluster aggregation to the core routers rather than having at the victim. The router based cluster aggregation mechanism checks the host system whether it is legitimate or not by providing a aggregation to be solved by the suspected host.

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