top of page

Multi-day Severe DDoS Attack Devastates Internet Archive: Unleashing Quantum Machine Learning for Superior Defense


Imagine waking up to find that one of the Internet’s most cherished resources is under attack. For the past few days, the Internet Archive, the non-profit digital library beloved by millions, has been battling a massive distributed denial-of-service (DDoS) attack. Tens of thousands of fake information requests per second have bombarded the site, causing major disruptions by an unknown adversary. The Wayback Machine, a vital tool for preserving the digital past, has been particularly hard hit. But how could BotMasters do this?In parallel Operation Endgame arrested some BotMasters.



BotMasters are hackers who create a stealthy adversarial network of zombie (hacked) devices and use them to mask the IP addresses of the servers they use for Command and Control.

Defenders must detect the masking mechanism. One example of such a mechanism is the Domain Generation Algorithm (DGA). In this approach, BotMasters create numerous fake domain names to hide their real IP addresses using free DNS servers and generated domains.

Here is an example of a such botnet

import hashlib
import time
import random
import string
import os

# Function to generate domain names using DGA
def generate_domain(seed, date):
    random.seed(seed + date)
    domain = ''.join(random.choices(string.ascii_lowercase + string.digits, k=16)) + ".com"
    return domain

# Get the current date as a seed
current_date = time.strftime("%Y%m%d")

# Generate a list of domains for today
domains = [generate_domain("secret_seed", current_date) for _ in range(10)]

print("Generated domains for today:")
for domain in domains:
    print(domain)

# Simulate the bot trying to connect to one of the domains
selected_domain = random.choice(domains)
print(f"Bot attempting to connect to: {selected_domain}")

# Example function for bot to communicate with C&C server
def communicate_with_c2(domain):
	# In a real scenario, this would involve network communication    
	# Here we'll just simulate a successful connection
    print(f"Connecting to C&C server at {domain}...")    
	# Simulated commands from C&C server
    commands = ["download payload", "execute payload", "send data"]
    return random.choice(commands)

# Function to simulate payload download
def download_payload(url):    
	# Simulate downloading a file
    print(f"Downloading payload from {url}...")
    payload_content = "This is a simulated payload."
    with open("payload.txt", "w") as f:
        f.write(payload_content)
    print("Payload downloaded and saved as payload.txt.")

# Function to execute the downloaded payload
def execute_payload():
    print("Executing payload...")
    with open("payload.txt", "r") as f:
        payload_content = f.read()
    # Simulate executing the payload
    print(f"Payload content: {payload_content}")
    # In a real scenario, this would involve running the payload

# Simulate bot receiving a command from C&C server
command = communicate_with_c2(selected_domain)
print(f"Received command: {command}")

# Simulate handling the received command
if command == "download payload":
    download_payload(f"http://{selected_domain}/payload")
elif command == "execute payload":
    execute_payload()
elif command == "send data":
    print("Sending data to C&C server...")
print("Bot operation complete.")


In this article, we want to show one way that CyberSec-DMS defense tools can detect this type of DDoS. Here we give an example of QML (Quantum Machine Learning) to show you how to detect these domains and update the denylist of the firewall automatically.


Step1-make model

You can see how Quantum Machine Learning can provide superior results in detecting fake domains here:


Step2-deploy your model for real-time inference

Also it is doable with other Global Cloud Service providers like Azure:


Step3- Make deny listing automated using an architecture like the below:


It contains numerous technical details, but it can stop DDoS attacks that traditional WAFs or firewalls cannot stop by leveraging Quantum Machine Learning.

You don't need to worry about this complex technology stack.

Transform your cybersecurity strategy with our cutting-edge Q-SIEM solution. You no longer need to worry about the complexities of managing this technical solution or the next DDoS attack disrupting your operations.

Our advanced system offers real-time monitoring, intelligent threat detection, and rapid response capabilities, ensuring your environment stays secure and resilient.

Choose Q-SIEM to experience:


  • Unmatched Security: Stop threats before they become breaches with our state-of-the-art detection mechanisms.

  • Seamless Integration: Easily integrate Q-SIEM into your existing infrastructure without any hassle.

  • Peace of Mind: Focus on your core business while we handle your cybersecurity needs.


Don’t wait for the next attack — empower your defenses today with Q-SIEM. You may think you have the best solution; in fact, the Internet Archive thought so. Contact us to learn more and schedule a demo.

12 views0 comments

Comments


bottom of page