A Novel Approach to Mitigate DDoS Attack Using Gateway Mechanism

Denial of service is one of the most terrible attacks is the cloning attack of the node, where the attacker captures the knot and extracts its secret information, create replicas and enter them in the network field other malevolent behavior. To detect and mitigate this attack, several static-based detection schemes have been proposed. The detection algorithm based on the node location speed was proposed, to detect the attack of nodes clones in the wireless network. This algorithm reduces the costs of communication, routing, overloading the entire network and improving network performance.

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Intelligent Traffic Classification for Detecting DDoS Attacks using SDN/OpenFlow

10.26686/wgtn.17064107.v1 ◽

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>

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Threshold Based Algorithm for the Detection of DDOS Attack in Wireless Sensor Networks

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.c4158.118419 ◽

2019 ◽

Vol 8 (4) ◽

pp. 1869-1873

Keyword(s):

Denial Of Service ◽

Research Work ◽

Industrial Applications ◽

Wireless Sensor ◽

Distributed Denial Of Service ◽

Black Hole Attack ◽

Malicious Nodes ◽

Ddos Attack ◽

Novel Approach ◽

Overall Functioning

The self-configuring type of network in which the sensor node are deployed in such a manner that they can join or leave the network when they want is known as wireless sensor network. The nodes start communicating with each other in order to transmit important information within the network. As this type of network is decentralized in nature there are numerous malicious nodes which might enter the network. There are so many attacks possible on WSN, in Distributed Denial of Service (DDOS) attacks, malicious nodes adapts many attacks such as flooding attack, black hole attack and warm hole attack, to halt the overall functioning of network. The risks are even more when we talk about military and industrial applications. The DDoS is an active type of attack. When the DDoS attack occurs in the network, it minimizes the lifetime of the network and also increases the overall energy consumption of the network. In order to detect the malicious nodes from the network which cause the DDoS attack, a novel approach is to be proposed in this research work.

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Real-Time Detection of Application-Layer DDoS Attack Using Time Series Analysis

Journal of Control Science and Engineering ◽

10.1155/2013/821315 ◽

2013 ◽

Vol 2013 ◽

pp. 1-6 ◽

Cited By ~ 9

Author(s):

Tongguang Ni ◽

Xiaoqing Gu ◽

Hongyuan Wang ◽

Yu Li

Keyword(s):

Time Series ◽

Denial Of Service ◽

Support Vector ◽

Svm Classifier ◽

Ddos Attacks ◽

Application Layer ◽

Ip Address ◽

Detection Systems ◽

Ddos Attack ◽

Novel Approach

Distributed denial of service (DDoS) attacks are one of the major threats to the current Internet, and application-layer DDoS attacks utilizing legitimate HTTP requests to overwhelm victim resources are more undetectable. Consequently, neither intrusion detection systems (IDS) nor victim server can detect malicious packets. In this paper, a novel approach to detect application-layer DDoS attack is proposed based on entropy of HTTP GET requests per source IP address (HRPI). By approximating the adaptive autoregressive (AAR) model, the HRPI time series is transformed into a multidimensional vector series. Then, a trained support vector machine (SVM) classifier is applied to identify the attacks. The experiments with several databases are performed and results show that this approach can detect application-layer DDoS attacks effectively.

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Artificial Intelligence-Enabled DDoS Detection for Blockchain-Based Smart Transport Systems

Sensors ◽

10.3390/s22010032 ◽

2021 ◽

Vol 22 (1) ◽

pp. 32

Author(s):

Tong Liu ◽

Fariza Sabrina ◽

Julian Jang-Jaccard ◽

Wen Xu ◽

Yuanyuan Wei

Keyword(s):

Deep Learning ◽

Transport System ◽

Public Transport ◽

Denial Of Service ◽

Transport Systems ◽

Public Transport System ◽

Blockchain Technology ◽

Novel Approach ◽

Wide Range ◽

Security Properties

A smart public transport system is expected to be an integral part of our human lives to improve our mobility and reduce the effect of our carbon footprint. The safety and ongoing maintenance of the smart public transport system from cyberattacks are vitally important. To provide more comprehensive protection against potential cyberattacks, we propose a novel approach that combines blockchain technology and a deep learning method that can better protect the smart public transport system. By the creation of signed and verified blockchain blocks and chaining of hashed blocks, the blockchain in our proposal can withstand unauthorized integrity attack that tries to forge sensitive transport maintenance data and transactions associated with it. A hybrid deep learning-based method, which combines autoencoder (AE) and multi-layer perceptron (MLP), in our proposal can effectively detect distributed denial of service (DDoS) attempts that can halt or block the urgent and critical exchange of transport maintenance data across the stakeholders. The experimental results of the hybrid deep learning evaluated on three different datasets (i.e., CICDDoS2019, CIC-IDS2017, and BoT-IoT) show that our deep learning model is effective to detect a wide range of DDoS attacks achieving more than 95% F1-score across all three datasets in average. The comparison of our approach with other similar methods confirms that our approach covers a more comprehensive range of security properties for the smart public transport system.

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Intelligent Traffic Classification for Detecting DDoS Attacks using SDN/OpenFlow

10.26686/wgtn.17064107 ◽

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>

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Structural characteristics of marandu palisadegrass swards subjected to continuous stocking and contrasting rhythms of growth

Scientia Agricola ◽

10.1590/s0103-90162010000100004 ◽

2010 ◽

Vol 67 (1) ◽

pp. 23-30 ◽

Cited By ~ 18

Author(s):

Priscila de Mesquita ◽

Sila Carneiro da Silva ◽

Adenilson José Paiva ◽

Fábio Olegário Caminha ◽

Lilian Elgalise Techio Pereira ◽

...

Keyword(s):

Structural Characteristics ◽

Light Interception ◽

Grazing Management ◽

Nitrogen Application ◽

Area Index ◽

Application Rates ◽

Wide Range ◽

And Control ◽

Sward Structure ◽

Monitor And Control

The concept of sward target has been used recently to characterise grazing management practices, but its efficiency to monitor and control sward structure questioned since it corresponds to a single sward structural feature, usually sward surface height. The objective of this experiment was to evaluate sward structure and its patterns of variation throughout the year on continuously stocked marandu palisadegrass swards maintained at 30 cm and subjected to contrasting rhythms of growth from January 2007 to April 2008. Treatments corresponded to three nitrogen application rates (150, 300 and 450 kg ha-1 of N) plus the control (no N fertilisation), and were allocated to experimental units according to a complete randomised block design, with four replications. Sward herbage mass, morphological composition, leaf area index (LAI), foliage angle and light interception were evaluated. The increase in nitrogen application rates resulted in increased sward herbage mass, proportion of leaf and stem, and reduction in the proportion of dead material. These modifications were in line with the increase in LAI and reduction in foliage angle, although they did not modify sward light interception. Despite the wide range of nitrogen application rates used, there was a common pattern of variation in sward structure. Overall, changes in sward structural characteristics generated by the range of growth rhythms studied were small, indicating that sward height corresponded to an efficient way to monitor and control the grazing process and sward structure, and can be used to define targets of grazing management.

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A Novel Approach of Detection and Mitigation of DDOS Attack

International Institute of Engineers April 20-21, 2015 Bangkok (Thailand) ◽

10.15242/iie.e0415036 ◽

2015 ◽

Keyword(s):

Ddos Attack ◽

Novel Approach

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SuperMOCA - Commercially-derived standards for space mission monitor and control

10.2514/6.1998-5127 ◽

1998 ◽

Author(s):

Michael Jones ◽

Carlos Carrion ◽

Elin Klaseen

Keyword(s):

Space Mission ◽

And Control ◽

Monitor And Control

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THE SOME QUESTIONS OF AUTONOMOUS MOTION AND MANAGEMENT OF LAND-MOBILE ROBOTIC COMPLEXES FOR UKRAINIAN GROUND FORCESE

Collection of scientific works of Odesa Military Academy ◽

10.37129/2313-7509.2019.11.53-58 ◽

2019 ◽

pp. 53-58

Author(s):

О. Кravchuk ◽

V. Symonenkov ◽

I. Symonenkova ◽

O. Hryhorev

Keyword(s):

Large Scale ◽

Armed Forces ◽

Distributed Information ◽

Wide Range ◽

Highly Effective ◽

Information Management Systems ◽

Robotic Devices ◽

Principles And Standards ◽

And Control ◽

The Eu

Today, more than forty countries of the world are engaged in the development of military-purpose robots. A number of unique mobile robots with a wide range of capabilities are already being used by combat and intelligence units of the Armed forces of the developed world countries to conduct battlefield intelligence and support tactical groups. At present, the issue of using the latest information technology in the field of military robotics is thoroughly investigated, and the creation of highly effective information management systems in the land-mobile robotic complexes has acquired a new phase associated with the use of distributed information and sensory systems and consists in the transition from application of separate sensors and devices to the construction of modular information subsystems, which provide the availability of various data sources and complex methods of information processing. The purpose of the article is to investigate the ways to increase the autonomy of the land-mobile robotic complexes using in a non-deterministic conditions of modern combat. Relevance of researches is connected with the necessity of creation of highly effective information and control systems in the perspective robotic means for the needs of Land Forces of Ukraine. The development of the Armed Forces of Ukraine management system based on the criteria adopted by the EU and NATO member states is one of the main directions of increasing the effectiveness of the use of forces (forces), which involves achieving the principles and standards necessary for Ukraine to become a member of the EU and NATO. The inherent features of achieving these criteria will be the transition to a reduction of tasks of the combined-arms units and the large-scale use of high-precision weapons and land remote-controlled robotic devices. According to the views of the leading specialists in the field of robotics, the automation of information subsystems and components of the land-mobile robotic complexes can increase safety, reliability, error-tolerance and the effectiveness of the use of robotic means by standardizing the necessary actions with minimal human intervention, that is, a significant increase in the autonomy of the land-mobile robotic complexes for the needs of Land Forces of Ukraine.

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