Distributed Denial of Service (DDoS) attacks today have been amplified into gigabits volume with broadband Internet access; at the same time, the use of more powerful botnets and common DDoS mitigation and protection solutions implemented in small and large organizations’ networks and servers are no longer effective. Our survey provides an in-depth study on the current largest DNS reflection attack with more than 300 Gbps on Spamhaus.org. We have reviewed and analysed the current most popular DDoS attack types that are launched by the hacktivists. Lastly, effective cloud-based DDoS mitigation and protection techniques proposed by both academic researchers and large commercial cloud-based DDoS service providers are discussed.
Nowadays DNS is used to load balance, failover, and geographically redirect connections. DNS has become so pervasive it is hard to identify a modern TCP/IP connection that does not use DNS in some way. Unfortunately, due to the reliability built into the fundamental RFC-based design of DNS, most IT professionals don't spend much time worrying about it. If DNS is maliciously attacked — altering the addresses it gives out or taken offline the damage will be enormous. Whether conducted for political motives, financial gain, or just the notoriety of the attacker, the damage from a DNS attack can be devastating for the target.
In this research we will review different DNS advanced attacks and analyze them. We will survey some of the most DNS vulnerabilities and ways of DNS attacks protection.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology
PASSWORD BASED SCHEME AND GROUP TESTING FOR DEFENDING DDOS ATTACKSIJNSA Journal
DOS ATTACKS ARE ONE OF THE TOP SECURITY PROBLEMS AFFECTING NETWORKS AND DISRUPTING SERVICES TO
LEGITIMATE USERS. THE VITAL STEP IN DEALING WITH THIS PROBLEM IS THE NETWORK'S ABILITY TO DETECT SUCH
ATTACKS. APPLICATION DDOS ATTACK, WHICH AIMS AT DISRUPTING APPLICATION SERVICE RATHER THAN
DEPLETING THE NETWORK RESOURCE. UP TO NOW ALL THE RESEARCHES MADE ON THIS DDOS ATTACKS ONLY
CONCENTRATES EITHER ON NETWORK RESOURCES OR ON APPLICATION SERVERS BUT NOT ON BOTH. IN THIS PAPER
WE PROPOSED A SOLUTION FOR BOTH THESE PROBLEMS BY AUTHENTICATION METHODS AND GROUP TESTING.
PASSWORD BASED SCHEME AND GROUP TESTING FOR DEFENDING DDOS ATTACKSIJNSA Journal
DOS ATTACKS ARE ONE OF THE TOP SECURITY PROBLEMS AFFECTING NETWORKS AND DISRUPTING SERVICES TO LEGITIMATE USERS. THE VITAL STEP IN DEALING WITH THIS PROBLEM IS THE NETWORK'S ABILITY TO DETECT SUCH ATTACKS. APPLICATION DDOS ATTACK, WHICH AIMS AT DISRUPTING APPLICATION SERVICE RATHER THAN DEPLETING THE NETWORK RESOURCE. UP TO NOW ALL THE RESEARCHES MADE ON THIS DDOS ATTACKS ONLY CONCENTRATES EITHER ON NETWORK RESOURCES OR ON APPLICATION SERVERS BUT NOT ON BOTH. IN THIS PAPER WE PROPOSED A SOLUTION FOR BOTH THESE PROBLEMS BY AUTHENTICATION METHODS AND GROUP TESTING.
This document summarizes DDoS threat trends from 2013 to early 2014 based on attacks seen by Incapsula. Key findings include:
- 81% of network attacks in the last 90 days used multiple vectors simultaneously, with over a third employing 3 or more vectors. This multi-vector approach allows attackers to bypass defenses.
- Large SYN floods combined with regular SYN floods ("SYN combo attacks") accounted for around 75% of large-scale network attacks above 20Gbps.
- NTP amplification attacks increased significantly in early 2014 and became the most common vector for large attacks in February 2014.
- Application layer attacks increased 240% from 2013, with over half originating from India, China, and Iran
This document discusses distributed denial of service (DDoS) attacks. It begins by defining DDoS attacks as using numerous compromised systems, or "zombie machines", to launch a coordinated attack against a target system to overwhelm its bandwidth and resources. The document then discusses how early DDoS attacks worked and how routers have evolved defenses. It describes how modern DDoS attacks are more sophisticated, using botnets of infected systems controlled remotely by attackers to amplify the scale and impact of the attacks.
Using the Web or another research tool, search for alternative means.pdffms12345
Using namespace std;
The expansion of a steel bridge as it heated to a final Celsius temperature, Tf, from an initial
temperature T0 , can be approximated using the following formula:
Increase in length= a* L*(Tf-T0). Where a is the coefficient of expansion that is for steel is
11.7e-6, L is the length of bridge at temperature T0.
Using this formula, write a C++ program that displays a table of expansion length for a steel
bridge that’s 7365 meters long at 0 degrees Celsius, as the temperature increases to 40 degrees in
5 degree increments.
Solution
#include
using namespace std;
float Length(int Tf)
{
const float a = 11.7E-6;
const float L = 7365;
const float To=0;
return a*L*(Tf-To);
}
int main(int argc, char const *argv[])
{
cout<<\"Intitial Temperature\\tFinal Temperature\\tIncreased Length\ \";
for (int i=1;i<=8;i++)
cout<<0<<\" degrees\\t\\t\"<.
Nowadays DNS is used to load balance, failover, and geographically redirect connections. DNS has become so pervasive it is hard to identify a modern TCP/IP connection that does not use DNS in some way. Unfortunately, due to the reliability built into the fundamental RFC-based design of DNS, most IT professionals don't spend much time worrying about it. If DNS is maliciously attacked — altering the addresses it gives out or taken offline the damage will be enormous. Whether conducted for political motives, financial gain, or just the notoriety of the attacker, the damage from a DNS attack can be devastating for the target.
In this research we will review different DNS advanced attacks and analyze them. We will survey some of the most DNS vulnerabilities and ways of DNS attacks protection.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology
PASSWORD BASED SCHEME AND GROUP TESTING FOR DEFENDING DDOS ATTACKSIJNSA Journal
DOS ATTACKS ARE ONE OF THE TOP SECURITY PROBLEMS AFFECTING NETWORKS AND DISRUPTING SERVICES TO
LEGITIMATE USERS. THE VITAL STEP IN DEALING WITH THIS PROBLEM IS THE NETWORK'S ABILITY TO DETECT SUCH
ATTACKS. APPLICATION DDOS ATTACK, WHICH AIMS AT DISRUPTING APPLICATION SERVICE RATHER THAN
DEPLETING THE NETWORK RESOURCE. UP TO NOW ALL THE RESEARCHES MADE ON THIS DDOS ATTACKS ONLY
CONCENTRATES EITHER ON NETWORK RESOURCES OR ON APPLICATION SERVERS BUT NOT ON BOTH. IN THIS PAPER
WE PROPOSED A SOLUTION FOR BOTH THESE PROBLEMS BY AUTHENTICATION METHODS AND GROUP TESTING.
PASSWORD BASED SCHEME AND GROUP TESTING FOR DEFENDING DDOS ATTACKSIJNSA Journal
DOS ATTACKS ARE ONE OF THE TOP SECURITY PROBLEMS AFFECTING NETWORKS AND DISRUPTING SERVICES TO LEGITIMATE USERS. THE VITAL STEP IN DEALING WITH THIS PROBLEM IS THE NETWORK'S ABILITY TO DETECT SUCH ATTACKS. APPLICATION DDOS ATTACK, WHICH AIMS AT DISRUPTING APPLICATION SERVICE RATHER THAN DEPLETING THE NETWORK RESOURCE. UP TO NOW ALL THE RESEARCHES MADE ON THIS DDOS ATTACKS ONLY CONCENTRATES EITHER ON NETWORK RESOURCES OR ON APPLICATION SERVERS BUT NOT ON BOTH. IN THIS PAPER WE PROPOSED A SOLUTION FOR BOTH THESE PROBLEMS BY AUTHENTICATION METHODS AND GROUP TESTING.
This document summarizes DDoS threat trends from 2013 to early 2014 based on attacks seen by Incapsula. Key findings include:
- 81% of network attacks in the last 90 days used multiple vectors simultaneously, with over a third employing 3 or more vectors. This multi-vector approach allows attackers to bypass defenses.
- Large SYN floods combined with regular SYN floods ("SYN combo attacks") accounted for around 75% of large-scale network attacks above 20Gbps.
- NTP amplification attacks increased significantly in early 2014 and became the most common vector for large attacks in February 2014.
- Application layer attacks increased 240% from 2013, with over half originating from India, China, and Iran
This document discusses distributed denial of service (DDoS) attacks. It begins by defining DDoS attacks as using numerous compromised systems, or "zombie machines", to launch a coordinated attack against a target system to overwhelm its bandwidth and resources. The document then discusses how early DDoS attacks worked and how routers have evolved defenses. It describes how modern DDoS attacks are more sophisticated, using botnets of infected systems controlled remotely by attackers to amplify the scale and impact of the attacks.
Using the Web or another research tool, search for alternative means.pdffms12345
Using namespace std;
The expansion of a steel bridge as it heated to a final Celsius temperature, Tf, from an initial
temperature T0 , can be approximated using the following formula:
Increase in length= a* L*(Tf-T0). Where a is the coefficient of expansion that is for steel is
11.7e-6, L is the length of bridge at temperature T0.
Using this formula, write a C++ program that displays a table of expansion length for a steel
bridge that’s 7365 meters long at 0 degrees Celsius, as the temperature increases to 40 degrees in
5 degree increments.
Solution
#include
using namespace std;
float Length(int Tf)
{
const float a = 11.7E-6;
const float L = 7365;
const float To=0;
return a*L*(Tf-To);
}
int main(int argc, char const *argv[])
{
cout<<\"Intitial Temperature\\tFinal Temperature\\tIncreased Length\ \";
for (int i=1;i<=8;i++)
cout<<0<<\" degrees\\t\\t\"<.
The document discusses distributed denial of service (DDoS) attacks, including how they work, common tools and methods used, and examples of recent large-scale DDoS attacks. It provides details on how botnets are used to overwhelm websites and infrastructure with malicious traffic. Specific DDoS attack types like UDP floods, SYN floods, and reflection attacks are outlined. Recent large attacks are described, such as those targeting bitcoin exchanges, social trading platforms, and Hong Kong voting sites ahead of a civil referendum.
An Ultimate Guide to DDos Attacks: Detection, Prevention and MitigationTechApprise
In this ultimate guide, you will learn everything about the Distributed Denial of Service (DDoS) Attacks including What are DDoS attacks, Types of DDos Attack, Major Causes, How to Detect DDoS Attacks, and How to Prevent/Mitigate a DDoS Attack and much more.
This document discusses Akamai's cloud security solutions for web, DNS, and infrastructure security. It outlines the changing threat landscape, including the growing size of denial-of-service attacks and shift to application layer attacks targeting data theft. It then reviews common on-premise, ISP, and cloud-based security approaches before detailing Akamai's intelligent platform and specific product offerings, including Kona Site Defender, Prolexic Routed, and Fast DNS. The platform is designed to defend against network and application layer DDoS attacks and data theft through a global cloud architecture with multiple layers of defense and integrated threat intelligence.
DOS / DDOS introduction
How Easy it is to get information
Real Life Examples MyDoom , GitHub , Dyn , Windows Server and Windows 10 servers running Internet Information Services (IIS) are vulnerable to denial of service (DOS) attacks
Base of Attacks
Types of DOS / DDOS
Attack Tools , LOIC, XOIC, Stacheldracht
DOS/DDOS Weaknesses
Category of OS/ DDOS
What to defend?
Botnets and Botnets mitigations
Michael Calce, a.k.a. MafiaBoy
Point of entrance / OSI Model ( If time permit)
This is a presentation i made about Denial of Service or a Distributed Denial of Service (DoS / DDoS) and the latest methods used to crash anything online and the future of such attacks which can disrupt the whole internet . Such attacks which are in TB's and can be launched from just single computer. And, there is not much that can be done to prevent them.
Study of flooding based ddos attacks and their effect using deter testbedeSAT Journals
Abstract Today, Internet is the primary medium for communication which is used by number of users across the Network. At the same time, its commercial nature is causing increase vulnerability to enhance cyber crimes and there has been an enormous increase in the number of DDOS (distributed denial of service attack) attacks on the internet over the past decade. Whose impact can be proportionally severe. With little or no advance warning, a DDoS attack can easily exhaust the computing and communication resources of its victim within a short period of time. Network resources such as network bandwidth, web servers and network switches are mostly the victims of DDoS attacks. In this paper different types of DDoS attacks has been studied, a dumb-bell topology have been created and effect of UDP flooding attacks has been analyzed on web service by using attack tools available in DETER testbed. Throughput of web server is analyzed with and without DDoS attacks.
Study of flooding based d do s attacks and their effect using deter testbedeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
This document examines a proposed alternative solution to mitigate distributed denial of service (DDoS) attacks using crowd-sourced bandwidth. It discusses how DDoS attacks work and their impacts on organizations. The proposal aimed to leverage unused bandwidth from multiple clients to filter out malicious traffic and redirect valid traffic. However, the document concludes the concept is not currently feasible due to security, performance, and reliability issues from placing too much trust in clients and relying on slow public DNS propagation. Existing centralized DDoS mitigation solutions from companies are still recommended.
PREVENTING DISTRIBUTED DENIAL OF SERVICE ATTACKS IN CLOUD ENVIRONMENTS IJITCA Journal
Distributed-Denial of Service (DDoS) is a key intimidation to network security. Network is a group of nodes that interrelate with each other for switch over the information. This information is necessary for that node is reserved confidentially. Attacker in the system may capture this private information and distorted. So security is the major issue. There are several security attacks in network. One of the major intimidations to internet examine is DDoS attack. It is a malevolent effort to suspending or suspends services to destination node. DDoS or DoS is an effort to create network resource or the machine is busy to
its intentional user. Numerous thoughts are developed for avoid the DDoS or DoS. DDoS occur in two different behaviors they may happen obviously or it may due to some attackers .Various schemes are developed defense against to this attack. The Main focus of paper is present basis of DDoS attack, DDoS
attack types, and DDoS attack components, intrusion prevention system for DDoS.
Preventing Distributed Denial of Service Attacks in Cloud Environments IJITCA Journal
Distributed-Denial of Service (DDoS) is a key intimidation to network security. Network is a group of
nodes that interrelate with each other for switch over the information. This information is necessary for
that node is reserved confidentially. Attacker in the system may capture this private information and
distorted. So security is the major issue. There are several security attacks in network. One of the major
intimidations to internet examine is DDoS attack. It is a malevolent effort to suspending or suspends
services to destination node. DDoS or DoS is an effort to create network resource or the machine is busy to
its intentional user. Numerous thoughts are developed for avoid the DDoS or DoS. DDoS occur in two
different behaviors they may happen obviously or it may due to some attackers .Various schemes are
developed defense against to this attack. The Main focus of paper is present basis of DDoS attack, DDoS
attack types, and DDoS attack components, intrusion prevention system for DDoS.
This document presents a case study on the impact of denial of service (DoS) attacks on cloud applications. It begins with an introduction to cloud computing and discusses how DoS and distributed DoS (DDoS) attacks are major security threats. The paper then reviews DoS and DDoS attacks, including their objectives to overwhelm resources or exploit vulnerabilities. Next, it discusses defense strategies against such attacks. Finally, the document describes how the case study will measure the stability of a questionnaire using Cronbach's alpha and determine the impact of related variables on the results using stepwise multiple linear regression analysis and Spearman correlation.
This document summarizes research analyzing the impact of distributed denial of service (DDoS) attacks on file transfer protocol (FTP) services. The researchers created a test network topology in the DETER cybersecurity testbed to simulate FTP traffic between clients and a server. They launched various DDoS attack types against the FTP server to measure the impact on network performance metrics like throughput, link utilization, and packet survival ratio. The attacks were found to degrade these metrics and disrupt the FTP services. The study provides insights into how DDoS attacks negatively impact network services like FTP.
IRJET- DDOS Detection System using C4.5 Decision Tree AlgorithmIRJET Journal
This document proposes a machine learning model using the C4.5 decision tree algorithm to detect DDOS attacks. It trains the model on DDOS attack samples from the CICIDS2017 dataset, dividing the samples into training and test data. The Weka data mining tool is used to build the model with attribute filtering and 10-fold cross-validation. The trained model is then validated on the test data to accurately differentiate between benign and DDOS flooding traffic. This combined signature-based and anomaly-based detection approach can effectively detect complex DDOS attacks.
The document provides an overview of common DDoS attack types including SYN floods, UDP floods, ICMP floods, and HTTP floods. It describes how these attacks work to overwhelm servers and networks with traffic to cause denial of service. The document also covers reflection DDoS attacks using protocols like DNS, NTP, and Memcached to amplify the traffic and discusses recommendations for mitigating these attacks.
DNS spoofing/poisoning Attack Report (Word Document)Fatima Qayyum
This document discusses DNS spoofing/poisoning attacks. It begins by explaining how DNS works, translating domain names to IP addresses. It then discusses different types of DNS attacks, focusing on DNS spoofing/poisoning. The document outlines how DNS spoofing occurs by tampering with DNS resolvers or using malicious DNS servers. It explains the goals of attackers, such as launching denial of service attacks or redirecting users to fake websites. The document also provides ways to exploit DNS spoofing through amplification attacks and discusses recommendations for preventing DNS spoofing, such as checking and flushing DNS settings on Windows systems.
Service providers are increasingly playing an important role in DDoS mitigation given the growing scale and sophistication of attacks. They have advantages over enterprise solutions due to their global traffic visibility and ability to filter attacks close to the source. As attacks continue rising in scale and evolving tactics, service providers need intelligent mitigation solutions to protect their infrastructure and ensure customer availability. DDoS mitigation is becoming a key differentiator for service providers to provide more value beyond just connectivity.
Among different online attacks obstructing IT security,
Denial of Service (DoS) and Distributed Denial of Service (DDoS)
are the most devastating attack. It also put the security experts under
enormous pressure recently in finding efficient defiance methods.
DoS attack can be performed variously with diverse codes and tools
and can be launched form different OSI model layers. This paper
describes in details DoS and DDoS attack, and explains how different
types of attacks can be implemented and launched from different OSI
model layers. It provides a better understanding of these increasing
occurrences in order to improve
Security, Availability and Integrity are top concerns around DNS. Infoblox Secure DNS
* provides a secure platform to host DNS services
* provides resilient DNS services even under attack ( like DNS DDoS, exploits )
* prevents data theft by malware/APT that uses DNS
* maintains DNS integrity that can otherwise be compromised by DNS hijacking
This document provides an overview of distributed denial of service (DDoS) attacks including:
- Common types of DDoS attacks like UDP floods, SYN floods, DNS floods and HTTP floods and how they work to overwhelm servers.
- How DDoS attacks are evolving to larger sizes and more complex botnets.
- Methods for mitigating DDoS attacks including black hole routing, rate limiting, web application firewalls, anycast networks and cloud-based DDoS protection services.
- A real example of mitigating a massive 400Gbps DDoS attack and the largest attacks seen to date.
The document discusses distributed denial of service (DDoS) attacks and methods to detect them. It describes DDoS attacks as attempts to make network resources unavailable by flooding them with traffic. The document then reviews literature on detection methods like packet marking and cumulative sum algorithms. It presents a methodology using packet sniffing and analysis to identify attack levels based on packet counts. Specifically, it generates DDoS attacks using LOIC and analyzes TCP SYN flood and UDP flood attacks to detect the length of attacks with over 99% accuracy. In conclusion, it emphasizes the challenge of identifying DDoS attacks and discusses using packet headers and contents to identify malicious traffic based on their behaviors.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
More Related Content
Similar to A SURVEY OF TRENDS IN MASSIVE DDOS ATTACKS AND CLOUD-BASED MITIGATIONS
The document discusses distributed denial of service (DDoS) attacks, including how they work, common tools and methods used, and examples of recent large-scale DDoS attacks. It provides details on how botnets are used to overwhelm websites and infrastructure with malicious traffic. Specific DDoS attack types like UDP floods, SYN floods, and reflection attacks are outlined. Recent large attacks are described, such as those targeting bitcoin exchanges, social trading platforms, and Hong Kong voting sites ahead of a civil referendum.
An Ultimate Guide to DDos Attacks: Detection, Prevention and MitigationTechApprise
In this ultimate guide, you will learn everything about the Distributed Denial of Service (DDoS) Attacks including What are DDoS attacks, Types of DDos Attack, Major Causes, How to Detect DDoS Attacks, and How to Prevent/Mitigate a DDoS Attack and much more.
This document discusses Akamai's cloud security solutions for web, DNS, and infrastructure security. It outlines the changing threat landscape, including the growing size of denial-of-service attacks and shift to application layer attacks targeting data theft. It then reviews common on-premise, ISP, and cloud-based security approaches before detailing Akamai's intelligent platform and specific product offerings, including Kona Site Defender, Prolexic Routed, and Fast DNS. The platform is designed to defend against network and application layer DDoS attacks and data theft through a global cloud architecture with multiple layers of defense and integrated threat intelligence.
DOS / DDOS introduction
How Easy it is to get information
Real Life Examples MyDoom , GitHub , Dyn , Windows Server and Windows 10 servers running Internet Information Services (IIS) are vulnerable to denial of service (DOS) attacks
Base of Attacks
Types of DOS / DDOS
Attack Tools , LOIC, XOIC, Stacheldracht
DOS/DDOS Weaknesses
Category of OS/ DDOS
What to defend?
Botnets and Botnets mitigations
Michael Calce, a.k.a. MafiaBoy
Point of entrance / OSI Model ( If time permit)
This is a presentation i made about Denial of Service or a Distributed Denial of Service (DoS / DDoS) and the latest methods used to crash anything online and the future of such attacks which can disrupt the whole internet . Such attacks which are in TB's and can be launched from just single computer. And, there is not much that can be done to prevent them.
Study of flooding based ddos attacks and their effect using deter testbedeSAT Journals
Abstract Today, Internet is the primary medium for communication which is used by number of users across the Network. At the same time, its commercial nature is causing increase vulnerability to enhance cyber crimes and there has been an enormous increase in the number of DDOS (distributed denial of service attack) attacks on the internet over the past decade. Whose impact can be proportionally severe. With little or no advance warning, a DDoS attack can easily exhaust the computing and communication resources of its victim within a short period of time. Network resources such as network bandwidth, web servers and network switches are mostly the victims of DDoS attacks. In this paper different types of DDoS attacks has been studied, a dumb-bell topology have been created and effect of UDP flooding attacks has been analyzed on web service by using attack tools available in DETER testbed. Throughput of web server is analyzed with and without DDoS attacks.
Study of flooding based d do s attacks and their effect using deter testbedeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
This document examines a proposed alternative solution to mitigate distributed denial of service (DDoS) attacks using crowd-sourced bandwidth. It discusses how DDoS attacks work and their impacts on organizations. The proposal aimed to leverage unused bandwidth from multiple clients to filter out malicious traffic and redirect valid traffic. However, the document concludes the concept is not currently feasible due to security, performance, and reliability issues from placing too much trust in clients and relying on slow public DNS propagation. Existing centralized DDoS mitigation solutions from companies are still recommended.
PREVENTING DISTRIBUTED DENIAL OF SERVICE ATTACKS IN CLOUD ENVIRONMENTS IJITCA Journal
Distributed-Denial of Service (DDoS) is a key intimidation to network security. Network is a group of nodes that interrelate with each other for switch over the information. This information is necessary for that node is reserved confidentially. Attacker in the system may capture this private information and distorted. So security is the major issue. There are several security attacks in network. One of the major intimidations to internet examine is DDoS attack. It is a malevolent effort to suspending or suspends services to destination node. DDoS or DoS is an effort to create network resource or the machine is busy to
its intentional user. Numerous thoughts are developed for avoid the DDoS or DoS. DDoS occur in two different behaviors they may happen obviously or it may due to some attackers .Various schemes are developed defense against to this attack. The Main focus of paper is present basis of DDoS attack, DDoS
attack types, and DDoS attack components, intrusion prevention system for DDoS.
Preventing Distributed Denial of Service Attacks in Cloud Environments IJITCA Journal
Distributed-Denial of Service (DDoS) is a key intimidation to network security. Network is a group of
nodes that interrelate with each other for switch over the information. This information is necessary for
that node is reserved confidentially. Attacker in the system may capture this private information and
distorted. So security is the major issue. There are several security attacks in network. One of the major
intimidations to internet examine is DDoS attack. It is a malevolent effort to suspending or suspends
services to destination node. DDoS or DoS is an effort to create network resource or the machine is busy to
its intentional user. Numerous thoughts are developed for avoid the DDoS or DoS. DDoS occur in two
different behaviors they may happen obviously or it may due to some attackers .Various schemes are
developed defense against to this attack. The Main focus of paper is present basis of DDoS attack, DDoS
attack types, and DDoS attack components, intrusion prevention system for DDoS.
This document presents a case study on the impact of denial of service (DoS) attacks on cloud applications. It begins with an introduction to cloud computing and discusses how DoS and distributed DoS (DDoS) attacks are major security threats. The paper then reviews DoS and DDoS attacks, including their objectives to overwhelm resources or exploit vulnerabilities. Next, it discusses defense strategies against such attacks. Finally, the document describes how the case study will measure the stability of a questionnaire using Cronbach's alpha and determine the impact of related variables on the results using stepwise multiple linear regression analysis and Spearman correlation.
This document summarizes research analyzing the impact of distributed denial of service (DDoS) attacks on file transfer protocol (FTP) services. The researchers created a test network topology in the DETER cybersecurity testbed to simulate FTP traffic between clients and a server. They launched various DDoS attack types against the FTP server to measure the impact on network performance metrics like throughput, link utilization, and packet survival ratio. The attacks were found to degrade these metrics and disrupt the FTP services. The study provides insights into how DDoS attacks negatively impact network services like FTP.
IRJET- DDOS Detection System using C4.5 Decision Tree AlgorithmIRJET Journal
This document proposes a machine learning model using the C4.5 decision tree algorithm to detect DDOS attacks. It trains the model on DDOS attack samples from the CICIDS2017 dataset, dividing the samples into training and test data. The Weka data mining tool is used to build the model with attribute filtering and 10-fold cross-validation. The trained model is then validated on the test data to accurately differentiate between benign and DDOS flooding traffic. This combined signature-based and anomaly-based detection approach can effectively detect complex DDOS attacks.
The document provides an overview of common DDoS attack types including SYN floods, UDP floods, ICMP floods, and HTTP floods. It describes how these attacks work to overwhelm servers and networks with traffic to cause denial of service. The document also covers reflection DDoS attacks using protocols like DNS, NTP, and Memcached to amplify the traffic and discusses recommendations for mitigating these attacks.
DNS spoofing/poisoning Attack Report (Word Document)Fatima Qayyum
This document discusses DNS spoofing/poisoning attacks. It begins by explaining how DNS works, translating domain names to IP addresses. It then discusses different types of DNS attacks, focusing on DNS spoofing/poisoning. The document outlines how DNS spoofing occurs by tampering with DNS resolvers or using malicious DNS servers. It explains the goals of attackers, such as launching denial of service attacks or redirecting users to fake websites. The document also provides ways to exploit DNS spoofing through amplification attacks and discusses recommendations for preventing DNS spoofing, such as checking and flushing DNS settings on Windows systems.
Service providers are increasingly playing an important role in DDoS mitigation given the growing scale and sophistication of attacks. They have advantages over enterprise solutions due to their global traffic visibility and ability to filter attacks close to the source. As attacks continue rising in scale and evolving tactics, service providers need intelligent mitigation solutions to protect their infrastructure and ensure customer availability. DDoS mitigation is becoming a key differentiator for service providers to provide more value beyond just connectivity.
Among different online attacks obstructing IT security,
Denial of Service (DoS) and Distributed Denial of Service (DDoS)
are the most devastating attack. It also put the security experts under
enormous pressure recently in finding efficient defiance methods.
DoS attack can be performed variously with diverse codes and tools
and can be launched form different OSI model layers. This paper
describes in details DoS and DDoS attack, and explains how different
types of attacks can be implemented and launched from different OSI
model layers. It provides a better understanding of these increasing
occurrences in order to improve
Security, Availability and Integrity are top concerns around DNS. Infoblox Secure DNS
* provides a secure platform to host DNS services
* provides resilient DNS services even under attack ( like DNS DDoS, exploits )
* prevents data theft by malware/APT that uses DNS
* maintains DNS integrity that can otherwise be compromised by DNS hijacking
This document provides an overview of distributed denial of service (DDoS) attacks including:
- Common types of DDoS attacks like UDP floods, SYN floods, DNS floods and HTTP floods and how they work to overwhelm servers.
- How DDoS attacks are evolving to larger sizes and more complex botnets.
- Methods for mitigating DDoS attacks including black hole routing, rate limiting, web application firewalls, anycast networks and cloud-based DDoS protection services.
- A real example of mitigating a massive 400Gbps DDoS attack and the largest attacks seen to date.
The document discusses distributed denial of service (DDoS) attacks and methods to detect them. It describes DDoS attacks as attempts to make network resources unavailable by flooding them with traffic. The document then reviews literature on detection methods like packet marking and cumulative sum algorithms. It presents a methodology using packet sniffing and analysis to identify attack levels based on packet counts. Specifically, it generates DDoS attacks using LOIC and analyzes TCP SYN flood and UDP flood attacks to detect the length of attacks with over 99% accuracy. In conclusion, it emphasizes the challenge of identifying DDoS attacks and discusses using packet headers and contents to identify malicious traffic based on their behaviors.
Similar to A SURVEY OF TRENDS IN MASSIVE DDOS ATTACKS AND CLOUD-BASED MITIGATIONS (20)
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Low power architecture of logic gates using adiabatic techniquesnooriasukmaningtyas
The growing significance of portable systems to limit power consumption in ultra-large-scale-integration chips of very high density, has recently led to rapid and inventive progresses in low-power design. The most effective technique is adiabatic logic circuit design in energy-efficient hardware. This paper presents two adiabatic approaches for the design of low power circuits, modified positive feedback adiabatic logic (modified PFAL) and the other is direct current diode based positive feedback adiabatic logic (DC-DB PFAL). Logic gates are the preliminary components in any digital circuit design. By improving the performance of basic gates, one can improvise the whole system performance. In this paper proposed circuit design of the low power architecture of OR/NOR, AND/NAND, and XOR/XNOR gates are presented using the said approaches and their results are analyzed for powerdissipation, delay, power-delay-product and rise time and compared with the other adiabatic techniques along with the conventional complementary metal oxide semiconductor (CMOS) designs reported in the literature. It has been found that the designs with DC-DB PFAL technique outperform with the percentage improvement of 65% for NOR gate and 7% for NAND gate and 34% for XNOR gate over the modified PFAL techniques at 10 MHz respectively.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
Technical Drawings introduction to drawing of prisms
A SURVEY OF TRENDS IN MASSIVE DDOS ATTACKS AND CLOUD-BASED MITIGATIONS
1. International Journal of Network Security & Its Applications (IJNSA), Vol.6, No.3, May 2014
DOI : 10.5121/ijnsa.2014.6305 57
A SURVEY OF TRENDS IN MASSIVE DDOS ATTACKS
AND CLOUD-BASED MITIGATIONS
FuiFui Wong and Cheng Xiang Tan
Department of Computer Science and Technology, TongJi University, Shanghai, 201804,
China
ABSTRACT
Distributed Denial of Service (DDoS) attacks today have been amplified into gigabits volume with
broadband Internet access; at the same time, the use of more powerful botnets and common DDoS
mitigation and protection solutions implemented in small and large organizations’ networks and servers
are no longer effective. Our survey provides an in-depth study on the current largest DNS reflection attack
with more than 300 Gbps on Spamhaus.org. We have reviewed and analysed the current most popular
DDoS attack types that are launched by the hacktivists. Lastly, effective cloud-based DDoS mitigation and
protection techniques proposed by both academic researchers and large commercial cloud-based DDoS
service providers are discussed.
KEYWORDS
DoS, DDoS, DNS reflection or amplification attack, SYN flood, UDP flood, ICMP flood, HTTP flood attack
1. INTRODUCTION
In March, 2013, Spamhaus.org was suffering the largest distributed denial of service (DDoS)
attacks on record, with an estimated size of more than 300 Gbps [1]. CloudFlare with cloud-based
DDoS protection solutions was engaged to mitigate this attack. According to Prolexic’s Q1 2013
Global DDoS Attack Report, more than 10% of the massive DDoS attacks today have exceeded
60 Gbps, and more than 75% of the attacks are directed to infrastructure (Layer 3 and 4), against
bandwidth capacity and routing infrastructure; the remaining attacks are on the application layer
[2].
In a DDoS attack, the attackers attempt to temporarily interrupt or suspend the services of a
website so that it is unavailable to the users. Akamai’s Fourth Quarter, 2012 State of the Internet
Report has stated that a total of 768 DDoS attacks were reported in 2012. Over a third (269 or
35%) of the attacks targeted companies in the Commerce sector, 164 attacks (22%) targeted
Media and Entertainment companies, 155 attacks (20%) targeted Enterprise companies that
include financial services, 110 attacks (14%) targeted High Tech companies, and 70 attacks (9%)
targeted Public Sector agencies [3]. These attacks have cost targeted companies or organizations
losses in revenues, customer satisfaction and brand equity.
This survey aims to provide a complete update on the current most popular DDoS attack types
used in massive attacks and to discuss the various effective cloud-based DDOS mitigation and
protection techniques. In Section 2 of the survey, we first look into the current largest DDoS
attack on Spamhaus in detail. We then discuss the current most popular infrastructure (layer 3 and
4) and application layer attack types in Section 3. Various effective cloud-based DDOS mitigation
2. International Journal of Network Security & Its Applications (IJNSA), Vol.6, No.3, May 2014
58
and protection techniques are discussed in Section 4, and lastly, we present our conclusions in
Section 5.
2. HISTORIC DDOS ATTACK ON SPAMHAUS
On 18 March, 2013, spamhaus.org, a website of Spamhaus that provides anti-spam filtering
services online, was attacked by a massive DDoS that was more than 100 Gbps. This attack was
enormous and saturated their Internet connection; access to their website was not possible. The
attacks were classified as Layer 3 attacks and were difficult to resolve with a software solution
because the router was saturated with excess network traffic compared with the traffic that it can
handle. The identity of the attacker was unknown during that time.
These large Layer 3 attacks are from many sources and are distributed, whereby sources send
traffic to flood the targeted Internet location. A group of individuals working together, a botnet of
compromised PCs, a botnet of compromised servers, misconfigured DNS resolvers, or even home
Internet routers with weak passwords could be the sources of attack traffic.
DDoS prevention techniques such as IP filtering will not be effective anymore because a Layer 3
attack is launched by sending randomised packets that contain spoof information, including the
source IP, and the received responses will be ignored. CloudFlare, a company that offers cloud-
based DDoS protection solutions, was engaged by Spamhaus to mitigate the attack, and the site
was up within hours [1].
2.1 Generation of the 75 Gbps DDoS Attack to Spamhaus
Since 2012, DNS reflection attack has become the main source of the largest Layer 3 DDoS
attacks. The largest attack traffic for Spamhaus was from DNS reflection.
The attacker of Spamhaus began by requesting a DNS zone file for ripe.net from the open DNS
resolvers. The CloudFlare IPs assigned to Spamhaus were spoofed by the attacker in their DNS
requests. The DNS zone file responded by opening resolvers that generated approximately 75
Gbps of attack traffic, which resulted from an amplified 36-byte request to a 3,000-byte response.
30,000 unique DNS resolvers were involved in the Spamhaus attack. Each open DNS resolver
was sending a 2.5 Mbps DNS zone file, which was allowed by most DNS resolvers. The attacker
then used only DNS amplification and controlling a botnet or cluster of servers to generate a 750
Mbps DNS zone file.
2.2 Mitigation of the 75 Gbps DDoS Attack to Spamhaus
Anycast was used by CloudFlare to mitigate the 75 Gbps DDoS attack on Spamhaus. Anycast
scatters an attack on Spamhaus to the 23 worldwide data centers of CloudFlare. Every data centre
used the same IP address for Spamhaus, which had the result that the traffic could not be targeted
to any one location. Instead of a many-to-one attack, the attack becomes many-to-many and
unable to cause a bottleneck at any single point in the network. After the attack was scattered, the
Layer 3 attack was stopped at each of the CloudFlare data centers before reaching Spamhaus
servers.
3. International Journal of Network Security & Its Applications (IJNSA), Vol.6, No.3, May 2014
59
3. CURRENT UPTREND OF MASSIVE DDOS ATTACK TYPES
The Open Systems Interconnection (OSI) model divides a communication system into seven
logical layers. Each layer has its own unique security challenges and is vulnerable for the Denial
of Service (DOS) attack or Distributed Denial of Service (DDoS) attack. The uptrend of
Distributed Denial of services attacks for the last two years primarily fall into two categories of
attack: Infrastructure (Layer 3 & 4) attacks and Application (Layer 7) attacks. Attacks in the first
category, infrastructure attacks, attempt to overwhelm the bandwidth capacity and routing
infrastructure by sending very large number of spurious requests. The second category,
application attacks, exploits the limitation of a specific application to cause performance
degradation or ultimately crashing the remote servers.
3.1 Infrastructure (Layer 3 and 4) Attacks
This section describes the current most popular DDoS attack types on the network layer (Layer 3)
and transport layer (Layer 4) in the OSI model, which are the following:
─ DNS Reflection Attacks
─ TCP SYN floods
─ UDP floods
─ ICMP floods
Based on the statistical record published on the security reports by the well-established leading
industries [2-4], these attack types are the primary focus of malicious actors and will stay at the
top on the global threatscape.
3.1.1. Domain Name Server (DNS) Reflection or Amplification Attacks.
A DNS Reflection or Amplification attack is a type of distributed denial of service (DDoS) attack
in which an attacker sends a DNS name lookup request to an open DNS resolver with the source
address spoofed to be the victim’s address. When the DNS server sends the DNS record response,
it is sent to the victim (the source address that was used in the spoofed request). Because the size
of the response is typically considerably to be larger than the request, the attacker can amplify the
volume of traffic directed at the victim. By leveraging a botnet to perform additional spoofed
DNS queries, an attacker can produce an overwhelming amount of traffic with very little effort, as
shown in Figure 1. Because the responses are legitimate data coming from valid name servers, it
is especially difficult to block these types of attacks [5].
Fig. 1 DNS Reflection Attack
A DNS Reflection attack is made possible by the following [6]:
Open recursion. Open DNS resolvers are referred to as servers on the Internet and have
recursion enabled, and they provide recursive DNS responses to anyone. According to Open
Resolver Project, there are approximately 27 million open DNS resolvers currently on the
4. International Journal of Network Security & Its Applications (IJNSA), Vol.6, No.3, May 2014
60
Internet. Open DNS resolvers are the source of amplification, returning a much larger DNS
response after receiving a small DNS query.
Source address spoofing. A DNS amplification attack is similar to a “Smurf” attack, in which the
source address for the DNS query is spoofed with a return address other than the sender’s. Then,
an open resolver returns a DNS response that is incorrectly sent to the spoofed address [7].
Botnets. In a DNS amplification attack, the attacker has compromised groups of online computers
that are known as Botnets for sending DNS queries to open resolvers.
Malware. DNS amplification attacks are triggered by botnet computers infected with Malware.
EDNS0. A 64-byte query will result in an 8x amplified 512 byte UDP reply if it is without
Extension Mechanisms for DNS (EDNS0) [8], allowing DNS requestors to advertise their UDP
packets size and facilitate the transfer of packets larger than 512 bytes.
DNSSEC. DNSSEC (short for DNS Security Extensions) [9] allows DNS servers to validate DNS
responses and prevents cache-poisoning attacks with cryptographic signatures added, resulting
in a larger DNS message size that requires EDNS0 support. DNSSEC has been criticised for
contributing to DNS amplification attacks because a server that supports DNSSEC will also
support large UDP packets in a DNS response.
3.1.2. TCP SYN Floods.
SYN flooding attack works on the design of a 3-way handshake to begin a TCP connection. In
this handshake, as shown in Figure 2, the client system begins by sending a SYN message to the
server. The server then acknowledges the SYN message by sending a SYN-ACK message to the
client. The client then finishes establishing the connection by responding with an ACK message.
The connection between the client and the server is then open, and the service-specific data can
be exchanged between the client and the server. The potential for abuse arises at the point where
the server system has sent an acknowledgment (SYN-ACK) back to the client but has not yet
received the ACK message [10].
Fig. 2 TCP 3-way handshake
The Transmission Control Block (TCB), a transport protocol data structure that holds all of the
information on a connection, is allocated, and the connection is only half open after the SYN
packet has been received by the server before the ACK message is received from the client. This
situation leads to the server's kernel memory being exhausted by incoming SYNs, which create
too many TCB allocations. However, Operating systems will usually use a “backlog” parameter
with a listening socket to avoid this memory exhaustion, but depleting the backlog is the goal of
the TCP SYN flooding attack, which attempts to send enough SYN segments to fill the entire
5. International Journal of Network Security & Its Applications (IJNSA), Vol.6, No.3, May 2014
61
backlog and, thus, causes the service to be denied to the new connection requests. Figure 3 below
presents a simplification of the sequence of events that are involved in a TCP SYN flooding
attack.
Fig. 3 TCP SYN flooding attack
Currently, there are 3 variants of TCP SYN flooding attacks [11] found on the Internet:
i) Direct Attack. A direct attack is where the attackers send many SYN segments without
spoofing their IP source address, and they prevent their operating system from responding to the
SYN-ACKs. This scenario can be accomplished through firewall rules that either filter outgoing
packets to the listener (allowing only SYNs out) or filter incoming packets so that any SYN-
ACKs are discarded before reaching the local TCP processing code, as shown in Figure 4.
Fig. 4 Direct Attack
ii) Spoofing-Based Attacks. SYN flooding attacks [12] use IP address spoofing, where the client
systems at the spoofed source addresses are not responding to the SYN-ACKs sent to them, either
because no client system exists at the address presently or because of the assumption that some
percentage of the spoofed addresses will not respond, as shown in Figure 5.
6. International Journal of Network Security & Its Applications (IJNSA), Vol.6, No.3, May 2014
62
Fig. 5 Spoofing-based attacks
iii) Distributed Attacks. A distributed SYN flooding attack occurs when the attacker takes
advantage of many drone machines or botnets throughout the Internet, and each changeable drone
uses a spoofing attack and multiple spoofed addresses, which make the attack much more difficult
to be blocked or stopped, as shown in Figure 6.
Fig. 6 Distributed attacks
3.1.3. UDP Floods.
A UDP flood is a type of bandwidth attack that uses the User Datagram Protocol (UDP). The
UDP is a stateless transmission protocol that does not require the client and server to have an
established session, and it has an emphasis on minimal latency rather than reliability in
transmitting information. A UDP flood attack can be initiated by generating massive amounts of
UDP packets to a random port on the victim system. The victim system will determine which
application is waiting on the destination port in response to an incoming UDP packet. When the
victim system that implements these services responds, it will respond to each UDP packet with
an IMCP unreachable message to the forged source IP address if no application is waiting on the
port. In this case, the malicious UDP sender forges the IP source address to be that of a victim,
and thus, the victim’s system is subject to being overloaded by the multiple UDP traffic
responders. This type of attack most commonly exploits both the “chargen” and “echo” services
weaknesses, as illustrated in figure 7, making them useful to the DoS attack (e.g., a UDP packet is
composed of a source port of echo for the target host B and a destination port of chargen for the
target host A) [13]. The chargen service will continue generating some random characters and
send them back to the apparent source, whereas the echo service keeps continuing to respond to
the packet by echoing the random characters back to the chargen. The attacker can pipe output
from the chargen to echo and cause an infinite ending stream of network activity. This scenario
creates an infinite loop between two UDP services, where host B will echo a packet to host A.
Host A then responds to host B’s echo port until the exhaustion of some shared resource (e.g.,
buffers, link, capacity) [14].
Because UDP is an unreliable protocol that does not regulate its sending traffic rate, this scenario
can easily allow a malicious UDP sender to forge the IP source address to be that of a victim.
7. International Journal of Network Security & Its Applications (IJNSA), Vol.6, No.3, May 2014
63
Most UDP floods are used frequently for the larger bandwidth DDoS attacks that are greater than
1 Gbps because it is easy to generate UPD packets from many different scripting and compiled
languages [15].
Fig. 7 UDP flooding attack
3.1.4. ICMP Floods.
The ICMP flood, occasionally referred to as a "Smurf" attack or "Ping" flood, is a ping-based
DOS attack that sends large numbers of ICMP packets to a server and attempts to crash the
TCP/IP stack on the server and cause it to stop responding to the incoming TCP/IP requests.
Then, hping or custom perl scripts installed on the compromised machines are used to launch
ICMP floods. Basic SYN floods are occasionally launched together with ICMP floods [2].
A SMURF attack occurs when an attacker sends ICMP requests with a victim’s spoofed IP to the
network's broadcast address of a router that is configured to relay ICMP to all of the devices
behind the router. The attack is amplified when all of those devices respond back to the ping,
where ICMP does not include a handshake and the source IP will not be verified. Figure 8 below
presented a SMURF attack [16]. Please refer to [17] and [18] for a more detailed description of a
Smurf attack.
Fig. 8 ICMP flooding attack
8. International Journal of Network Security & Its Applications (IJNSA), Vol.6, No.3, May 2014
64
3.2 Application (Layer 7) Attacks
The application layer DDoS attacks continue to grow in both complexity and prevalence. The
research firm Gartner forecasts that 25% of the DDoS attacks in the year 2013 will be application-
based, in the report titled, “Arming Financial and E-commerce Services Against Top 2013
Cyberthreats” [19]. DDoS attacks in the application layer attempt to target a specific service with
a web flood; for example, HTTP flood attacks send high rates of legitimate application-layer
requests to a server in an attempt to overwhelm the server resources. These attacks generally
consume less bandwidth and are far more difficult to identify because the attacker attacks the
victim server through a flood of legitimate requests [20].
3.2.1. Common Application-Layer DDoS Attack Types.
Application-layer attacks can be subdivided into four categories [21] [22]:
i) Request-Flooding Attacks occur when heavy legitimate application-layer requests (e.g., HTTP
GETs, DNS queries and SIP INVITEs) are sent to a server to overwhelm its session resources.
ii) Asymmetric Attacks occur when normal requests that consume large amounts of server
resources, such as CPU, memory or disk space, are sent to the web server with the objective of
severely degrading its service or bringing the server completely down.
iii) Repeated One-Shot Attacks occur when a high workload request across many TCP sessions is
sent to the server, with the goal of degrading or bringing down the service of the server. These
attacks are similar to executing both request-flooding and asymmetric application-layer attacks.
iv) Application-Exploit Attacks target vulnerabilities in applications by causing a fault in a
server’s operating system or applications and allow the attacker to gain control of the application,
system or network. Scripting vulnerabilities, buffer overflows, cookie poisoning, hidden field
manipulation, cross-site scripting and Structured Query Language (SQL) injection are the
examples of these attacks [23].
3.2.2. HTTP Flood Attacks.
According to Prolexic’s Q1 2013 Global DDoS Attack Report, 23.46 per cent of the Total DDOS
attacks come in application (layer 7) attacks, and 19.33 per cent of the total DDOS attacks come
in the form of HTTP GET floods, which represent the majority of application attacks. Http Post
floods, which enable attackers to POST large amounts of data to applications, are the second most
popular of the application attacks, which make up 1.43 per cent of the total DDoS attacks [2].
There are 3 types of HTTP floods that can be launched, as follows [21]:
i) HTTP Malformed Attacks occur when invalid HTTP packets are sent to web servers to exhaust
the server resources. An example of this type of attack, which uses malformed HTTP GET
requests, is Zafi.B worm.
ii) HTTP Request Attacks occur when different types of legitimate HTTP requests (i.e., HTTP
GETS, and POSTS) are sent to web servers in an attempt to flood them by consuming the server
resources [24].
iii) HTTP Idle Attacks occur when HTTP connections are opened and left idle without actually
sending a complete HTTP request by an attack. An example of this attack is “slowloris” [25],
which involves indefinitely dribbling out a small number of bytes per packet to keep the
connection from timing out but which never manages to complete the request .
9. International Journal of Network Security & Its Applications (IJNSA), Vol.6, No.3, May 2014
65
4. CURRENT DDOS MITIGATION AND PROTECTION TECHNIQUES USED
WITH THE CLOUD
Currently, common DDoS mitigation and protection techniques that are implemented on the small
and large organizations’ networks and servers find it difficult or no longer possible to mitigate the
overwhelming gigabit attacks. Cloud computing with geographically distributed high Internet
bandwidth and high processing power is required for these DDoS mitigation and protection
techniques to be effective.
Various effective massive DDoS mitigation and protection techniques, which are researched by
academic researchers and used by large commercial cloud-based DDoS service providers such as
Prolexic, CloudFlare, Cisco, Akamai and Arbor for mitigating the attack types mentioned in the
above section, will be discussed, as follows:
4.1 DNS Reflection or Amplification Attacks
4.1.1. Ingress filtering.
Ingress filtering checks the validity of the IP addresses that belong to your network for all of the
outgoing packets and is fully written down in a Best Common Practices document, BCP-38. The
DNS server reflects traffic that relies on spoofed IP addresses, which are dropped by using this
filtering, and it is easy to implement in routers because all of the major router vendors have
methods that are built-in, to implement BCP-38 [26].
4.1.2. Limiting DNS recursion.
Limiting DNS recursion [5] can be performed by:
i) Configuring your server to allow recursion for a list of authorised DNS servers
ii) Configuring firewall to block the DNS queries that are not coming from your designated
internal recursive DNS servers.
iii) Configuring your server to use the recursive DNS servers of your ISP and then only allow
the DNS queries that are related to these servers.
iv) Splitting your authoritative and recursive DNS servers so that the recursive DNS is reachable
only from within the LAN, as in Figure 9 below.
Fig. 9 Splitting Authoritative and Recursive DNS Servers
10. International Journal of Network Security & Its Applications (IJNSA), Vol.6, No.3, May 2014
66
v) Using a hidden master so that only your slave authoritative DNS servers are publicly
available on the Internet, as in Figure 10 below.
Fig. 10 Authoritative DNS is hidden master
4.1.3. DNS Response Rate Limiting.
DNS-RRL.DNS Response Rate Limiting is an experimental mechanism for limiting the number
of responses per second returned by a DNS server. The effectiveness of a DNS amplification
attack can then be reduced by dropping responses that exceed the configured rate limit. There are
3 ways that response rate limiting can be applied to a DNS server: by a source IP address, by a
destination IP address and by the DNS query type [27].
4.1.4. Anycast.
Anycast allows multiple, identical, globally deployed DNS servers to advertise the same IP
address. Using Anycast, each DNS server IP corresponds to hundreds of systems world-wide that
are announced from different geographical locations. DNS servers reflect traffic that has spoofed
IP addresses is then dropped at the closest DNS server to the querying client.
Most of the Anycast implementations are in the network layer, but research performed by the
authors, Ioannis Avramopoulos and Martin Suchara, has proved that Anycast can be implemented
in an applications layer, and the result shown is that the security performance is approximately the
same as the network-layer implementation [28].
4.2 TCP SYN Flooding
SYN flooding mitigations have evolved into 2 classes, which are End-Host and Network based.
End-Host mitigations involve hardening the end-host TCP implementation, which includes
altering the algorithms and data structures that are used for connection lookup and establishment.
Network-Based mitigations involve hardening the network, which either lessens the likelihood of
the attack preconditions or inserts middleboxes that can isolate servers on the networks behind
them from illegitimate SYNs [11].
11. International Journal of Network Security & Its Applications (IJNSA), Vol.6, No.3, May 2014
67
End-Host mitigation techniques include the following:
i) Increasing TCP Backlog
ii) Reducing the SYN-RECEIVED Timer
iii) SYN caches and SYN cookies that operate by reducing the amount of state (SYN caches) /
generating zero state (SYN cookies) that is allocated initially for a TCB generated by a
received SYN, and putting off instantiating the full state.
iv) A hybrid approach that combines two or more of the above techniques.
Network-Based mitigation techniques include:
i) Ingress filtering that is very effective at preventing SYN flooding attacks, which rely on
spoofed IP packets.
ii) Use firewalls and proxies to buffer end hosts from SYN flooding attacks through either
spoofing SYN-ACKs to the initiators or spoofing ACKs to the listener.
iii) Use of a less expensive and easy-to-deploy active monitor device to observe and inject
traffic to the listeners of the entire network without requiring every listener's operating
system to implement an end-host mitigation.
Both End-Host and Network-Based mitigations are frequently employed and usually do not
interfere when used in combination. Mitigations at End-Host are to take precedence over
Network-Based because SYN flooding is targeted at end hosts rather than attempting to exhaust
the network capacity.
The SYN caches technique is currently the most effective and most-often used end-host
mitigation; it can withstand heavy attacks without the negative effects of SYN cookies, and
heuristics for the threshold settings are not needed when they are employed in many hybrid
approaches.
For Network-based mitigations, both SYN-ACK spoofing and ACK-spoofing of firewall/proxies
produced the same effectiveness; active monitors are preferred to firewall/proxies for their low
cost and easy administration, and both Ingress and egress filtering are commonly used as a good
Internet security practice.
4.3 UDP Flood
The UDP flood attack has become prominent due to the recent high-profile attacks launched by a
group of Internet activists called Anonymous [29, 30]. A DoS attack tool called LOIC (Low Orbit
Ion Cannon), which performs flooding attacks using UDP packets, is widely available on the web.
To mitigate the impact of UDP flooding attacks, several approaches have been proposed to
suppress these types of attacks, such as prohibiting the UDP service, rate limits on UDP traffic,
protection of proxy servers, and configuring the router to stop IP directed-broadcast transmission.
For example, Komatsu et al. [31] have conducted a simulation that uses CHOKe with ACC
(complex bandwidth control) as a congestion control method to prove the effectiveness of rate-
limiting methods in mitigating UDP flood attacks.
4.4 ICMP Flood
ICMP flood attacks are losing popularity in the last few quarters, as stated in the Prolexic’s Q1
2013 report. They are succeeded by more effective and stealthy attack methods that are available
in the Internet. Currently, these attacks, which rely on the router serving a large multi-access
broadcast network to frame an IP broadcast address, are easy to stop where the network operators
deny the forwarding ICMP requests to a network's broadcast address by configuring their routers.
12. International Journal of Network Security & Its Applications (IJNSA), Vol.6, No.3, May 2014
68
There are some operating systems that allow configurations for preventing your server from being
used as an intermediary and that respond to the ICMP packets (which do not travel through a
router on the local network) forwarded to an IP broadcast [17].
4.5 HTTP Flood Attacks
Vulnerability in the protocol is the main reason for flood attacks. A mitigation method for the
flood attacks must consider the perspective of the system/protocol design to ensure an effective
and successful implementation.
The HTTP protocol that serves at the application layer is used to launch HTTP flood attacks and
can be detected and analysed by application layer security devices such as IPS (Intrusion
Detection System) or WAF (Web Application Firewall). For other security devices at different
layers of the OSI model, TCP connection counts made for the HTTP responses are the only
detection method for them to prevent and block the HTTP Flood attacks.
The HTTP flood attacks can be mitigated at 5 main levels, as shown in Figure 11, which are the
Cloud Services Level, Network Level, Web Server Level, Web Service Level, and Web
Application Level [32]:
The Cloud Services Level and Network Level are the most important levels for detecting and
blocking the HTTP flood attacks before reaching the web server.
Fig. 11 Mitigation levels of HTTP flooding attack
13. International Journal of Network Security & Its Applications (IJNSA), Vol.6, No.3, May 2014
69
4.5.1. IOSEC HTTP Anti Flood/DoS Security Gateway Module.
The author Gokhan Muharremoglu [32] has proposed a web application level approach against
the HTTP Flood Attacks, IOSEC HTTP Anti Flood/DoS Security Gateway Module. This
approach can be summarised into the following 3 steps:
i) Detect IP addresses of the abnormally excessive requests according to a previously defined
rule,
ii) To reduce the attack surface, return the requests with a response that uses a small amount of
resources (e.g., a blank page),
iii) Block detected IP addresses using other components at the other mitigation levels (e.g.,
WAF, web server/service).
Interested readers can refer to [32] for a more detailed description of the IOSEC HTTP Anti -
Flood/DoS Security Gateway Module.
4.5.2. Detection of HTTP-GET Attack with Clustering and Information Theoretic
Measurements.
The authors Chwalinski et al. [33] have recently proposed an off-line clustering technique that
uses entropy-based clustering and the application of information-theoretical measurements to
distinguish more than 80% of the legitimate and attacking sequences, regardless of the strategies
chosen by the HTTP Flooding attackers.
The authors focus their research on the recent behaviour of actual web users by analysing the
actual sequences of the web requests that the attackers do not know and could not reproduce. Two
types of attacking hosts, frequently-changing and rarely-changing, are targeted by the proposed
technique.
4.5.3. Detection of HTTP GET flooding attack in three different attack scenarios.
The authors Das et al. [34] have proposed a detection method for HTTP GET flooding attacks in
three different scenarios, which are named in the following way:
i) Random Flooding App-DoS, which compares HTTP request arrivals with input thresholds.
ii) Shrew Flooding App-DoS, which detects the attacks using the generation of Legitimate
Access Pattern (LAP) and computation of Pattern Disagreement (PD)
iii) Flash Crowds App-DoS, which uses a detection mechanism called DSB to perform offline
analysis of attack datasets.
4.5.4. Arbor’s Peakflow SP and Peakflow SP TMS to Stop Application-Layer DDoS
Attacks.
Peakflow SP and Peakflow SP TMS are the commercial solutions that are provided by Arbor to
stop DDoS attacks on the application layer. Peakflow SP is a very popular and effective DDoS
mitigation solution that is capable of detecting bandwidth-consuming, connection-layer
exhaustion and application attacks. The solution is used by the majority of the world’s Internet
service providers as one of their main DDoS detection and surgical mitigations.
Arbor relies mainly on a Peakflow SP Threat Management System (TMS) in their Peakflow SP
solution to detect and mitigate HTTP flood attacks. This approach is a robust application-
intelligent system for multi-service converged networks that speeds remediation by coupling
high-level threat identification with packet-level analysis. It also provides visibility into critical
14. International Journal of Network Security & Its Applications (IJNSA), Vol.6, No.3, May 2014
70
applications that are running on the network, and it can monitor key application performance
metrics [21].
5. CONCLUSIONS
This study has presented a comprehensive survey and analysis of the current most popular DDoS
attack types and mitigations.
In this survey, we have presented a complete analysis on the generation and mitigation of the
current largest DNS reflection attack with more than 300 Gbps on Spamhaus.org. This analysis is
followed by a discussion on the current most popular DDoS attack types (DNS Reflection
Attacks, SYN floods, UDP floods, ICMP floods and HTTP Flood Attacks) in the Infrastructure
and Application layers.
For combating the current most popular DDoS attack types presented in this survey, we have
extensively discussed various effective cloud-based DDoS mitigation and protection techniques
that have been proposed by both the academic researchers and large commercial cloud-based
DDoS service providers.
REFERENCES
[1] M. Prince, "The Ddos That Knocked Spamhaus Offline (And How We Mitigated It)," Vol. 2013, Ed:
Cloudflare, March 20, 2013 P. Web Log Post.
[2] Prolexic Technologies, "Prolexic Quarterly Global Ddos Attack Report Q1 2013," Florida2013.
[3] Akamai Technologies. (2013). The State Of The Internet 4th Quarter, 2012 Report. 5. Available:
Http://Www.Akamai.Com/Dl/Akamai/Akamai_Soti_Q412_Exec_Summary.Pdf
[4] D. Anstee, D. Bussiere, And G. Sockrider. (2013). Worldwide Infrastructure Security Report 2012
Viii. Available: Http://Pages.Arbornetworks.Com/Rs/Arbor/Images/Wisr2012_En.Pdf
[5] Cert. (2013, April 15). Dns Amplification Attacks And Open Dns Resolvers. Available:
Https://Www.Cert.Be/Pro/Docs/Dns-Amplification-Attacks-And-Open-Dns-Resolvers
[6] G. Lindsay. (2012, March 10). Dnssec And Dns Amplification Attacks. Available:
Http://Technet.Microsoft.Com/En-Us/Security/Hh972393.Aspx
[7] R. Beverly And S. Bauer, "The Spoofer Project: Inferring The Extent Of Source Address Filtering On
The Internet," Presented At The Proceedings Of The Steps To Reducing Unwanted Traffic On The
Internet On Steps To Reducing Unwanted Traffic On The Internet Workshop, Cambridge, Ma, 2005.
[8] P. Vixie. (August 1999, Rfc 2671 , Extension Mechanisms For Dns (Edns0). Available:
Http://Tools.Ietf.Org/Html/Rfc2671
[9] Dnssec.Net. (2013). Dnssec: Dns Security Extensions Securing The Domain Name System.
Available: Http://Www.Dnssec.Net/
[10] T. Peng, C. Leckie, And K. Ramamohanarao, "Survey Of Network-Based Defense Mechanisms
Countering The Dos And Ddos Problems," Acm Comput. Surv., Vol. 39, P. 3, 2007.
[11] W. M. Eddy, "Defenses Against Tcp Syn Flooding Attacks," The Internet Protocol Journal Vol. 9,
2006.
[12] D. S. Paul Ferguson. (2000, Network Ingress Filtering: Defeating Denial Of Service Attacks Which
Employ Ip Source Address Spoofing. 1-10. Available: Http://Www.Ietf.Org/Rfc/Rfc2827.Txt
[13] Cert. (1997, Cert® Advisory Ca-1996-01 Udp Port Denial-Of-Service Attack. Available:
Http://Www.Cert.Org/Advisories/Ca-1996-01.Html
[14] T. Bowman, "Incident Handling And Hacker Exploits Certification Practical Version 1.5c," Sans
Institutemay 10, 2013 2001.
[15] M. Sauter, ""Loic Will Tear Us Apart": The Impact Of Tool Design And Media Portrayals In The
Success Of Activist Ddos Attacks," American Behavioral Scientist, P. 0002764213479370.
[16] M. Prince, "Deep Inside A Dns Amplification Ddos Attack," Vol. 2013, Ed: Cloudflare, October 30,
2012 P. Web Log Post.
15. International Journal of Network Security & Its Applications (IJNSA), Vol.6, No.3, May 2014
71
[17] Cert. (2000, Cert® Advisory Ca-1998-01 Smurf Ip Denial-Of-Service Attacks. Available:
Http://Www.Cert.Org/Advisories/Ca-1998-01.Html
[18] C. A. Huegen. (2000, The Latest In Denial Of Service Attacks: "Smurfing" Description And
Information To Minimize Effects. Available: Http://Www.Pentics.Net/Denial-Of-Service/White-
Papers/Smurf.Cgi
[19] A. Litan. (2013, Arming Financial And E-Commerce Services Against Top 2013 Cyberthreats.
Available: Http://Www.Gartner.Com/Technology/Reprints.Do?Id=1-1f9xfpx&Ct=130429&St=Sb
[20] S. Mcgregory, "Preparing For The Next Ddos Attack," Network Security, Vol. 2013, Pp. 5-6, 5//
2013.
[21] Arbor Networks, "The Growing Threat Of Application-Layer Ddos Attacks," 2012.
[22] S. Ranjan, R. Swaminathan, M. Uysal, And E. Knightly, "Ddos-Resilient Scheduling To Counter
Application Layer Attacks Under Imperfect Detection," In Infocom 2006. 25th Ieee International
Conference On Computer Communications. Proceedings, 2006, Pp. 1-13.
[23] D. Watson, "Web Application Attacks," Network Security, Vol. 2007, Pp. 10-14, 10// 2007.
[24] C. Linhart, A. Klein, R. Heled, And S. Orrin, "Http Request Smuggling," Computer Security Journal,
Vol. 22, Pp. 13-26, 2006.
[25] S. Heron, "Denial Of Service: Motivations And Trends," Network Security, Vol. 2010, Pp. 10-12, 5//
2010.
[26] T. Rozekrans And J. D. Koning. (2013, Defending Against Dns Reflection Amplication Attacks.
System & Network Engineering Rp1.
[27] S. Lima, "3 Ways To Use Dns Rate Limit Against Ddos Attacks," Vol. 2013, Ed: Cloudshield
January 29, 2013 P. Web Log Post.
[28] I. Avramopoulos And M. Suchara, "Protecting The Dns From Routing Attacks: Two Alternative
Anycast Implementations," Security & Privacy, Ieee, Vol. 7, Pp. 14-20, 2009.
[29] Cert. (2012, May 7). "Anonymous" Ddos Activity. Available: Http://Www.Us-
Cert.Gov/Ncas/Alerts/Ta12-024a
[30] A. S. Aiko Pras, Giovane C. M. Moura, Idilio Drago, Rafael Barbosa, Ramin Sadre, Ricardo Schmidt,
Rick Hofstede, "Attacks By “Anonymous” Wikileaks Proponents Not Anonymous," University Of
Twente, Enschede, The Netherlands2010.
[31] T. Komatsu And A. Namatame, "On The Effectiveness Of Rate-Limiting Methods To Mitigate
Distributed Dos (Ddos) Attacks(<Special Section>New Challenge For Internet Technology And Its
Architecture)," Ieice Transactions On Communications, Vol. 90, Pp. 2665-2672, 2007/10/01 2007.
[32] G. Muharremoğlu. (2012) Web Application Level Approach Against The Http Flood Attacks : Iosec
Http Anti Flood/Dos Security Gateway Module. Hakin9 - It Security Magazine. 56-59. Available:
Http://Www.Iosec.Org/Hakin9_11_2012_Iosec.Pdf
[33] P. Chwalinski, R. Belavkin, And X. Cheng, "Detection Of Http-Get Attack With Clustering And
Information Theoretic Measurements," In Foundations And Practice Of Security. Vol. 7743, J.
Garcia-Alfaro, F. Cuppens, N. Cuppens-Boulahia, A. Miri, And N. Tawbi, Eds., Ed: Springer Berlin
Heidelberg, 2013, Pp. 45-61.
[34] D. Das, U. Sharma, And D. K. Bhattacharyya, "Detection Of Http Flooding Attacks In Multiple
Scenarios," Presented At The Proceedings Of The 2011 International Conference On Communication,
Computing & Security, Rourkela, Odisha, India, 2011.
Authors
Fui Fui Wong is currently a Ph.D. candidate in the Department of Computer Science and Technology, at
TongJi University, China. She received her Master of Information and Communication Technology from
University of Wollongong, Australia in 2004. Her research interests are Network Security and Cloud
Computing.
Prof. Dr. Cheng Xiang Tan is a Professor at the Department of Computer Science and Technology of
TongJi University, China. He received his Ph.D. degree from Northwestern polytechnical university, China
in 1994. He is a member of the Information Security Standardization Commission, China Ministry of
Public Security, Consultant for China State Project Anti-Cybercrime Computer Forensics, and founding
Vice President of China State Research Centre Against Computer Attacks and Virus. His research activity
is focus on information security, cell phone and mobile security with a special interest in digital forensics.