To simulate an intrusion detection projects using OPNET (Riverbed Modeler) that enables designing and estimating how an Intrusion Detection System (IDS) operates in identifying and reacting to malicious activity within a network. Below is a detailed procedure to simulate this project in OPNET.
Steps to Simulate Intrusion Detection Projects in OPNET
- Define the Intrusion Detection Objectives
- Detect the kind of IDS to replicate like Network-based IDS (NIDS) or Host-based IDS (HIDS).
- Indicate attack types such as DoS, unauthorized access, port scanning, malware to experiment the IDS capabilities.
- Find crucial performance parameters that contain detection accuracy, response time, false positives or negatives, and resource utilization.
- Set Up the Network Topology
- Design the network: Make a network topology with routers, switches, firewalls, servers, and client nodes using OPNET’s GUI.
- Configure network protocols: Configure the essential protocols like TCP or IP, HTTP and describe applications such as web browsing, file sharing to replicate normal network traffic.
- Deploy the Intrusion Detection System (IDS)
- Install IDS nodes: Locate IDS nodes within strategic network positions like at the gateway, close critical servers, or on the internal network.
- Set detection rules: Set up the IDS with rules to detect abnormal or malicious patterns within network traffic, like:
- Suspicious port access (e.g., unexpected SSH or FTP requests)
- Abnormally high traffic rates (DoS)
- Unusual data packet sizes or formats.
- Configure alerts and logs: Allow recording and notifying on IDS nodes to encapsulate and report identified threats.
- Simulate Attack Scenarios
Make particular attack models to estimate the IDS’s detection capabilities. Some instances involve:
- Denial of Service (DoS) Attack:
- Set up a node to make excessive traffic that aiming a certain server or network segment.
- Experiment the IDS’s ability to acknowledge the traffic surge and activate an alert.
- Port Scanning:
- Configure a node to scan several ports over the network or particular hosts, which trying to detect open ports.
- Monitor whether the IDS flags this performance as suspicious.
- Unauthorized Access Attempt:
- Mimic an attacker node attempt to record into protect systems with invalid identifications.
- Observe the IDS for discovery of suspicious login performances or repeated access attempts.
- Malware Traffic:
- Set up a node to simulate the affected device behavior by transmitting the uncommon outbound traffic to well-known malicious IPs.
- Verify if the IDS detect the abnormal patterns in addition to flags the traffic.
- Monitor Network and IDS Performance Metrics
- Detection Metrics:
- Monitor detection rates, alert counts, and kinds of identified threats such as DoS, unauthorized access.
- Calculate the response time among begin of an attack and the alert generation of IDS.
- False Positives and Negatives:
- Record any legitimate traffic erroneously flagged as missed attacks (false negatives) or malicious (false positives).
- System Resource Utilization:
- Observe CPU and memory usage on the IDS nodes, as high detection rates can be filtered resources.
- Analyze the Effectiveness of the IDS
- Evaluate Detection Accuracy: Examine how successfully the IDS identify each kind of attack and whether it effectively makes alerts for malicious performances.
- Assess Performance Impact: Check any effect on network latency or throughput, particularly if the IDS are in-order with network traffic.
- Optimize for False Positives: Change IDS rules or thresholds to minimize needless alerts, enhancing accuracy and response time.
- Optimize and Re-Test the IDS (Optional)
- Refine IDS Rules: Adapt detection metrics like observed false positives or false negatives enhancing exactness.
- Simulate Under Varying Loads: Maximize the network load or amount of attack instances, under heavy traffic to experiment the IDS’s scalability and behaviour.
- Generate Reports and Document Findings
- Visualize Detection Results: Indicate the intrusion attempts, detection rates, and false positives over time using OPNET’s analysis tools.
- Summarize Findings: Record the IDS’s performance, detection capabilities, and areas for enhancement according to the simulation outcomes.
Finally, we had done the simulation approach on how to model and how to estimate the Intrusion Detection projects that were simulated using the OPNET environment. If you have any more doubts, we will be clarified it too. We assure you of the best research ideas and topics for Intrusion Detection Projects in your area of interest. Contact us for customized simulation assistance from the phdprime.com team.
