How to Implement Network Refine Forensics in NS2
To implement Refined Network Forensics in NS2, we aim to enhance the detection, logging, and assess of network activities with higher accuracy and granularity. Refined forensics usually contain more detailed tracking of packet behaviours, deeper understandings into attack patterns, and automated event correlation for better learning of the network security posture.
This procedure delivers step-by-step instructions on how to execute Refined Network Forensics in NS2.
Step-by-Step Implementation:
- Set up NS2
Make sure NS2 is installed on system. If not, install it using:
sudo apt-get install ns2
- Define the Network Topology
Generate a simple network topology in which refined forensic monitoring can be executed. We contain nodes for sending, receiving, attacking, and monitoring.
Example:
set ns [new Simulator]
set tracefile [open refine_forensics.tr w]
$ns trace-all $tracefile
# Create nodes
set n1 [$ns node] ;# Sender node
set n2 [$ns node] ;# Receiver node
set nAttacker [$ns node] ;# Attacker node
set nForensics [$ns node] ;# Forensic node
# Create links between the nodes
$ns duplex-link $n1 $n2 1Mb 10ms DropTail
$ns duplex-link $nAttacker $n2 1Mb 10ms DropTail
$ns duplex-link $nForensics $n2 1Mb 10ms DropTail
- Set Up Traffic and Attack Simulation
Configure normal traffic among n1 and n2, and mimic attacks from nAttacker. These events will be logged and measured by the forensic node (nForensics).
(A) Set up Normal Traffic
Generate UDP traffic from n1 to n2.
# Set up UDP traffic between n1 and n2
set udp1 [new Agent/UDP]
set null1 [new Agent/Null]
$ns attach-agent $n1 $udp1
$ns attach-agent $n2 $null1
$ns connect $udp1 $null1
# Create CBR (Constant Bit Rate) traffic generator
set cbr1 [new Application/Traffic/CBR]
$cbr1 set packetSize_ 512
$cbr1 set rate_ 1Mb
$cbr1 attach-agent $udp1
# Start normal traffic at 1.0 second
$ns at 1.0 “$cbr1 start”
(B) Simulate an Attack (DDoS or Packet Injection)
Set up a malicious attack from nAttacker to flood n2 with traffic.
# Set up DDoS traffic from the attacker node
set udpAttacker [new Agent/UDP]
set cbrAttacker [new Application/Traffic/CBR]
$cbrAttacker set packetSize_ 512
$cbrAttacker set rate_ 5Mb ;# High rate to simulate attack
$cbrAttacker attach-agent $udpAttacker
# Connect attacker to the receiver node
$ns attach-agent $nAttacker $udpAttacker
$ns connect $udpAttacker $null1
# Start the attack at 2.0 seconds
$ns at 2.0 “$cbrAttacker start”
- Enhanced Packet Logging for Forensic Analysis
For refined forensics, we need to capture detailed information about each packet. This contains:
- Source/Destination IPs
- Packet size
- Timestamp
- Hop count
- Payload details (if necessary)
(A) Log Traffic with Detailed Information
Generate a function that logs detailed data for each packet, that has packet metadata and event-specific details.
# Function to log packet details for forensic analysis
proc log_packet_forensics {packet_id source dest size time hop_count payload} {
puts “Forensics: Packet $packet_id: Source=$source, Dest=$dest, Size=$size, Time=$time, Hops=$hop_count, Payload=$payload”
}
# Simulate logging of traffic at the forensic node
proc monitor_traffic {packet_id source dest size time hop_count payload} {
log_packet_forensics $packet_id $source $dest $size $time $hop_count $payload
}
# Capture and log traffic for forensic analysis
$ns at 1.5 “monitor_traffic 1 n1 n2 512 1.5 2 ‘Normal data'”
$ns at 2.5 “monitor_traffic 2 nAttacker n2 512 2.5 2 ‘Attack traffic'”
(B) Store Logs in a File for Offline Analysis
Record packet logs in a file for detailed post-simulation analysis.
# Open a file to store forensic logs
set forensic_log [open refine_forensics_log.txt w]
# Log packet details to the forensic log file
proc log_to_file {packet_id source dest size time hop_count payload} {
global forensic_log
puts $forensic_log “Packet $packet_id: Source=$source, Dest=$dest, Size=$size, Time=$time, Hops=$hop_count, Payload=$payload”
}
# Log packet traffic to the file
$ns at 1.5 “log_to_file 1 n1 n2 512 1.5 2 ‘Normal data'”
$ns at 2.5 “log_to_file 2 nAttacker n2 512 2.5 2 ‘Attack traffic'”
- Correlate Events for Forensic Analysis
Refined forensics needs the ability to relate multiple events and classify patterns of attacks. This can contain looking for traffic anomalies, repeated patterns, or unusual packet sizes.
(A) Automated Event Correlation
We can build a function that system relates multiple events and logs findings.
# Function to correlate events for forensic analysis
proc correlate_events {packet_id source dest size time payload} {
if { $size > 512 } {
puts “Anomaly detected in packet $packet_id: Abnormal packet size from $source to $dest”
}
if { [regexp “Attack” $payload] } {
puts “Possible attack detected in packet $packet_id”
}
}
# Correlate traffic events
$ns at 1.5 “correlate_events 1 n1 n2 512 1.5 ‘Normal data'”
$ns at 2.5 “correlate_events 2 nAttacker n2 1024 2.5 ‘Attack traffic'”
(B) Forensic Anomaly Detection
Establish a function that flags anomalies according preset thresholds such as high traffic rate, unusual packet sizes, unexpected sources.
# Function to detect anomalies in traffic
proc detect_anomalies {source dest size time rate} {
if { $size > 512 || $rate > 5 } {
puts “Anomaly detected: Large packet size or high traffic rate from $source to $dest”
}
}
# Detect anomalies in traffic
$ns at 1.5 “detect_anomalies n1 n2 512 1.5 1”
$ns at 2.5 “detect_anomalies nAttacker n2 1024 2.5 10”
- Simulate Forensic Investigation
Mimic a post-incident investigation in which logs are evaluated to trace the attack’s origin and impact.
(A) Reconstruct Events from Logs
After logging traffic, reconstruct events to envision the attack’s flow and origin.
# Function to reconstruct forensic events
proc reconstruct_forensic_events {file} {
puts “Reconstructing forensic events…”
set logfile [open $file r]
while {[gets $logfile line] >= 0} {
if {[regexp “Attack” $line]} {
puts “Attack detected: $line”
}
}
close $logfile
}
# Reconstruct events after the simulation
$ns at 5.0 “reconstruct_forensic_events refine_forensics_log.txt”
(B) Replay Traffic for Deeper Analysis
Replay recorded traffic to further examines the incident and check detection.
# Function to replay logged traffic
proc replay_traffic {packet_id source dest size time} {
puts “Replaying packet $packet_id from $source to $dest with size $size at $time”
# Simulate replay of captured traffic
}
# Replay captured traffic for forensic analysis
$ns at 5.5 “replay_traffic 1 n1 n2 512 1.5”
$ns at 6.0 “replay_traffic 2 nAttacker n2 1024 2.5”
- Run the Simulation
Once script is ready, execute the simulation in NS2:
ns your_script.tcl
- Analyse Results
After the simulation completes, evaluate the forensic logs (refine_forensics_log.txt). Validate for:
- Anomalies and suspicious patterns.
- Attack events that contain timestamps, sources, and impact.
- Event correlations for deeper insights.
We can also use NAM (Network Animator) to envision network activity and the progression of attacks.
- Extend the Simulation
We can expand this execution by:
- Adding different attack types: To contain more attacks such as spoofing, replay attacks, and man-in-the-middle.
- Implementing advanced anomaly detection: Use statistical models or machine learning to identify complex patterns.
- Incorporating encryption and decryption: Mimic encrypted traffic to make attacks more sophisticated.
- Using more detailed forensic logging: To contain payload inspection, checksum verification, and hop-by-hop tracking.
Within this module, we presented the entire demonstration about how to replicate the scenario and analyse the performance regarding the Refined Network Forensics in the tool of ns2. To implement Network Refine Forensics in the NS2 tool, please provide us with your requirements, and we will ensure timely results. We invite you to share your specific needs, enabling our team to perform a comprehensive network comparative analysis customized for your research objectives. Our developers will assist you with attack patterns and automated event correlation relevant to your projects.