How to Begin Implement a Network Forensics in NS3

To stimulate the Network Forensics in ns3 tool has contains the generating a replication of that we can seizure, analyze, and examine the network actions for find the malicious behavior, diagnose security incidents, or understand network performance. Here’s an organized method for executing the network forensics in ns-3:

Steps to Begin Implement a Network Forensics in NS3

1. Set up ns-3 Environment

1. Install ns-3:
   • Download and install ns3 from the official website.
   • Validate the installation by a simple script such as ./waf –run hello-simulator.
2. Install Required Modules:
   • It contains the components such as internet, point-to-point, wifi, and applications.

2. Define Forensic Objectives

Clarify the goals of your network forensic simulation:

• Capture Traffic: Record the all packets flowing with the network.
• Analyze Activities: classify the suspicious designs or behaviors.
• Investigate Events: Recreate the movements like as attacks or unauthorized access.

3. Set up the Network Topology

1. Create Nodes:
   • Describe the devices for network, like as clients, servers, routers, and forensic monitoring nodes.

NodeContainer nodes;

nodes.Create(3); // Client, Server, and Forensic Node

1. Configure Connections:
   • Point-to-Point Links:

PointToPointHelper p2p;

p2p.SetDeviceAttribute(“DataRate”, StringValue(“100Mbps”));

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

NetDeviceContainer devices = p2p.Install(nodes.Get(0), nodes.Get(1));

1. • Wireless Network:

WifiHelper wifi;

YansWifiPhyHelper phy = YansWifiPhyHelper::Default();

YansWifiChannelHelper channel = YansWifiChannelHelper::Default();

phy.SetChannel(channel.Create());

WifiMacHelper mac;

mac.SetType(“ns3::AdhocWifiMac”);

NetDeviceContainer devices = wifi.Install(phy, mac, nodes);

1. Assign IP Addresses:

InternetStackHelper internet;

internet.Install(nodes);

Ipv4AddressHelper ipv4;

ipv4.SetBase(“10.1.1.0”, “255.255.255.0”);

Ipv4InterfaceContainer interfaces = ipv4.Assign(devices);

4. Set Up Forensic Data Collection

1. Packet Capture:
   • Use callbacks for track the all packets on a detailed connection or node.

Config::ConnectWithoutContext(“/NodeList/*/DeviceList/*/MacRx”, MakeCallback(&PacketCapture));

void PacketCapture(Ptr<const Packet> packet) {

NS_LOG_UNCOND(“Packet Captured: ” << packet->ToString());

}

1. Traffic Logging:
   • Use the metrices for AsciiTraceHelper network congestion for offline study.

AsciiTraceHelper ascii;

p2p.EnableAsciiAll(ascii.CreateFileStream(“forensic-log.tr”));

1. Flow Monitoring:
   • Use FlowMonitor for gathering the specific congestion statistics.

FlowMonitorHelper flowmon;

Ptr<FlowMonitor> monitor = flowmon.InstallAll();

5. Simulate Traffic

1. Generate Normal Traffic:
   • Use applications such as UdpEchoClientHelper or OnOffHelper.

UdpEchoServerHelper echoServer(9);

ApplicationContainer serverApps = echoServer.Install(nodes.Get(1));

serverApps.Start(Seconds(1.0));

serverApps.Stop(Seconds(10.0));

UdpEchoClientHelper echoClient(interfaces.GetAddress(1), 9);

echoClient.SetAttribute(“MaxPackets”, UintegerValue(100));

echoClient.SetAttribute(“Interval”, TimeValue(Seconds(0.1))); // Every 100 ms

echoClient.SetAttribute(“PacketSize”, UintegerValue(1024));

ApplicationContainer clientApps = echoClient.Install(nodes.Get(0));

clientApps.Start(Seconds(2.0));

clientApps.Stop(Seconds(10.0));

1. Simulate Malicious Activities:
   • It establish the abnormal or malicious congestion, like as a Denial of Service (DoS) attack.

OnOffHelper attack(“ns3::UdpSocketFactory”, InetSocketAddress(interfaces.GetAddress(1), 9));

attack.SetAttribute(“DataRate”, StringValue(“1Gbps”));

attack.SetAttribute(“PacketSize”, UintegerValue(1024));

ApplicationContainer attackApps = attack.Install(nodes.Get(2)); // Attacker Node

attackApps.Start(Seconds(3.0));

attackApps.Stop(Seconds(10.0));

6. Analyze Forensic Data

1. Real-Time Monitoring:
   • Payloads for suspicious designs of log packets and analyze headers.

void AnalyzePacket(Ptr<const Packet> packet) {

PppHeader pppHeader;

packet->PeekHeader(pppHeader);

if (/* suspicious traffic condition */) {

NS_LOG_UNCOND(“Potential intrusion detected!”);

}

}

1. Offline Analysis:
   • Distribute the logs and flow data for analysis using tools such as Wireshark or Python.
2. Event Reconstruction:
   • Associate the logs and specific packet for reconstruct the sequence of actions during the attack.

7. Visualize the Network

1. NetAnim:
   • Use the tool AnimationInterface for envisions the packet flows for interactions.

AnimationInterface anim(“network-forensics.xml”);

1. Graphical Tools:
   • Transfer the metrices and envision for the data using Python, MATLAB, or Excel.

8. Extend and Enhance

1. Deep Packet Inspection:
   • Examine the packet payloads for classify the designs, like as malware signatures.
2. Anomaly Detection:
   • Statistical approaches or machine learning use detect the unusual behaviors.
3. Real-Time Alerts:
   • Forwarding the alerts after suspicious actions is finding.

9. Evaluate Forensic Capabilities

1. Performance Metrics:
   • It includes the metrices for Packet seizure rate, false positives, finding the latency.
2. Scalability:
   • Validate the forensic system for larger networks by further nodes and traffic.

Example Use Cases

• Incident Investigation: Recreate the attacks such as DoS or data breaches.
• Threat Detection: The threats classify the interruptions and malicious behaviors.
• Network Performance Analysis: It recognizes the congestion designs and enhances the setting.

In this simulation setup, we offered the simple approaches that were demonstrated using the brief explanation related to the network forensics projects which were simulated and evaluated through ns3 tool. Some specific details regarding this process will be provided later.