Network Forensic analysis is a sub-domain in the broad spectrum of digital forensics used for retrospective analysis of networks to find pieces of evidence left behind following a cyberattack. It analyses network traffic to gather the information that could connect security teams to the threat actor, find vulnerabilities exploited to enter the network and so on.
Network forensics analysis can be accomplished in two ways. The first is “catch it as you can” strategy, which entails recording all network traffic for analysis. This methodology requires a lot of storage so as to store previous data for future forensics.
The “stop, look and listen” strategy entails analysing each data packet travelling across the network and only collecting what is judged suspicious and worthy of further investigation; this approach can demand a lot of processing power but requires less storage space.
Analyzing the events, leading up to an attack, in great detail not only helps organizations to understand their vulnerabilities but also helps prevent future attacks by aiding in developing a robust threat hunting and response mechanism enabling cyber situational awareness.
To facilitate optimum Network Forensic analysis, various tools are at the disposal of security teams that analyse North-South and East-West network traffic to its granular details for conducting network audits, comprehending network transactions, usage of protocols and applications.
Following the analysis of network traffic, these tools transform the raw data into a human-readable format that projects individual details of each transaction like source IP, destination IP, packet count, MAC address, etc to identify the intrusion path undertaken by the threat and other details.
Network forensics tools help safeguard networks from both subtle and malicious security attacks. They help an organization gain deep insight into its network environment and prevent data breaches that could cost them money, a competitive advantage, or both. Having a thorough record of network activity can be quite useful when dealing with a variety of technical, operational, and organisational difficulties.
Vehere’s Artificial Intelligence-powered and Machine Learning-enabled PacketWorker is the leading network forensic tool with a built-in content management system to ease analysis and eliminate dependence on third-party software. It delivers an improved value while conducting the investigation or threat analysis.
Network forensic investigations centre around evidence collecting, indexing and analysis. Investigators must rely on effective technologies to retrieve data and aid in analysis.
Investigators and cybercrime professionals use network forensics to track down all network transactions and build timelines based on network events logs.