How to Implement Radio Fingerprinting in OMNeT++
To implement radio fingerprinting in OMNeT++ has encompasses to emulate a scenario where the devices are identified based on distinct features in their radio signal is known as radio fingerprints. This is especially helpful in security applications like device authentication and in scenarios where classifying the individual devices based on their transmission characteristics is needed. The below are the procedures to implementing radio fingerprinting in OMNeT++ with examples:
Step-by-Step Implementation:
Step 1: Set Up the OMNeT++ Environment
Make sure that OMNeT++ and essential libraries like INET are installed and configured correctly. INET delivers the models for wireless communication that can expand to conclude the radio fingerprinting functionality.
Step 2: Define the Radio Fingerprinting Model
Radio fingerprinting depends on extracting features from the physical layer signals and these features can be based on features such as signal strength, phase noise, frequency offset, etc. For simplicity, we will describe a simple model that allocates a distinct “fingerprint” to each node based on these characteristics.
Example Radio Fingerprint Module
class RadioFingerprint
{
public:
int deviceId; // Unique device ID
double signalStrength; // Example characteristic: signal strength
double frequencyOffset; // Example characteristic: frequency offset
RadioFingerprint(int id) : deviceId(id), signalStrength(0), frequencyOffset(0) {}
void setSignalStrength(double strength) { signalStrength = strength; }
void setFrequencyOffset(double offset) { frequencyOffset = offset; }
// Generate a fingerprint string based on the characteristics
std::string generateFingerprint() const
{
std::stringstream ss;
ss << “DeviceID:” << deviceId << “_SS:” << signalStrength << “_FO:” << frequencyOffset;
return ss.str();
}
};
Step 3: Implement the Radio Fingerprinting Logic
Execute the logic that creates and transmits radio fingerprints when a device transfers the packet. The receiver will use these fingerprints to classify the transmitting device.
Example Transmitter Logic
class RadioFingerprintTransmitter : public cSimpleModule
{
protected:
virtual void initialize() override;
virtual void handleMessage(cMessage *msg) override;
void sendPacket();
private:
RadioFingerprint fingerprint;
cMessage *sendTimer;
};
void RadioFingerprintTransmitter::initialize()
{
int deviceId = par(“deviceId”);
fingerprint = RadioFingerprint(deviceId);
fingerprint.setSignalStrength(par(“signalStrength”).doubleValue());
fingerprint.setFrequencyOffset(par(“frequencyOffset”).doubleValue());
sendTimer = new cMessage(“sendTimer”);
scheduleAt(simTime() + par(“sendInterval”), sendTimer);
}
void RadioFingerprintTransmitter::handleMessage(cMessage *msg)
{
if (msg == sendTimer)
{
sendPacket();
scheduleAt(simTime() + par(“sendInterval”), sendTimer);
}
else
{
delete msg;
}
}
void RadioFingerprintTransmitter::sendPacket()
{
cMessage *packet = new cMessage(“DataPacket”);
packet->addPar(“fingerprint”) = fingerprint.generateFingerprint().c_str();
send(packet, “out”);
}
Example Receiver Logic
class RadioFingerprintReceiver : public cSimpleModule
{
protected:
virtual void handleMessage(cMessage *msg) override;
private:
void processPacket(cMessage *msg);
};
void RadioFingerprintReceiver::handleMessage(cMessage *msg)
{
processPacket(msg);
delete msg;
}
void RadioFingerprintReceiver::processPacket(cMessage *msg)
{
std::string fingerprint = msg->par(“fingerprint”).stringValue();
EV << “Received packet with fingerprint: ” << fingerprint << endl;
// Here you can add logic to identify the device based on the fingerprint
}
Step 4: Define the Network Nodes with Radio Fingerprinting
Generate nodes that signify the devices in the network and each node will make a distinct radio fingerprint when transmitting the information.
Example Node Definition
module RadioFingerprintNode
{
parameters:
@display(“i=block/wifilaptop”); // Icon for visualization
gates:
inout ethg; // Ethernet communication gate
submodules:
eth: <default(“EthernetInterface”)>; // Ethernet NIC for communication
transmitter: RadioFingerprintTransmitter;
receiver: RadioFingerprintReceiver;
connections:
ethg <–> eth.physIn;
transmitter.out –> ethg;
ethg –> receiver.in;
}
Step 5: Define the Network Scenario
Generate a network scenario where multiple nodes interact, and the receiver identifies each transmitting node based on its radio fingerprint.
Example Network Scenario Definition
network RadioFingerprintNetwork
{
parameters:
int numNodes = default(3); // Number of nodes in the network
submodules:
nodes[numNodes]: RadioFingerprintNode {
@display(“p=100,100”);
}
connections allowunconnected:
for i=0..numNodes-2 {
nodes[i].ethg <–> EthernetCable <–> nodes[i+1].ethg;
}
}
Step 6: Configure the Simulation Parameters
Setup the simulation parameters in the .ini file, that has includes the signal strength and frequency offset values to replicate various fingerprints.
Example Configuration in the .ini File
network = RadioFingerprintNetwork
sim-time-limit = 300s
# Radio fingerprinting parameters
*.nodes[0].transmitter.deviceId = 1
*.nodes[0].transmitter.signalStrength = 100.0
*.nodes[0].transmitter.frequencyOffset = 5.0
*.nodes[1].transmitter.deviceId = 2
*.nodes[1].transmitter.signalStrength = 90.0
*.nodes[1].transmitter.frequencyOffset = 4.5
*.nodes[2].transmitter.deviceId = 3
*.nodes[2].transmitter.signalStrength = 85.0
*.nodes[2].transmitter.frequencyOffset = 4.8
# Traffic generation
*.nodes[*].transmitter.sendInterval = 1s # Interval between sending messages
Step 7: Run the Simulation
Compile and execute the simulation. The transmitter nodes will transfer packets with their unique radio fingerprints, and the receiver will log these fingerprints.
Step 8: Analyse the Results
Use OMNeT++’s analysis tools to assess the efficiency of the radio fingerprinting. Check the following:
- Correctness of Fingerprints: Make sure that each device’s fingerprint is distinct and appropriately transmitted and received.
- Identification Accuracy: check that the receiver can correctly identify the transmitting device based on the received fingerprint.
Step 9: Extend the Simulation (Optional)
We can expand the simulation by:
- Adding More Complex Fingerprints: To conclude more characteristics like phase noise, modulation scheme, or antenna characteristics to make more complex fingerprints.
- Simulating Attacks: validate the robustness of radio fingerprinting by replicating the spoofing attacks where an attacker attempts to implement another device’s fingerprint.
- Realistic Channel Models: Establish more realistic channel models that impact the fingerprint characteristics, like multipath fading or Doppler shifts.
In this demonstration, we understood the distinct concept on how to stimulate the radio fingerprinting in the devices using OMNeT++ tool. We plan to elaborate more information regarding the radio fingerprinting. To achieve optimal outcomes in Radio Fingerprinting implementation, we invite you to contact us for personalized assistance.