scholarly journals Recent Analysis of Forged Request Headers Constituted by HTTP DDoS

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3820
Author(s):  
Abdul Ghafar Jaafar ◽  
Saiful Adli Ismail ◽  
Mohd Shahidan Abdullah ◽  
Nazri Kama ◽  
Azri Azmi ◽  
...  
Keyword(s):  
Critical Analysis ◽  
Denial Of Service ◽  
Web Server ◽  
Recent Analysis ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Application Layer ◽  
Ddos Attack ◽  
Client Request ◽  
Attack Patterns

Application Layer Distributed Denial of Service (DDoS) attacks are very challenging to detect. The shortfall at the application layer allows formation of HTTP DDoS as the request headers are not compulsory to be attached in an HTTP request. Furthermore, the header is editable, thus providing an attacker with the advantage to execute HTTP DDoS as it contains almost similar request header that can emulate a genuine client request. To the best of the authors’ knowledge, there are no recent studies that provide forged request headers pattern with the execution of the current HTTP DDoS attack scripts. Besides that, the current dataset for HTTP DDoS is not publicly available which leads to complexity for researchers to disclose false headers, causing them to rely on old dataset rather than more current attack patterns. Hence, this study conducted an analysis to disclose forged request headers patterns created by HTTP DDoS. The results of this study successfully disclose eight forged request headers patterns constituted by HTTP DDoS. The analysis was executed by using actual machines and eight real attack scripts which are capable of overwhelming a web server in a minimal duration. The request headers patterns were explained supported by a critical analysis to provide the outcome of this paper.

scholarly journals Application Layer DDoS Attack Defense Methods and A new Defense Mechanism against Flooding

2020 ◽  
Vol 8 (6) ◽  
pp. 208-212
Keyword(s):  
Machine Learning ◽  
Defense Mechanisms ◽  
Defense Mechanism ◽  
Denial Of Service ◽  
Distributed Denial Of Service ◽  
Network Environment ◽  
Ddos Attacks ◽  
Application Layer ◽  
New Approach ◽  
Ddos Attack

In a network environment, Distributed Denial of Service (DDoS) attacks eemploys a network or server is unavailable to its normal users. Application-layer Distributed Denial of Service (App-DDoS) attacks are serious issues for the webserver itself. The multitude and variety of such attacks and defense approaches are overwhelming. This paper here follows, we analyze the different defense mechanisms for application-layer DDoS attacks and proposes a new approach to defend using machine learning.

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.

scholarly journals Reducing distributed denial of service (DDoS) attacks using client puzzle mechanism

2017 ◽  
Vol 7 (1.1) ◽  
pp. 230
Author(s):  
C. Vasan Sai Krishna ◽  
Y. Bhuvana ◽  
P. Pavan Kumar ◽  
R. Murugan
Keyword(s):  
Denial Of Service ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Dos Attack ◽  
Computing Power ◽  
Server Side ◽  
Ddos Attack ◽  
Client Machine ◽  
Client Side

In a typical DoS attack, the attacker tries to bring the server down. In this case, the attacker sends a lot of bogus queries to the server to consume its computing power and bandwidth. As the server’s bandwidth and computing power are always greater than attacker’s client machine, He seeks help from a group of connected computers. DDoS attack involves a lot of client machines which are hijacked by the attacker (together called as botnet). As the server handles all these requests sent by the attacker, all its resources get consumed and it cannot provide services. In this project, we are more concerned about reducing the computing power on the server side by giving the client a puzzle to solve. To prevent such attacks, we use client puzzle mechanism. In this mechanism, we introduce a client-side puzzle which demands the machine to perform tasks that require more resources (computation power). The client’s request is not directly sent to the server. Moreover, there will be an Intermediate Server to monitor all the requests that are being sent to the main server. Before the client’s request is sent to the server, it must solve a puzzle and send the answer. Intermediate Server is used to validate the answer and give access to the client or block the client from accessing the server.

Cluster-Based Countermeasures for DDoS Attacks

2016 ◽  
pp. 206-227
Author(s):  
Mohammad Jabed Morshed Chowdhury ◽  
Dileep Kumar G
Keyword(s):  
Unsupervised Learning ◽  
Network Traffic ◽  
Denial Of Service ◽  
Security Threats ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Ddos Attack ◽  
Real Progress ◽  
Bandwidth Capacity

Distributed Denial of Service (DDoS) attack is considered one of the major security threats in the current Internet. Although many solutions have been suggested for the DDoS defense, real progress in fighting those attacks is still missing. In this chapter, the authors analyze and experiment with cluster-based filtering for DDoS defense. In cluster-based filtering, unsupervised learning is used to create profile of the network traffic. Then the profiled traffic is passed through the filters of different capacity to the servers. After applying this mechanism, the legitimate traffic will get better bandwidth capacity than the malicious traffic. Thus the effect of bad or malicious traffic will be lesser in the network. Before describing the proposed solutions, a detail survey of the different DDoS countermeasures have been presented in the chapter.

Defending against Distributed Denial of Service

2011 ◽  
pp. 121-129
Author(s):  
Yang Xiang ◽  
Wanlei Zhou
Keyword(s):  
Web Sites ◽  
Credit Card ◽  
Denial Of Service ◽  
Online Gambling ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Web Traffic ◽  
Internet Applications ◽  
Ddos Attack ◽  
Interactive Advertising

Recently the notorious Distributed Denial of Service (DDoS) attacks made people aware of the importance of providing available data and services securely to users. A DDoS attack is characterized by an explicit attempt from an attacker to prevent legitimate users of a service from using the desired resource (CERT, 2006). For example, in February 2000, many Web sites such as Yahoo, Amazon.com, eBuy, CNN.com, Buy. com, ZDNet, E*Trade, and Excite.com were all subject to total or regional outages by DDoS attacks. In 2002, a massive DDoS attack briefly interrupted Web traffic on nine of the 13 DNS “root” servers that control the Internet (Naraine, 2002). In 2004, a number of DDoS attacks assaulted the credit card processor Authorize. net, the Web infrastructure provider Akamai Systems, the interactive advertising company DoubleClick (left that company’s servers temporarily unable to deliver ads to thousands of popular Web sites), and many online gambling sites (Arnfield, 2004). Nowadays, Internet applications face serious security problems caused by DDoS attacks. For example, according to CERT/CC Statistics 1998-2005 (CERT, 2006), computer-based vulnerabilities reported have increased exponentially since 1998. Effective approaches to defeat DDoS attacks are desperately demanded (Cisco, 2001; Gibson, 2002).

scholarly journals A Feature Analysis Based Identifying Scheme Using GBDT for DDoS with Multiple Attack Vectors

2019 ◽  
Vol 9 (21) ◽  
pp. 4633 ◽  
Author(s):  
Jian Zhang ◽  
Qidi Liang ◽  
Rui Jiang ◽  
Xi Li
Keyword(s):  
Success Rate ◽  
Denial Of Service ◽  
Detection Algorithm ◽  
Feature Analysis ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Detection Capability ◽  
Ddos Attack ◽  
Attack Mitigation ◽  
Multiple Attack

In recent years, distributed denial of service (DDoS) attacks have increasingly shown the trend of multiattack vector composites, which has significantly improved the concealment and success rate of DDoS attacks. Therefore, improving the ubiquitous detection capability of DDoS attacks and accurately and quickly identifying DDoS attack traffic play an important role in later attack mitigation. This paper proposes a method to efficiently detect and identify multivector DDoS attacks. The detection algorithm is applicable to known and unknown DDoS attacks.

scholarly journals Intelligent Traffic Classification for Detecting DDoS Attacks using SDN/OpenFlow

2021 ◽  
Author(s):  
◽  
Jarrod Bakker
Keyword(s):  
Denial Of Service ◽  
Network Control ◽  
Traffic Classification ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Network Information ◽  
Ddos Attack ◽  
Machine Learning Methods ◽  
Attack Scenario ◽  
And Control

<p>Distributed denial of service (DDoS) attacks utilise many attacking entities to prevent legitimate use of a resource via consumption. Detecting these attacks is often difficult when using a traditional networking paradigm as network information and control are not centralised. Software-Defined Networking is a recent paradigm that centralises network control, thus improving the ability to gather network information. Traffic classification techniques can leverage the gathered data to detect DDoS attacks.This thesis utilises nmeta2, a SDN-based traffic classification architecture, to study the effectiveness of machine learning methods to detect DDoS attacks. These methods are evaluated on a physical network testbed to demonstrate their application during a DDoS attack scenario.</p>

scholarly journals Detecting High and Low Intensity Distributed Denial of Service (DDoS) Attacks

2021 ◽  
Author(s):  
◽  
Abigail Koay
Keyword(s):  
Information Sharing ◽  
Detection System ◽  
Denial Of Service ◽  
Attack Detection ◽  
Traffic Classification ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Low Intensity ◽  
Ddos Attack ◽  
Ddos Attack Detection

<p>High and low-intensity attacks are two common Distributed Denial of Service (DDoS) attacks that disrupt Internet users and their daily operations. Detecting these attacks is important to ensure that communication, business operations, and education facilities can run smoothly. Many DDoS attack detection systems have been proposed in the past but still lack performance, scalability, and information sharing ability to detect both high and low-intensity DDoS attacks accurately and early. To combat these issues, this thesis studies the use of Software-Defined Networking technology, entropy-based features, and machine learning classifiers to develop three useful components, namely a good system architecture, a useful set of features, and an accurate and generalised traffic classification scheme. The findings from the experimental analysis and evaluation results of the three components provide important insights for researchers to improve the overall performance, scalability, and information sharing ability for building an accurate and early DDoS attack detection system.</p>

scholarly journals Detection and Prevention Algorithm of DDoS Attack Over the IOT Networks

TEM Journal ◽  
2020 ◽  
pp. 899-906
Keyword(s):  
Denial Of Service ◽  
The Other ◽  
High Rate ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Huge Number ◽  
Security Issues ◽  
Ddos Attack ◽  
Legitimate User ◽  
The Impact

One of the most notorious security issues in the IoT is the Distributed Denial of Service (DDoS) attack. Using a large number of agents, DDoS attack floods the host server with a huge number of requests causing interrupting and blocking the legitimate user requests. This paper proposes a detection and prevention algorithm for DDoS attacks. It is divided into two parts, one for detecting the DDoS attack in the IoT end devices and the other for mitigating the impact of the attack placed on the border router. Also, it has the ability to differentiate the High-rate from the Lowrate DDoS attack accurately and defend against these two types of attacks. It is implemented and tested against different scenarios to dissect their efficiency in detecting and mitigating the DDoS attack.

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.

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