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Network forensics

Network forensics is the process of identifying, capturing, and preserving volatile data transmitted across a network to reconstruct events, establish timelines, and uncover actionable digital evidence.

The scope of network forensics encompasses the monitoring, interception, and analysis of network traffic across internal and external boundaries to identify security anomalies, trace policy violations, and reconstruct information security incidents. This operational domain extends from localized local area network (LAN) activity and wide area network (WAN) perimeters to virtualized cloud environments and software-defined networks. Rather than focusing on static storage media, investigators target data in motion using two primary methodologies:

  • Deep-Analysis Systems: Utilize Full Packet Capture (FPC) and Deep Packet Inspection (DPI) to record every byte passing through a network monitoring point (via TAPs or SPAN ports), allowing investigators to reconstruct entire transmissions down to the application layer.
  • Flow-Based Systems: Aggregate traffic into compact, structured metadata records based on a unique "5-tuple" identity (Source/Destination IP, Source/Destination Port, and Protocol) to provide long-term behavioral visibility without inspecting payload contents.

By combining these packet-level and flow-level capture capabilities with the evaluation of network device logs (such as firewall and IDS records), advanced hybrid systems establish an authenticated, end-to-end timeline of how an attacker accessed, navigated, and exfiltrated data from an enterprise ecosystem.

Categories of Analysis

The analysis of captured network data is commonly broken down into the following categories:

  • Session reconstruction - Rebuilding complete user sessions by recovering application-layer content (files, email, web pages) from captured packets; see also Session reconstruction.
  • Flow-based analysis - Examining compact 5-tuple records (volume, duration, timing) to find unusual peers, tunneling, exfiltration, and beaconing patterns; see also Flow-based analysis.
  • Intrusion and anomaly detection - Matching traffic against signature rules or behavioral baselines to identify attacks and malware; see also Intrusion detection.
  • Data leakage analysis - Combining flow volumes with inspection of unencrypted payloads and DNS queries to identify sensitive data leaving the network.
  • DNS analysis - Inspecting queries and responses for tunneling, domain generation algorithms, and indicators of compromise.
  • Wireless and Radio Frequency (RF) analysis - Analysis of 802.11 and other radio-based traffic; see also Wireless forensics.
  • TLS/SSL analysis - Examining handshake and certificate metadata, or the payload when keys are available; see also SSL forensics.
  • Geolocation and path analysis - Using TTL values, traceroutes, and address data to map routes; see also IP geolocation.
  • Timeline correlation - Aligning network events with host and log evidence to build an end-to-end incident timeline; see also Timeline analysis and Logfile analysis.

See also