A Distributed Denial of Service or DDoS attack is a type of DoS attack in which an attacker uses a number of compromised computers to send a huge number of requests to the target host. Attackers often use a botnet to perpetrate this type of attack. (What is a botnet?)(What is an IoT Botnet?)

Attackers may first use malware to compromise a number of devices or computers. The malware may turn the compromised devices into bots or zombie computers. Then, attackers may control the devices remotely and make them send a huge number of requests to a target host that results in a DoS attack.

For example, attackers may use a botnet to send a huge number of ICMP Echo request messages or ping packets to a target host. The target host may end up consuming all its computational resources to send replies to the ping packets and that may result in a DDoS attack. This type of DDoS attack is also called a Ping Flood. (What is Ping Flood and how does it work?)

In a DoS attack, attackers often spoof the source IP address of the packets before sending the packets to the target host. As a result, it becomes difficult to detect the source of the attack. (What is IP address spoofing?)

 

What is a DrDoS attack?

A DrDoS or Distributed Reflection Denial of Service attack is a type of DDoS attack. In this attack, attackers first select a large number of victim hosts and send requests to those victim hosts. But, attackers spoof the source IP address of the sent packets and instead use the IP address of a target host as the source IP address. As a result, the victim hosts start sending replies to the target host. As the number of victim hosts is large, and the size of the replies is more than the size of the requests, the huge number of replies consume the network bandwidth of the target host and that results in a DoS attack.

Here, attackers use multiple source machines to perpetrate the attack. So, it is a DDoS attack. And, the requests made to the victim hosts are reflected or redirected to the target host. So, it is called a Distributed Reflection Denial of Service attack or DrDoS attack.

Attackers may exploit several Internet protocols to perpetrate this attack. Attackers often use DNS, NTP, SNMP, or CHARGEN protocols to make this attack. For example, attackers may send spoofed requests to DNS resolvers and use the IP address of the target host as the source IP address of all the sent packets. Each DNS resolver will send a response that is larger in size than the actual request. And, when the huge number of responses will reach the target host, that will result in a DrDoS attack.

How to protect servers from DoS, DDoS and DrDoS attacks? We have discussed that in detail in this article: How to protect servers from DoS and DDoS attacks?

I hope this helps. However, interested readers who want to know more about how different web application attacks work and how we can prevent them can refer to the book “Web Application Vulnerabilities And Prevention.”

 

Security Fundamentals Practice Tests

The Security Fundamentals Practice Tests test one’s fundamental knowledge of cyber security. The practice tests are good for those who are preparing for various certification exams like the CCNA, CCNP, or CompTIA. They are also good for students and IT/security professionals who want to improve their understanding of cyber security.

These practice tests are accessible only to Premium Members. Please login below to take these tests or upgrade your membership:

Not a member yet? Please follow the link below to register for The Security Buddy.

You can find more on The Security Buddy membership plan here:


Facebooktwitterredditpinterestlinkedinmail

Calculate the pseudoinverse of a matrix using Python

What is the pseudoinverse of a matrix? We know that if A is a square matrix with full rank, then A-1 is said to be the inverse of A if the following condition holds: $latex AA^{-1}=A^{-1}A=I $ The pseudoinverse or the Moore-Penrose inverse of a matrix is a...

Cholesky decomposition using Python

What is Cholesky decomposition? A square matrix A is said to have Cholesky decomposition if it can be written as a product of a lower triangular matrix and its conjugate transpose. $latex A=LL^{*} $ If all the entries of A are real numbers, then the conjugate...

Tensor Hadamard Product using Python

In one of our previous articles, we already discussed what the Hadamard product in linear algebra is. We discussed that if A and B are two matrices of size mxn, then the Hadamard product of A and B is another mxn matrix C such that: $latex H_{i,j}=A_{i,j} \times...

Perform tensor addition and subtraction using Python

We can use numpy nd-array to create a tensor in Python. We can use the following Python code to perform tensor addition and subtraction. import numpy A = numpy.random.randint(low=1, high=10, size=(3, 3, 3)) B = numpy.random.randint(low=1, high=10, size=(3, 3, 3)) C =...

How to create a tensor using Python?

What is a tensor? A tensor is a generalization of vectors and matrices. It is easily understood as a multidimensional array. For example, in machine learning, we can organize data in an m-way array and refer it as a data tensor. Data related to images, sounds, movies,...

How to combine NumPy arrays using horizontal stack?

We can use the hstack() function from the numpy module to combine two or more NumPy arrays horizontally. For example, we can use the following Python code to combine three NumPy arrays horizontally. import numpy A = numpy.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) B =...

How to combine NumPy arrays using vertical stack?

Let’s say we have two or more NumPy arrays. We can combine these NumPy arrays vertically using the vstack() function from the numpy module. For example, we can use the following Python code to combine three NumPy arrays vertically. import numpy A = numpy.array([[1, 2,...

Singular Value Decomposition (SVD) using Python

What is Singular Value Decomposition (SVD)? Let A be an mxn rectangular matrix. Using Singular Value Decomposition (SVD), we can decompose the matrix A in the following way: $latex A_{m \times n}=U_{m \times m}S_{m \times n}V_{n \times n}^T $ Here, U is an mxm matrix....

Eigen decomposition of a square matrix using Python

Let A be a square matrix. Let’s say A has k eigenvalues λ1, λ2, ... λk. And the corresponding eigenvectors are X1, X2, ... Xk. $latex X_1=\begin{bmatrix} x_{11} \\ x_{21} \\ x_{31} \\ ... \\ x_{k1} \end{bmatrix} \\ X_2=\begin{bmatrix} x_{12} \\ x_{22} \\ x_{32} \\ ......

How to calculate eigenvalues and eigenvectors using Python?

In our previous article, we discussed what eigen values and eigenvectors of a square matrix are and how we can calculate the eigenvalues and eigenvectors of a square matrix mathematically. We discussed that if A is a square matrix, then $latex (A- \lambda I) \vec{u}=0...

Amrita Mitra

Author

Ms. Amrita Mitra is an author, who has authored the books “Cryptography And Public Key Infrastructure“, “Web Application Vulnerabilities And Prevention“, “A Guide To Cyber Security” and “Phishing: Detection, Analysis And Prevention“. She is also the founder of Asigosec Technologies, the company that owns The Security Buddy.

0 Comments

Submit a Comment

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Not a premium member yet?

Please follow the link below to buy The Security Buddy Premium Membership.

Featured Posts

Translate »