DDOS distributed denial-of-service IEEE PAPERS AND PROJECTS-2020



a denial-of-service attack is a cyber-attack in which the perpetrator seeks to make a machine or network resource unavailable to its intended users by temporarily or indefinitely disrupting services of a host connected to the Internet



Poseidon: Mitigating volumetric ddos attacks with programmable switches
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Distributed Denial-of-Service ( DDoS ) attacks have become a critical threat to the Internet. Due to the increasing number of vulnerable Internet of Things (IoT) devices, attackers can easily compromise a large set of nodes and launch highvolume DDoS attacks from the

Impact analysis of SYN flood DDoS attack on HAProxy and NLB cluster-based web servers
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In recent, the high available internet service is the main demand of most people. However, online services occasionally become inaccessible due to various threats and attacks. Synchronization (SYN) flood distributed denial of service ( DDoS ) is the most used and has a

Why would we get attacked An analysis of attackers aims behind DDoS attacks
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Reliable availability to the internet and internet-based services is crucial in todays world. DDoS attacks pose a severe threat to the availability of such online resources especially owing to booters virtually everyone can execute them nowadays. In order to appropriately

Naïve Bayes Classifier to Mitigate the DDoS Attacks Severity in Ad-Hoc Networks
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Ad-Hoc networks are becoming more popular due to their unique characteristics. As there is no centralized control, these networks are more vulnerable to various attacks, out of which Distributed Denial of Service ( DDoS ) attacks consider as more severe attacks. DDoS attack Abstract Distributed Denial-of-Service ( DDoS ) attack has been a serious threat to the availability feature of cloud computing. As traditional DDoS attacks are implemented using a huge volume of malicious traffic, the detection of such attacks becomes a naive task. To

Application-Layer DDoS Defense with Reinforcement Learning
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Page 1. Application-Layer DDoS Defense with Reinforcement Learning June 1 2020. Yebo Feng, Li, Thanh Nguyen Computer and Information Science Department University of Oregon IEEE/ACM International Symposium on Quality of Service (IWQoS) Page 2 Today, the providers of cloud computing services are among the most prominent service suppliers worldwide. Availability of cloud services is one of the most important concerns of cloud service providers (CSPs) and cloud users (CUs). Distributed Denial of Service ( DDoS )In the current internet world, most of the services, businesses and other things are mostly relying on the cloud services let it be mail service, social medias, payment gateways, and nowadays traditional computing and data storage of businesses are done in the cloud

Scheduling DDoS Cloud Scrubbing in ISP Networks via Randomized Online Auctions
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While both Internet Service Providers (ISPs) and third-party Security Service Providers (SSPs) offer Distributed Denial-of-Service ( DDoS ) mitigation services through cloud-based scrubbing centers, it is often beneficial for ISPs to outsource part of the traffic scrubbing to

Towards Detection of DDoS Attacks for Next-Gen Industrial Internet of Things
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In this work, we present a deep learning based Distributed Denial of Service ( DDoS ) detection system for next generation Industrial Internet of things (IIoT). Next generation IIoT stems from the fact that as 3GPP Release 16 is finalised on July 20 the need to achieveAbstract Denial of Service (DoS) and Distributed Denial of Service ( DDoS ) attacks can largely damage the availability of the cloud services and can be effectively initiated by utilizing different tools, prompting financial harm or influencing the reputation. Consequently Distributed denial-of-service ( DDoS ) attacks are nowadays easy and cheap to carry out, and have become bigger and more frequent over the last years. Cloud-based scrubbers have emerged as a service which victims can hire on demand to fend off attacks. There are manyAbstract Internet of Things (IoT) involves all the surrounding with smart devices to Internet and has been gaining more recognition because it provides substantial benefits in comparison to other systems. Further, due to the decentralized nature of IoT network many

An Intelligent and Time-Efficient DDoS Identification Framework for Real-Time Enterprise Networks
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Enterprise networks face a magnitude of threats that are managed and mitigated with a combination of proprietary and third-party security tools and services. However, the techniques and principles employed by the said tools, techniques and services are quite

A Quantitative Study of DDoS and E- DDoS Attacks on WiFi Smart Home Devices
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Internet of Things (IoT) has facilitated the prosperity of smart homes, providing conveniences for everyones daily lives. However, smart home IoT devices are often vulnerable to various security attacks. This paper quantifies the impact of Distributed Denial of Service ( DDoS )

The Survey DDoS Attack Prevention and Defense Technique
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Without the security measures and controls, our data might be subjected to an attack. The DDoS attack is an attempt of attacking in a distributed fashion to make a server and its resources unavailable to its authorized users. The DDoS attack is a malicious attempt to

APPLICATION LAYER DDoS ATTACK DETECTION IN THE PRESENCE OF FLASH CROWD
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Application layer DDoS attacks are growing at an alarming rate in terms of attack intensity and number of attacks. Attackers target websites of government agencies as well as private business for different motives. In some situations, application layer DDoS attacks occur

Towards a unified in-network DDoS detection and mitigation strategy
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Distributed Denial of Service ( DDoS ) attacks have terrorized our networks for decades, and with attacks now reaching 1.7 Tbps, even the slightest latency in detection and subsequent remediation is enough to bring an entire network down. Though strides have been made to

DDoS Attack Detection via Multi-Scale Convolutional Neural Network
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Distributed Denial-of-Service ( DDoS ) has caused great damage to the network in the big data environment. Existing methods are characterized by low computational efficiency, high false alarm rate and high false alarm rate. In this paper, we propose a DDoS attack detection Cyber security attacks and defenses are constantly evolving, requiring us to re-tool our networks at a regular pace. New systems are usually evaluated within restricted corporate or enterprise networks, with limited or no access for researchers and cyber security students. In

Mitigating DDoS Attacks in Cloud Network using Fog and SDN: A Conceptual Security Framework
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In recent years, Cloud computing has changed the entire Information Technology (IT) domain due to bi-overlay focus points as against the traditional computer networks, ie, capital expenditure (CapEx) and operational (OpEx) reduction. Both Cloud users(CS) data

A two level security mechanism to detect a DDoS flooding attack in software-defined networks using entropy-based and C4. 5 technique.
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Software-Defined Network (SDN) has recently emerged as a network paradigm due to its high network programmability and flexibility which can overcome the problem in traditional networks by decoupling the control plane from the data plane. The data plane will forward Most of the people across the world accesses Internet based applications and web services in their daily activities. Distributed Denial of Service ( DDoS ) attack is one of the well-known attacks that crush the computing and communication resources of a web server hosting

DDOS Attacks Analysis Based On Machine Learning in Challenges of Global Changes
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This article will allow users to search for the necessary information about DDOS attacks around the world and predict future attacks, check whether their network protection is working, and help to debug it. The purpose is to investigate possible DDOS attacks, predict

Certain improvements to Location aided packet marking and DDoS attacks in internet
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Security is the primary factor considered during any transmission process. While providing the needed service, security maintained during the entire process noticed. Here security indicates the protection given to the components situated in the network physically and

DoS and DDoS Attack Detection Using Deep Learning and IDS
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In the recent years, Denial-of-Dervice (DoS) orDistributed Denial-of-Service ( DDoS ) attack has spread greatly and attackers make online systems unavailable to legitimate users by sending huge number of packets to the target system. In this paper, we proposed two

CLASSIFICATION OF ATTACKS OF DDOS AND THEIR DEFENSE METHODS UTILIZING INTRUSION PREVENTION SYSTEM
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ABSTRACT DDoS (Distributed Denial of Service) Attacks has been progressively discovered to be having an impact on the normal operation of organizations triggering millions and millions of dollars of damages. Companies are attempting their best efforts to

Detection DDOS Attacks Using Machine Learning Methods
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Wishing to communicate with each other of people contributes to improving technology, and it has made the internet concept an indispensable part of our daily life. Cyber attacks from extranets to enterprise networks or intranets, which are used as personal, can cause

Data mining approach and security over Ddos attacks
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The benefit of on-demand services is one of the most important benefits of using cloud computing; therefore, the payment method in the cloud environment is pay per use. This feature results in a new type of DDOS attack called Economic Denial of Sustainability

An Optimized Approach-Based Machine Learning to Mitigate DDoS Attack in Cloud Computing
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With the emerging growth of cloud computing technology and on-demand services, users can access cloud services and software freely and applications based on the pay-as-you go concept. This innovation reduced service costs and made them cheaper with high

The Forensics of DDoS Attacks in the Fifth Generation Mobile Networks Based on Software-Defined Networks.
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The number of devices connected to the Internet has been increasing with the emergence of the Internet of things technology. Although it has many advantages, the weak configuration of Internet of things devices and the higher number of such devices provide a good potential Abstract The Internet of Things (IoT) is an ever expanding discipline encompassing all orbits of life, and its development has resulted in enormous benefits. IoT has made it possible for simple electronic objects to participate in the Internet. However, the growth of IoT has alsoIn a cloud computing environment, the Distributed Denial of Service ( DDoS ) attack is considered as the crucial issue that needs to be addressed in ensuring the availability of resources that emerge due to the compromisation of hosts. The process of detecting and

Game Theory for Strategic DDoS Mitigation
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Mitigating DDoS attacks on the networks is an important security challenge for the Internet Service Providers. Recent work has shown a flexible and elastic DDoS defense mechanism via Software Defined Networking/Network functions virtualization and such systems are

IoTSTEED: Bot-side Defense to IoT-based DDoS Attacks (Extended)
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We propose IoTSTEED, a system running in edge routers to defend against Distributed Denial-of-Service ( DDoS ) attacks launched from compromised Internet-of-Things (IoT) devices. IoTSTEED watches traffic that leaves and enters the home network, detecting IoT

MACHINE LEARNING APPROACH FOR DDOS DETECTION
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Distributed denial of service ( DDoS ) attacks are a major threat to any network-based service provider. The ability of an attacker to harness the power of a lot of compromised devices to launch an attack makes it even more complex to handle. This complexity can increase evenThe system is an advancement to ad-hoc wireless network its security. A mobile ad-hoc network (MANET) faces a malicious activities cause, unlike any other network manet cannot support heavy security algorithms techniques and algorithms because of lack of power

4 Overview of Talks 4.1 DDoS Still Challenging 20 Years Later
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We provide an overview of the fundamental flaws that have contributed to allowing the distributed denial-of-service ( DDoS ) phenomenon [ 2] to happen over the last 20 years. This includes design flaws for the Internet and its protocols, management decisions, and

DDOS ATTACKS USING MACHINE LEARNING
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? Distributed Denial of Service are a kind of cyber attacks that make the network-grid unavailable to its users. These attacks are growing exponentially so as to mitigate these attacks has been a challenging task. An active student portal was built on a cloud computingThe article deals with a problem of detecting low and slow distributed denial of service ( DDoS ) attacks. It is widely known that the detection of slow DDoS attacks differs significantly from volume based attacks, because slow attacks do not increase the intensity of traffic in the Application layer distributed denials of service ( DDoS ) attacks have become a severe threat to the security of web servers. DDoS is a rapidly growing problem. These attacks evade most intrusion prevention systems by sending numerous HTTP requests. Since most of these

RESEARCH ON DDOS ATTACK DETECTION BASED ON ISOLATION FOREST AND KMeans ALGORITHM IN SDN
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Compared with the traditional network, as a new generation of network architecture, Software Defined Network (SDN) has the advantages of separation of control and forwarding, centralized control, and is more suitable for todays complex and changeable

A New DDoS Detection Method in Software Defined Network
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Abstract Software Defined Networking (SDN) is a new network architecture in which network control is separated from direct traffic and is programmed directly. Any change in network information and its configuration can be easily implemented in software by using the

NUMEROUS TOPOGRAPHIES BASED QUASI SUPERVISED CLUSTERING DDOS DETECTION METHOD
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DDoS attack stream from different agent host converged at victim host will become very large, which will lead to system halt or network congestion. Therefore, it is necessary to propose an effective method to detect the DDoS attack behavior from the massive data Abstract Named Data Networking (NDN) is a new and attractive paradigm that got a broad interest in recent researches as a potential alternative for the existing IP-based (hostbased) Internet architecture. Security is considered explicitly as one of the most critical issues aboutSince the last decade, Internet users increased rapidly and most of them are depending on the World Wide Web (WWW) service for achieving daily routine. Having Internet access and especially WWW sometimes users face difficulties because of various security problems

Towards Explicable and Adaptive DDoS Traffic Classification
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The traffic classification of the Distributed Denial of Service ( DDoS ) attack is a well-studied but not completed field. In this paper, we propose a learning-based DDoS traffic detection and classification method, which utilizes a modified k-nearest neighbors algorithm to detect

Semi-supervised Machine Learning Approach for DDoS Detection
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Abstract Even though advanced Machine Learning (ML) techniques have been adopted for DDoS detection, the attack remains a major threat of the Internet. Most of the existing ML- based DDoS detection approaches are under two categories: supervised and unsupervised

Evaluating the Impact of Feature Selection Methods on the Performance of the Machine Learning Models in Detecting DDoS Attacks
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Heaps of Data lie in network equipment of the organizations. To break down this information and reach some significant inferences is inconceivable for the present day IDS (Intrusion Detection System). Moreover, their signature-based defense mechanisms are ineffective in

Classification of DDoS Attacks A Survey
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Availability ensures the data or service is available when needed. DoS and DDoS attacks are the greatest threat to service availability in cloud computing. This paper focuses on the details of the various types of DDoS attacks Classification of DDoS Attacks The DDoS attacks, being

Two Decades of DDoS Attacks and Defenses
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Distributed denial-of-service ( DDoS ) attacks are easy to launch but difficult to defend against. Despite two decades of DDoS research, DDoS attacks continue to impose threats to todays networks. Recent attacks such as [ 3] have shown that resourceful attackers can

Performance comparison of DDoS attack detection with different machine learning algorithms and four feature selection methods
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Kyushu University Graduate School of Information Science and Electrical Engineering† 1† 2.3 Abstract:: Most DDoS attack detection methods use machine learning. In this study, we compared RandamForest, LightGBM, Lasso, and ElasticNet by comparing the relationship

Towards Intelligent Defense against Application-Layer DDoS with Reinforcement Learning
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Application-layer distributed denial-of-service (L7 DDoS ) attacks, by exploiting application- layer requests to overwhelm functions or components of victim servers, has become a major rising threat to todays Internet. However, because the traffic from an L7 DDoS attackImprovement of utilizing cloud computing in the field of Statistics Tools to manage giving available and adaptable capacities to the customers according to demand is starting nowadays. Cloud computing decreased advantages in three levels understood as base The appearance of malicious apps is a serious threat to the Android platform. Most types of network interfaces based on the integrated functions, steal users personal information and start the attack operations. In this paper, we propose an effective and automatic malware

COLLABORATIVE ROUTING PROTOCOL FOR DETECTION OF DDOS ATTACKS IN WIRELESS NETWORKS
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Distributed Denial-of-Service ( DDoS ) attacks continue to trouble network operators and service providers, and with increasing intensity. Effective response to DDoS can be slow and potentially self-defeating, and this is the result of the discrepancy between the serviceInternet and online services are facing many threats. Distributed Denial of Service ( DDOS ) attack is one of these threats. This type of attack is harmful and it is capable of bringing networks or services down within a short period of time. HTTP Flood, TCP SYN Flood, ICMP

Modern DDoS Attacks and Defences-Survey
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Service of Service ( DDoS ) attacks are commonly used to disrupt network services. Attack techniques are always improving and due to the structure of the internet and properties of network protocols it is difficult to keep detection and mitigation techniques up to date. A lot of

A New Cybersecurity Approach for Protecting Cloud Services against DDoS Attacks
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Cybersecurity of cloud services is extremely important, especially when developing web services and cloud apps. Cloud computing depends on internet connections; therefore, the security of its services is constantly under attack. Distributed Denial of Service ( DDoS )One of the most serious threat to network security is Denial of service (DOS) attacks. When this attack is performed in distributed manner it can create more disaster. Lot of research has been carried for the detection of this attack. In this various techniques has been studied and