How to implement Network Ransomware Detection in ns3

To implement the network ransomware detection in ns3 has numerous steps that generates and setup the network emulation then it generate the ransomware detection mechanism. The given below are the detailed procedures on how to implement the ransomware detection in ns3:

Step-by-Step Implementation:

Step 1: Set Up ns3 Environment

1. Install ns3: Install the ns3 in the computer.
2. Familiarize yourself with ns3: Read through the ns3 tutorial to know the simple concepts and structure of ns3 simulations.

Step 2: Define the Network Topology

1. Create a Simple Network: describe the  basic network topology using ns3 and it  contains creating nodes, setting up channels, and configuring IP addresses.

#include “ns3/core-module.h”

#include “ns3/network-module.h”

#include “ns3/internet-module.h”

#include “ns3/point-to-point-module.h”

using namespace ns3;

int main(int argc, char *argv[]) {

NodeContainer nodes;

nodes.Create(3); // Example: 3 nodes (1 server, 1 client, 1 attacker)

PointToPointHelper pointToPoint;

pointToPoint.SetDeviceAttribute(“DataRate”, StringValue(“5Mbps”));

pointToPoint.SetChannelAttribute(“Delay”, StringValue(“2ms”));

NetDeviceContainer devices;

devices = pointToPoint.Install(nodes);

InternetStackHelper stack;

stack.Install(nodes);

Ipv4AddressHelper address;

address.SetBase(“10.1.1.0”, “255.255.255.0”);

Ipv4InterfaceContainer interfaces = address.Assign(devices);

Simulator::Run();

Simulator::Destroy();

return 0;

}

Step 3: Implement Ransomware Detection Mechanism

1. Create Detection Application: To build the application or module that identifies ransomware activities. Ransomware is usually shows the certain characteristics like rapid file encryption and anomalous network traffic patterns. We need to execute a simple detection mechanism based on these characteristics.

class RansomwareDetectionApp : public Application {

public:

RansomwareDetectionApp() {}

virtual ~RansomwareDetectionApp() {}

void SetDetectionCriteria(std::function<bool(Ptr<const Packet>)> criteria) {

m_criteria = criteria;

}

private:

virtual void StartApplication() {

// Schedule the first packet inspection

Simulator::Schedule(Seconds(1.0), &RansomwareDetectionApp::InspectTraffic, this);

}

virtual void StopApplication() {

// Teardown code

}

void InspectTraffic() {

// Inspect packets for ransomware characteristics

// Example: Check for rapid file encryption patterns or anomalous network traffic

// If ransomware is detected, take appropriate action (e.g., alert or block traffic)

// Reschedule the next inspection

Simulator::Schedule(Seconds(1.0), &RansomwareDetectionApp::InspectTraffic, this);

}

std::function<bool(Ptr<const Packet>)> m_criteria;

};

Step 4: Configure and Integrate the Detection Application

1. Attach the Detection Application to Nodes: Attach your ransomware detection application to the relevant nodes in your network. For example, we need to monitor traffic on a server node.

Ptr<RansomwareDetectionApp> detectionApp = CreateObject<RansomwareDetectionApp>();

detectionApp->SetDetectionCriteria([](Ptr<const Packet> packet) {

// Define detection logic (e.g., identify ransomware traffic patterns)

return false; // Example: No ransomware detected

});

Ptr<Node> serverNode = nodes.Get(1); // Example: Server node

serverNode->AddApplication(detectionApp);

Run the Simulation: Run the simulation to observe the behaviour of your ransomware detection mechanism.

detectionApp->SetStartTime(Seconds(2.0));

detectionApp->SetStopTime(Seconds(10.0));

Simulator::Run();

Simulator::Destroy();

Step 5: Analyze and Visualize Results

1. Collect Metrics: To gather relevant metrics to assess the performance of the ransomware detection mechanism, like detection accuracy, false positives, and false negatives.
2. Visualize Results: Use tools like Gnuplot or Python’s Matplotlib to visualize the simulation results and analyze the effectiveness of your detection mechanism.

At the last, we entirely understand how the network ransomware detection is implemented in ns3 and that is used to classify the disruption in the network. More information will be shared in further about network ransomware detection and its execution in different simulations.

Reach out to us to learn more about how your project is doing; we’ll provide you with a detailed report. If you need help with implementing Ransomware Detection in ns3program, just get in touch. We also do comparison analysis for your project, so share all your details with us for extra support.