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 Performance Analysis of an Effective Approach to Protect Cloud Systems against Application Layer Based Attacks

2019 ◽  
Vol 15 (03) ◽  
pp. 82
Author(s):  
Hosam F. El-Sofany ◽  
Samir Abou El-Seoud
Keyword(s):  
Cloud Computing ◽  
Web Applications ◽  
Complexity Analysis ◽  
Denial Of Service ◽  
Ddos Attacks ◽  
Application Layer ◽  
Analysis Model ◽  
New Paradigm ◽  
Dos Attacks ◽  
Web Based

Cloud computing is a new paradigm for hosting hardware and software resources and provides a web-based services to organizations and consumers. It also provides an easy to use and on-demand access to cloud based computing resources that can be published by easy, minimal administration and with a great efficiency. Services of cloud computing are accessing and sharing through internet connection thus it is open for attacker to attack on its security. Application layer based attacks is one of Distributed Denial of Service attacks (DDoS) that can cause a big problem in cloud security. The main objective of DDoS attacks is to infect computer resources (e.g., software applications, network, CPU, etc.) and make them not working properly for the authorized users. In DDoS, the attacker tries to overload the web-based service with traffic. HTTP and XML-based DDoS attacks are founded under the application layer based category of DoS attacks. This category of attack is focused on particular web applications. The main objective of this research paper is to introduce an effective approach to protect cloud-based systems against application layer based attacks. Complexity analysis, effectiveness and performance evaluations of the presented approach are presented.  The feedbacks of the experimental results were highly promising, for protecting cloud computing systems against both DoS and DDoS attacks. Correlation analysis model is also used to validate the efficiency of the proposed approach.

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.

scholarly journals A Novel Protective Framework for Defeating HTTP-Based Denial of Service and Distributed Denial of Service Attacks

2015 ◽  
Vol 2015 ◽  
pp. 1-19 ◽  
Author(s):  
Mohammed A. Saleh ◽  
Azizah Abdul Manaf
Keyword(s):  
Web Applications ◽  
Denial Of Service ◽  
Optimal Solution ◽  
High Rate ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Innovative Design ◽  
Flash Crowd ◽  
Black List ◽  
Efficient Protection

The growth of web technology has brought convenience to our life, since it has become the most important communication channel. However, now this merit is threatened by complicated network-based attacks, such as denial of service (DoS) and distributed denial of service (DDoS) attacks. Despite many researchers’ efforts, no optimal solution that addresses all sorts of HTTP DoS/DDoS attacks is on offer. Therefore, this research aims to fix this gap by designing an alternative solution called a flexible, collaborative, multilayer, DDoS prevention framework (FCMDPF). The innovative design of the FCMDPF framework handles all aspects of HTTP-based DoS/DDoS attacks through the following three subsequent framework’s schemes (layers). Firstly, an outer blocking (OB) scheme blocks attacking IP source if it is listed on the black list table. Secondly, the service traceback oriented architecture (STBOA) scheme is to validate whether the incoming request is launched by a human or by an automated tool. Then, it traces back the true attacking IP source. Thirdly, the flexible advanced entropy based (FAEB) scheme is to eliminate high rate DDoS (HR-DDoS) and flash crowd (FC) attacks. Compared to the previous researches, our framework’s design provides an efficient protection for web applications against all sorts of DoS/DDoS attacks.

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.

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.

Detecting App-DDoS Attacks Based on Marking Access and d-SVDD

2013 ◽  
Vol 347-350 ◽  
pp. 3734-3739 ◽  
Author(s):  
Jin Ling Li ◽  
Bin Qiang Wang
Keyword(s):  
Denial Of Service ◽  
Detection Algorithm ◽  
Decision Boundary ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Application Layer ◽  
Time Space

In order to enhance the extensibility of current attack feature extracted and detection means for App-DDoS(Application Layer Distributed Denial of Service, App-DDoS) attacks, a novel feature extracted method based on marking access and a new detection algorithm named d-SVDD are proposed. After expressing kinds of App-DDoS attacks as characteristic vectors by access marked strategy and feature extracted strategy, d-SVDD algorithm is used for secondary classification and detection of pre-set area around decision boundary based on SVDD. It is proved by experiments that the proposed feature extracted and detection means can realize effective detection for kinds of App-DDoS attacks, both have satisfying time, space and extensibility performance.

scholarly journals New Features of User’s Behavior to Distributed Denial of Service Attacks Detection in Application Layer

2018 ◽  
Vol 14 (12) ◽  
pp. 164
Author(s):  
Silvia Bravo ◽  
David Mauricio
Keyword(s):  
Detection Rate ◽  
Detection Method ◽  
Denial Of Service ◽  
Classification Algorithm ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Application Layer ◽  
Data Set ◽  
The Web

Distributed Denial of Service (DDoS) attacks are a threat to the security of red. In recent years, these attacks have been directed especially towards the application layer. This phenomenon is mainly due to the large number of existing tools for the generation of this type of attack. The highest detection rate achieved by a method in the application capacity is 98.5%. Therefore, the problem of detecting DDoS attacks persists. In this work an alternative of detection based on the dynamism of the web user is proposed. To do this, evaluate the user's characteristics, mouse functions and right click. For the evaluation, a data set of 11055 requests was used, from which the characteristics were extracted and entered into a classification algorithm. To that end, it can be applied once in Java for the classification of real users and DDoS attacks. The results showed that the evaluated characteristics achieved an efficiency of 100%. Therefore, it is concluded that these characteristics show the dynamism of the user and can be used in a detection method of DDoS attacks.

scholarly journals Systematic review of aspects of DDoS attacks detection

2019 ◽  
Vol 14 (1) ◽  
pp. 155 ◽  
Author(s):  
Silvia Bravo ◽  
David Mauricio
Keyword(s):  
Systematic Review ◽  
Computer Security ◽  
Scientific Literature ◽  
Denial Of Service ◽  
Detection Accuracy ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Detection Mechanism ◽  
Location Point ◽  
Adequate Analysis

Distributed Denial of Service attacks (DDoS) are one of the biggest problems facing the Internet. To eliminate this type of attack, the number of which has increased in the period under study, various methods of defense have been proposed. However a detection mechanism that is able to completely counteract the attacks has not yet been found. Therefore, detection and defense against DDoS attacks is of great importance for specialists engaged in computer security. This paper presents a systematic review of the scientific literature on methods of detecting DDoS attacks. From the literature the main aspects related to detection have been formulated. Six aspects for analysis in this investigation were identified: techniques, variables, tools, deployment location, point in time and detection accuracy. It was found that each technique used for the detection of attacks exploits certain characteristics of the network traffic, user requests and specific tools. Finally, it managed to identify the mechanisms that have the highest detection accuracy, such as the datasets they use. It has been concluded that an adequate analysis of the above aspects of detection of DDoS attacks can make a useful contribution to designing an appropriate strategy for neutralizing the attacks.

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