To simulate Signalling System 7 (SS7) Attack environment in MATLAB, we can concentrate on susceptibilities in SS7 which impacts telecom networks, like location tracking, call/SMS interception, denial of service (DoS), and fraud. SS7 attacks exploit flaws in the signalling network utilized to configured and handle phone calls, text messages, and other telecommunication services among mobile networks.
Here’s a step-by-step approach to replicating SS7 attack mechanisms in MATLAB.
Key Components of an SS7 Attack Simulation
- Network Setup and Signalling Simulation:
- Generate a replicated scenario of network nodes signify attributes such as MSC (Mobile Switching Center), HLR (Home Location Register), VLR (Visitor Location Register), and SMSC (Short Message Service Center).
- Execute simple SS7 signalling messages like Send Routing Information (SRI), Update Location (UL), and MAP (Mobile Application Part) operations which the SS7 networks were utilized.
- SS7 Attack Mechanisms:
- Location Tracking: Replicate how an attacker can request location data around a target device by transmitting spoofed SRI or Send Routing Information for Short Message (SRI-SM) requests.
- SMS Interception or Redirection: Replicate SMS redirection using spoofed SRI-SM messages, possibly interrupting the SMS content.
- Denial of Service (DoS): Execute a environment in which an attacker floods a target network node with SS7 messages, exhausting resources.
- Call Interception or Forwarding: Replicate unauthorized call transmit by manipulating the MAP protocol.
- Detection and Analysis:
- Measure the simulated SS7 traffic to identify abnormal patterns signifies an attack.
- Utilize statistical evaluation to identify unusual request frequencies, high error rates, or resource exhaustion.
Example Code Outline
Here’s an instance MATLAB code describes to replicate an SS7 location tracking attack environment with simple signaling and evaluation functions.
- Network Setup and Signaling Message Simulation
% Define nodes in the network (MSC, HLR, VLR, SMSC)
nodes = {‘MSC’, ‘HLR’, ‘VLR’, ‘SMSC’, ‘Attacker’};
numNodes = length(nodes);
% Create adjacency matrix representing links (1 means connected, 0 means no link)
networkMatrix = [
0 1 1 1 1; % MSC connected to HLR, VLR, SMSC, and Attacker
1 0 1 1 1; % HLR connected to MSC, VLR, SMSC, and Attacker
1 1 0 1 1; % VLR connected to MSC, HLR, SMSC, and Attacker
1 1 1 0 1; % SMSC connected to MSC, HLR, VLR, and Attacker
1 1 1 1 0 % Attacker connected to MSC, HLR, VLR, and SMSC
];
% Display network nodes and connections
disp(‘Network Nodes and Connections:’);
disp(array2table(networkMatrix, ‘VariableNames’, nodes, ‘RowNames’, nodes));
- Simulate SS7 Location Tracking Attack (Spoofed SRI Request)
% Function to simulate Send Routing Information (SRI) message
function response = sendSRI(sender, receiver, target)
disp([‘[‘, sender, ‘] Sending SRI request to [‘, receiver, ‘] for target [‘, target, ‘]’]);
% Simulate valid response with target location if message comes from trusted node
if strcmp(receiver, ‘HLR’)
if strcmp(sender, ‘MSC’) || strcmp(sender, ‘VLR’)
response = [‘Location of ‘, target, ‘ found in network’];
else
response = ‘Unauthorized request – Spoofed SRI detected’;
end
else
response = ‘Invalid message routing – SRI must go to HLR’;
end
end
% Attacker tries to track a target’s location by sending a spoofed SRI to the HLR
sender = ‘Attacker’;
receiver = ‘HLR’;
target = ‘TargetDevice’;
response = sendSRI(sender, receiver, target);
disp([‘Response from HLR: ‘, response]);
- Denial of Service Attack Simulation (Flooding HLR with SRI Requests)
% Function to simulate a DoS attack by flooding with SRI requests
function dosAttack(targetNode, duration)
disp([‘— Starting DoS Attack on ‘, targetNode, ‘ —‘]);
requests = 0;
for t = 1:duration
% Simulate SRI request flooding
response = sendSRI(‘Attacker’, targetNode, ‘RandomTarget’);
disp([‘Attempt ‘, num2str(t), ‘: ‘, response]);
requests = requests + 1;
end
disp([‘Total requests sent during DoS: ‘, num2str(requests)]);
end
% Run DoS attack on HLR for 10 simulated time steps
dosAttack(‘HLR’, 10);
- Anomaly Detection and Analysis
% Collect SRI request data for anomaly detection (example data)
timeSteps = 100;
sriRequests = randi([0, 10], 1, timeSteps); % Random SRI requests per time step
dosThreshold = 8; % Threshold for unusual request frequency
% Detect DoS by analyzing SRI request rate
anomalousTimes = find(sriRequests > dosThreshold);
disp(‘Anomalous SRI Request Rates Detected at Time Steps:’);
disp(anomalousTimes);
% Plot request rates over time
figure;
plot(1:timeSteps, sriRequests, ‘-o’);
hold on;
yline(dosThreshold, ‘–r’, ‘DoS Threshold’);
title(‘SRI Request Rate Over Time’);
xlabel(‘Time Step’);
ylabel(‘SRI Requests’);
legend(‘SRI Requests’, ‘Threshold’);
grid on;
Explanation of the Code
- Network Setup and Signaling Message Simulation: The networkMatrix describes connections among network nodes like MSC, HLR, VLR, SMSC, and an attacker node to signify SS7 signalling links. Each node can transmit SS7 signaling requests to other nodes according to the matrix.
- Location Tracking Attack (Spoofed SRI): The sendSRI function replicates an SRI request transmit by a node (potentially spoofed by an attacker) to the HLR to recover location information of a target device. If an unauthorized node such as the attacker transmits the request, the HLR identifies it as unauthorized.
- Denial of Service Attack Simulation: The dosAttack function replicate a DoS attack by transmitting repetitive SRI requests to a target node such as HLR for a certain duration that replicates resource exhaustion.
- Anomaly Detection and Analysis: By generating random SRI request data in excess of time, thresholds maintenances to detect unusual request frequencies that demonstrate a DoS attack. The plot envisions the request rate, with threshold emphasizing anomalous traffic.
Extending the Simulation
For a briefer SS7 attack simulation:
- SMS and Call Interception Simulation: execute SMS redirection by spoofing SRI-SM requests, possibly interrupting or redirecting SMS messages.
- Unauthorized Call Forwarding: Mimic an unauthorized call redirection by manipulating MAP messages to change call routing paths.
- Advanced Anomaly Detection: Utilize statistical or machine learning approaches to know uncommon traffic patterns, improving the ability to identify attacks in real-time.
- Attack Variants: Replicate other SS7 attacks like IMSI Catching (to collect subscriber information) or fraudulent call redirection.
This illustration has given you the general steps to create a simulation network which help us to simulate the Signalling System 7 (SS7) Attack in the MATLAB environment and also we provide how to attach the enhance features to the simulation. If you have any queries about this approach, we will guide you.
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