Network Forensics projects examples using omnet++

Network forensics has encompasses observing, capturing, analysing, and reporting on network traffic to find security breaches, cyber-attacks, or other malicious activities. We can mimic numerous network forensics scenarios to learn how forensic investigations can be conducted in a network environment by using OMNeT++,. The following are certain instances of network forensics projects that can be executed using OMNeT++:

Packet Capture and Analysis for Forensic Investigation

Objective: Mimic the capture and analysis of network packets to find potential security breaches or malicious activities.
Implementation: Create a network where traffic is generated among numerous nodes. Execute a packet capture module that logs all traffic for later analysis. Use these module to classify abnormal traffic patterns, like unusually large packets, unexpected IP addresses, or unusual port usage.
Extension: Improve a system that automatically flags suspicious packets for closer inspection and makes a forensic report specifying the nature of the potential threat.

Forensic Analysis of a Distributed Denial of Service (DDoS) Attack

Objective: Feign a DDoS attack on a network and execute forensic analysis to follow the attack’s origin and know its impact.
Implementation: Make a network where several attacker nodes create excessive traffic to overcome a target server. Encapsulate network traffic via the attack and evaluate it to find the source IP addresses, attack patterns, and the kind of DDoS attack used.
Extension: Execute methods to relate traffic data across various network segments to classify coordinated attacks, and use the gathered data to reconstruct the attack timeline.

Intrusion Detection and Forensic Response

Objective: Feign an intrusion detection system (IDS) that not only identifies potential intrusions but also begins forensic data collection for post-attack analysis.
Implementation: Generate a network with an IDS that observes traffic in real-time. While an intrusion is identified like through a signature-based or anomaly-based detection system, the IDS triggers forensic modules to get related traffic, logs, and system states for further analysis.
Extension: Improve a system that automatically creates a described forensic report after an intrusion, with a timeline of events, affected systems, and potential vulnerabilities consumed by the attacker.

Reconstruction of Network Attacks from Log Files

Objective: Feign a scenario where network logs are used to rebuild the sequence of events through a cyberattack.
Implementation: Execute logging mechanisms in network devices like routers, firewalls, and servers. In a simulated attack, such as a brute-force login attempt or data exfiltration, logs are gathered from these devices. Use forensic tools to consider the logs and reconstruct the attack timeline, finding the entry point, attack method, and affected systems.
Extension: Mimic scenarios where attackers attempt to interfere with logs to cover their tracks. Advance approaches to identify log manipulation and reinstate original logs for exact forensic analysis.

Forensic Analysis of Malware Propagation in a Network

Objective: Feign the spread of malware in a network and execute forensic analysis to track its propagation path and find compromised systems.
Implementation: Generate a network where a malware infection begins from a single node and spreads to other nodes through general infection vectors such as email attachments, file sharing, or network vulnerabilities. Encapsulate network traffic and system logs to examine the malware’s propagation and detect patient zero (the first infected node).
Extension: Execute tools to evaluate the malware’s behaviour, like sandboxing or dynamic analysis, and relate the discoveries with the network forensics data to know the complete impact of the attack.

Steganography Detection in Network Traffic

Objective: Emulate network traffic encompassing steganographic data and make forensic analysis to identify hidden messages.
Implementation: Form a network where some nodes use steganography to hide data in network traffic, like in packet headers, payloads, or timing intervals. Execute steganalysis tools that consider traffic patterns, packet sizes, and timing anomalies to discover the presence of hidden data.
Extension: Improve techniques to get and evaluate the hidden data once it is identified, and generate a forensic report describing the detection process and the content of the hidden messages.

Forensic Analysis of Insider Threats

Objective: Mimic a scenario where an insider misuses their privileges to access and exfiltrate sensitive data, and execute forensic analysis to track their activities.
Implementation: Generate a network where an insider with legitimate access attempts to exfiltrate data or sabotage systems. Execute observing and logging mechanisms to follow the insider’s activities, containing file access logs, command history, and network traffic. Execute forensic analysis to detect the insider’s actions and compile evidence.
Extension: Enhance a behavioural analysis system that observes user activities over time and flags deviations from typical behaviour as potential insider threats. Assess the system’s efficiency in discovering and reacting to insider threats in real-time.

Forensic Analysis of Wireless Network Attacks

Objective: Emulate attacks on a wireless network, like rogue access points, deauthentication attacks, or eavesdropping, and execute forensic analysis to detect the attacker and measure the damage.
Implementation: Create a wireless network with several nodes, containing access points and client devices. Feign many wireless attacks and take network traffic and logs through the attack. Evaluate the captured data to trace the attacker’s location, find the method used, and determine the extent of the attack.
Extension: Execute detection tools that examine signal strength, MAC address spoofing, and wireless traffic anomalies to discover and mitigate wireless attacks. Liken the efficiency of various forensic methods in finding and reacting to wireless threats.

Forensic Recovery of Deleted Network Data

Objective: Feign a scenario where network data is deliberately removed by an attacker to cover their tracks, and do forensic analysis to recover the deleted data.
Implementation: Execute a network where an attacker attempts to delete logs, files, or other crucial data to hide their activities. Use forensic recovery methods, like data carving or file system analysis, to recover the deleted data. Investigate the recovered data to recreate the attack and detect the attacker.
Extension: Discover advanced data wiping methods used by attackers and improve approaches to counteract these techniques, make sure that crucial forensic evidence can still be recovered.

Forensic Analysis of Phishing Attacks

Objective: Mimic a phishing attack on a network where users are tricked into giving sensitive information, and execute forensic analysis to follow the phishing attempt and mitigate its effects.
Implementation: Construct a network where users receive phishing emails or visit phishing websites. Capture network traffic and analyze email headers, website logs, and user interactions to trace the source of the phishing attempt and identify compromised accounts or data.
Extension: Ripen automated tools that evaluate incoming emails or website traffic for phishing indicators, like suspicious URLs, spoofed email addresses, or abnormal user behavior. Execute a system to alert users and network administrators to possible phishing attempts in real-time.

Network Forensic Analysis of Ransomware Attacks

Objective: Mimic a ransomware attack within a network and execute forensic analysis to trace the origin, propagation, and impact of the ransomware.
Implementation: Make a network where ransomware is presented through a compromised email attachment or a vulnerable service. Take network traffic, file access logs, and system events via the ransomware attack. Act forensic analysis to find the initial infection vector, the encryption method used, and the systems affected.
Extension: Emulate various ransomware variants with several propagation techniques, like worm-like behaviour or lateral movement in the network. Improve tools to discover early signs of a ransomware attack and make forensic reports describing the attack’s progression and impact.

Network Forensics for IoT Devices

Objective: Feign a scenario encompassing compromised IoT devices in a network and execute forensic analysis to detect how the devices were breached and what actions were taken by the attacker.
Implementation: Form a network with several IoT devices interactive with a central server. Mimic an attack that compromises one or more IoT devices, like a botnet formation or unauthorized access. Take network traffic and device logs to evaluate the attack’s origin, method, and impact on the IoT network.
Extension: Enhance forensic tools specifically tailored to IoT environments, considering the limited resources and single communication patterns of IoT devices. Assess the challenges of execution forensic analysis on IoT devices and propose solutions to increase data collection and analysis in such environments.

Network Forensics in Cloud Environments

Objective: Mimic a cloud-based network environment and complete forensic analysis to examine security incidents, like data breaches, VM compromise, or inter-tenant attacks.
Implementation: Execute a cloud network with several virtual machines (VMs) and tenants. Feign a security incident, like unauthorized access to a VM or data exfiltration among tenants. Encapsulate network traffic, VM logs, and cloud management data to follow the incident and find the attacker.
Extension: Improve forensic methods that address the challenges of cloud environments, like multi-tenancy, data privacy, and dynamic resource allocation. Emulate various cloud attack scenarios and estimate the efficiency of forensic tools in cloud-based investigations.

We had demonstrate the approaches and some examples are supports to execute the network Forensics Projects using the tool OMNeT ++. If you needed, we will offer more details regarding this topic.

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