How to Implement Network Multi Attacks Detection in NS2
To implement the Network Multi-Attack Detection in NS2, We have to simulate various kinds of attacks include DDoS attacks, packet injection, replay attacks and others. This system will observe network traffic for several attack patterns and react with proper mitigation strategies. In the following below, we provide the instructions to accomplish this in ns2:
Step-by-Step Implementation:
- Set Up NS2
Make sure that NS2 is installed on your system. If it is not installed, you can install it by executing:
sudo apt-get install ns2
- Define the Network Topology
We will configure a basic network topology in which the attacks can be replicated and IDS node can observe the traffic and identify attacks.
Example topology:
set ns [new Simulator]
set tracefile [open multi_attack_detection.tr w]
$ns trace-all $tracefile
# Create nodes
set n1 [$ns node] ;# Normal node (Sender)
set n2 [$ns node] ;# Normal node (Receiver)
set nMalicious [$ns node] ;# Malicious node (Attacker)
set nIDS [$ns node] ;# Intrusion Detection System (IDS)
# Create links between nodes
$ns duplex-link $n1 $n2 1Mb 10ms DropTail
$ns duplex-link $nMalicious $n2 1Mb 10ms DropTail
$ns duplex-link $nIDS $n2 1Mb 10ms DropTail
- Simulate Normal Traffic
Design a flow of normal traffic amongst n1 (sender) and n2 (receiver). The IDS node (nIDS) will see the traffic amongst these nodes.
# 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 attached to UDP
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”
- Simulate Multiple Types of Attacks
Launch numerous variants of attacks from the malicious node (nMalicious) to imitate multi-attack detection.
(A) DDoS Attack Simulation (Traffic Flooding)
Simulate a Distributed Denial of Service (DDoS) attack by producing the malicious node delivering an abnormally high volume of traffic to the receiver.
# Set up a DDoS traffic flood attack from the malicious node
set udpMalicious [new Agent/UDP]
set cbrMalicious [new Application/Traffic/CBR]
$cbrMalicious set packetSize_ 512
$cbrMalicious set rate_ 10Mb ;# High rate for DDoS
$cbrMalicious attach-agent $udpMalicious
# Attach malicious node to the network and send attack traffic
$ns attach-agent $nMalicious $udpMalicious
$ns connect $udpMalicious $null1
# Start DDoS attack at 2.0 seconds
$ns at 2.0 “$cbrMalicious start”
(B) Packet Injection Attack Simulation
Simulate a Packet Injection attack where the malevolent node inserts illegitimate packets into the network.
# Function to simulate packet injection
proc inject_packet {source dest size time} {
puts “Packet injected by malicious node from $source to $dest at $time”
}
# Inject malicious packets at 2.5 seconds
$ns at 2.5 “inject_packet nMalicious n2 512 2.5”
(C) Replay Attack Simulation
In a Replay Attack, the malicious node seizes packets and sends them again to the receiver.
# Function to simulate replay attack (resending captured packets)
proc replay_attack {source dest size time} {
puts “Replay attack: Resending captured packet from $source to $dest at $time”
}
# Simulate replay attack at 3.0 seconds
$ns at 3.0 “replay_attack nMalicious n2 512 3.0”
- Implement Multi-Attack Detection in the IDS Node
The IDS node (nIDS) will observe traffic and spot different types of attacks using traffic pattern analysis. Detection rules will encompass:
- DDoS Detection: Abnormally high traffic volume or rate.
- Packet Injection Detection: Packets from unauthorized sources.
- Replay Attack Detection: Duplicate packets within a short time window.
(A) Traffic Monitoring Function
Develop a function to monitor traffic patterns and identify anomalies based on thresholds for traffic volume, rate, or illegal packet sources.
# Variables to track traffic statistics
set pkt_count 0
set ddos_threshold 1000 ;# Set a threshold for DDoS detection
set last_pkt_time 0
set replay_threshold 0.1 ;# Threshold for replay detection (time window)
# Function to monitor traffic for multi-attack detection
proc monitor_traffic {source dest size time} {
global pkt_count ddos_threshold last_pkt_time replay_threshold
# Increment packet count
incr pkt_count
# Check for DDoS attack (high traffic volume)
if { $pkt_count > $ddos_threshold } {
puts “DDoS attack detected from $source to $dest”
return 1 ;# DDoS detected
}
# Check for replay attack (duplicate packets within short time window)
set inter_arrival_time [expr $time – $last_pkt_time]
set last_pkt_time $time
if { $inter_arrival_time < $replay_threshold } {
puts “Replay attack detected from $source to $dest”
return 2 ;# Replay attack detected
}
# Check for packet injection (unauthorized source)
if { $source == “nMalicious” } {
puts “Packet injection detected from $source to $dest”
return 3 ;# Packet injection detected
}
return 0 ;# No attack detected
}
(B) Simulate Traffic Monitoring at the IDS Node
The IDS node will seize the packets and establish the detection rules to monitor for DDoS, packet injection, and replay attacks.
# Function to simulate IDS capturing packets and detecting attacks
proc capture_packet {source dest size time} {
puts “Packet captured by IDS: Source=$source Dest=$dest Size=$size Time=$time”
set attack_type [monitor_traffic $source $dest $size $time]
if { $attack_type == 1 } {
puts “DDoS attack mitigation triggered”
# Add DDoS mitigation actions (e.g., block the malicious node)
} elseif { $attack_type == 2 } {
puts “Replay attack mitigation triggered”
# Add replay attack mitigation actions
} elseif { $attack_type == 3 } {
puts “Packet injection mitigation triggered”
# Add packet injection mitigation actions
}
}
# Capture traffic at the IDS node and apply detection rules
$ns at 1.5 “capture_packet n1 n2 512 1.5”
$ns at 2.0 “capture_packet nMalicious n2 512 2.0”
- Implement Mitigation Actions
Once an attack is detected, the IDS node can activate mitigation actions include throttling the traffic, congesting the malicious node, or sending alerts.
(A) Mitigation: Throttling Traffic
The IDS can decrease the traffic rate from the malicious node if a DDoS attack is identified.
# Function to throttle traffic from a node
proc throttle_traffic {node new_rate} {
puts “Throttling traffic from $node to $new_rate”
$node set rate_ $new_rate ;# Reduce traffic rate
}
# Trigger traffic throttling if DDoS is detected
$ns at 2.5 “throttle_traffic $cbrMalicious 512kb”
(B) Mitigation: Blocking Malicious Nodes
The IDS can block the malicious node from interacting further by detaching it from the network.
# Function to block a node from communicating
proc block_node {node} {
puts “Blocking traffic from $node”
$ns detach-agent $node ;# Detach the malicious node from the network
}
# Trigger block if packet injection is detected
$ns at 3.5 “block_node nMalicious”
- Run the Simulation
Save your Tcl script and execution the simulation using NS2:
ns your_script.tcl
- Analyze Results
After the simulation, inspect the trace file (multi_attack_detection.tr) to assess how the IDS node monitored traffic and spotted various kinds of attacks. You can also use NAM (Network Animator) to visualize the network and see the detection and mitigation process.
- Extend the Simulation
You can extend this implementation by:
- Attaching more attack types like man-in-the-middle or eavesdropping attacks.
- Incorporating machine learning models for dynamic behavioral detection.
- Executing multi-layered defense, where various network layers (application, transport and so on) has several detection systems.
- Assessing detection accuracy by investigating against various traffic patterns and comparing false positives/negatives.
This guide will walk you through the implementation of a system that identifies numerous kinds of attacks with the help of behavioral analysis or rule-based detection by establishing Intrusion Detection System (IDS) to monitor the traffic in the ns2 environment. Our developers is prepared to assist you with DDoS attacks, packet injection, replay attacks, and various other aspects relevant to your projects, ensuring prompt implementation support throughout the process. For exceptional project ideas related to Network Multi Attacks Detection that are customized to your research focus, visit ns2project.com and share your specific requirements with us.