Network Forensics

Network Forensics: Concepts and Challenges

Network forensic is a branch of digital forensic analysis that involves monitoring, capturing, recording and analysing data over a network. Network forensics involves scientifically proven and tested methods to collect and analyse network packages and events that take place over a network. Forensic network analysis is extensive network security that traditionally focuses on network attack analysis and detection. The current model of network forensics allows detection of malicious activity and it also helps the organisations to track attacks related to the organisations from both internal and external environments. This post highlights the concepts and challenges of network forensics. Understanding the current challenges helps the investigators to make a well-informed decision in case of difficulty.

Network forensic concepts

In terms of forensics, network forensic deals with data associated with a network connection between nodes that are interconnected. The main focus is the data entering and exiting the nodes. The forensic network analyser performs a thorough analysis of the data from the data traffic that has been generated by respective firewalls or IDS or on devices such as routers. The primary goal is to find the source of the attack to identify the cybercriminals.

The network security forensics is precisely defined as the use of scientifically tested and proven methods to perform various functions such as collect, identify, examine, correlate, analyse and document digital evidence from various sources. The process is done to discover facts about the planned intention of unauthorized persons who carry out activities that aim at interrupting, corrupting or compromising system components. The network forensic is also done to provide information that is used to assist in the response or recovery of the intervening activities.

Network analysis comprises reform and analysis of computer networks linked to unauthorized access. The main purpose is to allow the specialist to understand the reason for the current circumstances of the investigated activity and present the evidence collected before the court.

The process is characterized by functions like detection; recognition and assigning the responsibilities to investigate attacks. The investigations done in a network forensics and security allows the forensic investigator to determine the following:

  • Who is to be blamed for the action?
  • What exactly has the attacker do?
  • When is the likely time for the next event?
  • Where is the node of attack located?
  • Why did the crime take place?
  • How did the crime take place? (vulnerability sources are detected)


The first challenge in forensic network analysis is to make sure that the network is adequate to the needs of the forensic investigator. For successful and efficient investigation it must be equipped with the required infrastructures. Some of the common challenges that interfere with infrastructure designing are as follows:

  • Data sources
  • Granularity in the data
  • Data integrity
  • Privacy issues
  • Data analysis

A powerful tool such as the Network Miner can overcome the challenges and leverage network forensic processes in an agency or organisation.

Network Miner

The Network Miner is a multi-pronged forensic analysis tool based on open source mainly for Windows. The tool can also be used as a passive network sniffer tool to identify the OS, sessions, hostnames, open ports etc.

The network miner makes it simple and facile for advanced traffic network analysis by offering extracted artefacts in a powerful interface.


  • Live sniffing
  • Parse PCAP files
  • IPv6 support
  • Runs in Windows and Linux
  • OS Fingerprinting
  • Extract files from FTP, HTTP/2, SMB, SMB2, SMTP, POP3, IMAP traffic and other traffic.

Bottom lines

Network analysis is crucial to protect the existing network system. Pelorus as one of the top-grossing forensic solution providers of India, offers the best Network analysis. Get your hands on the latest model after experiencing the demo.

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