How to Start Network Forensics Projects Using NS3

To start a network forensics project using NS3 which has contains to replicate the network activity, to seize data, and examining it to rebuild events and identifying possible security breaches. Network forensics targets to gather and examining the network traffic to analyse for security incidents, malicious activity, track intruders, or gather evidence. We will guide you through below procedure to configuring and executing the network forensics projects in NS3.

Steps to Stat Network Forensics Projects in NS3

  1. Define Project Objectives and Scope
  • Identify Forensic Use Cases:
    • Traffic Analysis and Packet Capture: Seize and examine the packets for suspicious activity.
    • Intrusion Detection and Reconstruction: Configure IDS for real-time detection that tracked by in-depth analysis to rebuild the attack events.
    • Incident Response Simulation: Design network response to events like denial-of-service (DoS) or data exfiltration, measuring the forensic capabilities.
    • Tracing Attack Origin: Detect and track the source of an attack which is helpful for DDoS or insider threat replications.
  • Define Key Performance Metrics:
    • Detection Rate: We estimate the accuracy within identifying malicious activities.
    • Forensic Completeness: We need to measure the ability, according to the captured data to rebuild complete series of events.
    • Resource Utilization: Estimate CPU, memory, and bandwidth effect of capturing and logging forensic data.
    • Latency and Throughput: Assess the forensic activities effect on network performance.
  1. Install and Set Up NS3
  • Download NS3: Go to NS3 official page to download the new version of NS3 on the computer.
  • Install NS3: We adhere to configure installation guide and check by executing an example script.
  • External Tools: Verify tools such as for packet analysis use Wireshark and Python for log analysis and visualization. To install Pandas and Scikit-Learn can also be supported if we are performing statistical or machine learning analysis on network logs.
  1. Design the Network Topology
  • Choose a Network Layout:
    • Star Topology: Replicate normal attack scenarios like DDoS to utilize a single target server along with several clients.
    • Multi-Segment Network: Mimic zones such as LAN, DMZ that are isolated by routers to observe inter-segment traffic.
    • Peer-to-Peer (P2P) Network: It is helpful for replicating the decentralized attacks like worm propagation.
  • Configure Nodes and Network Devices:
    • Make nodes like clients, servers, and routers to utilising NodeContainer.
    • For wired networks, we utilize CsmaHelper or use WifiHelper for wireless network topologies.
  1. Set Up Packet Capture for Forensic Analysis
  • Use NS3’s Tracing Tools:
    • PcapTrace: To seize packets at certain nodes or links examining the raw packet information.
    • AsciiTrace: Take high-level traffic summaries like packet counts, source-destination pairs, and timing.
    • Allow tracing on crucial nodes such as routers, servers, or firewalls, observing the inbound and outbound traffic.
  • Selective Capture Points:
    • Locate capture points on crucial nodes seizing high-value traffic. For instance:
      • Observe the incoming and outgoing traffic at servers.
      • On routers recording all traffic traversing diverse segments.
  • Log Export:
    • We need to store captured information to external files within tools such as Wireshark or for processing with Python for post-simulation analysis.
  1. Simulate Cyber Attacks for Forensic Testing
  • DDoS Attack Simulation:
    • Make high-rate UDP or TCP traffic to aim a server node using several nodes with OnOffApplication, to replicate a DDoS attack.
    • Examine and seize traffic detecting source IPs, request patterns, and traffic volumes.
  • Data Exfiltration:
    • Configure a node to transmit sensitive data packets occasionally to an unauthorized external node, to experiment the capability to identify the data leakage.
  • Port Scanning:
    • We mimic a port scan by containing a node that try to associate at diverse ports of a target, to permit the IDS identifying often connection attempts.
  • Malware Propagation:
    • Set an infected node associating to and “infect” neighboring nodes, to replicate the worm-like behavior, which distributes over the network.
  1. Implement Forensic Analysis Techniques
  • Traffic Analysis:
    • Examine packet headers, source and destination IPs, and protocol usage identifying patterns or anomalies, which show suspicious activity.
    • Record critical data like packet size, timing, and flags utilising NS3’s packet inspection capabilities.
  • Sequence and Timeline Reconstruction:
    • Arrange packets by timestamps rebuilding an attack’s timeline.
    • Link actions by integrating captured data including source and destination data following the series of events.
  • Intrusion Detection System (IDS):
    • Configure IDS rules identifying certain patterns like high packet counts from a single IP (for DDoS) or repeated connection attempts at specific ports (for port scanning).
    • For abnormal packet rates, unusual payload sizes, or suspicious source IPs to utilize threshold-based detection.
  1. Set Up Application Layer for Realistic Traffic
  • Normal Network Activity:
    • Make regular network traffic to utilize applications such as UdpEchoClient/UdpEchoServer and OnOffApplication.
    • Different traffic patterns by means of inserting web-like requests, streaming data, or file transfer activity.
  • Malicious Traffic Patterns:
    • Set attack traffic like high-rate bursts for DDoS, or connection attempts on several ports replicating the port scanning.
    • Design sensitive data packets utilising custom payloads within data exfiltration scenarios.
  1. Define and Measure Forensic Performance Metrics
  • Detection Rate:
    • We can log true positives (correctly identified attacks), false positives (normal traffic flagged as attacks), false negatives (missed attacks), and true negatives.
    • Compute the detection rate, false positive rate, and false negative rate, measuring the performance of IDS.
  • Reconstruction Accuracy:
    • Examine how successfully capture permits for comprehensive rebuilding of attack events.
    • Depends on the completeness of the captured sequence and any missing data, we estimate the accuracy.
  • Impact on Network Performance:
    • Compute the impact of data capture on latency and throughput knowing any forensic overhead.
  • Resource Usage:
    • Monitor CPU and memory usage to execute IDS or logging systems that particularly in attack for nodes.
  1. Simulate and Analyze Results
  • Run Simulation:
    • Experiment diverse scenarios like various attack types and intensities, to estimate the IDS effectiveness and forensic capabilities.
    • We execute the network both with and without forensic mechanisms, equating the performance and detection accuracy.
  • Data Collection and Export:
    • Accumulate packet data on headers, timing, and source-destination pairs to utilize NS3’s tracing tools.
    • Transfer records using Python, Wireshark, or other data analysis tools for post-simulation analysis.
  • Visualization and Analysis:
    • For visualizing packet flow, detection events, and timeline of network activity, we can utilize tools such as Matplotlib or Gnuplot.
    • Make logs to sum up detected attacks, key IPs involved, and the timeline of events.

Example Code Outline for a Network Forensics Project with DDoS Detection in NS3

The following is a simple code structure of NS3 to replicate a DDoS attack whereas capturing packets for forensic analysis.

#include “ns3/core-module.h”

#include “ns3/network-module.h”

#include “ns3/internet-module.h”

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

#include “ns3/applications-module.h”

#include <iostream>

using namespace ns3;

void MonitorTraffic(Ptr<Node> node, uint32_t threshold) {

Ptr<Ipv4> ipv4 = node->GetObject<Ipv4>();

uint32_t packetsReceived = ipv4->GetNReceived();

if (packetsReceived > threshold) {

std::cout << “Potential DDoS detected on Node ” << node->GetId()

<< ” – Packets received: ” << packetsReceived << std::endl;

}

Simulator::Schedule(Seconds(1.0), &MonitorTraffic, node, threshold); // Schedule next check

}

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

// Step 1: Create Nodes

NodeContainer attackers, targetNode;

attackers.Create(5); // Five attacking nodes

targetNode.Create(1); // One target node

// Step 2: Set Up Point-to-Point Links

PointToPointHelper p2p;

p2p.SetDeviceAttribute(“DataRate”, StringValue(“10Mbps”));

p2p.SetChannelAttribute(“Delay”, StringValue(“2ms”));

NetDeviceContainer devices;

for (uint32_t i = 0; i < attackers.GetN(); ++i) {

devices.Add(p2p.Install(attackers.Get(i), targetNode.Get(0)));

}

// Step 3: Install Internet Stack

InternetStackHelper internet;

internet.Install(attackers);

internet.Install(targetNode);

Ipv4AddressHelper address;

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

address.Assign(devices);

// Step 4: Set Up DDoS Attack Traffic

uint16_t port = 8080;

OnOffHelper onOffHelper(“ns3::UdpSocketFactory”, InetSocketAddress(Ipv4Address(“10.1.1.1”), port));

onOffHelper.SetConstantRate(DataRate(“1Mbps”)); // High-rate traffic for DDoS simulation

ApplicationContainer attackerApps;

for (uint32_t i = 0; i < attackers.GetN(); ++i) {

attackerApps.Add(onOffHelper.Install(attackers.Get(i)));

}

attackerApps.Start(Seconds(1.0));

attackerApps.Stop(Seconds(10.0));

// Step 5: Enable Packet Capture on Target Node for Forensic Analysis

p2p.EnablePcap(“forensic-capture”, devices.Get(1), true); // Enable pcap tracing

// Step 6: Run Simulation

Simulator::Run();

Simulator::Destroy();

return 0;

}

In this setup, we clearly learned about how to execute and simulate the Network Forensics projects using the tool NS3. We plan to provide more information about this topic based on your requests.

We provide you with a comprehensive guide for configuring and executing your tasks, offering personalized support throughout the process. The team at phdprojects.org specializes in Network Forensics Projects utilizing the NS3 tool, focusing on security incidents, identifying malicious activities, tracking intruders, and collecting evidence to deliver accurate results. Allow us to assist you in achieving optimal configuration with a clear and concise explanation.