The recent success of the Kerala Police in solving a decades-old cold case using AI shows how artificial intelligence is empowering law enforcement. As Stephen Kavanagh, Interpol’s Executive Director of Police Services, aptly noted, “AI allows investigators to 'process vast amounts of data in minutes, not months.’

A key area where this transformation takes place is analysing a suspect’s digital pattern of life. By rapidly decoding and correlating massive volumes of PCAP data, AI tools help uncover how individuals interact online, turning scattered digital data into actionable intelligence.

What Is a Digital Pattern of Life?

A digital pattern of life refers to a behavioural map created by tracking an individual’s daily interactions with digital systems, from app usage and web browsing to communication patterns and access timing.

These patterns help investigators answer critical questions:

• What digital platforms does a suspect use regularly?
• When and how often are they active?
• Are there any deviations that point to suspicious behaviour?

With the help of AI, these seemingly ordinary data points become clues that reveal intent, associations, and movements without needing to decrypt encrypted data.

For example, imagine an investigation where two suspects seem unrelated. By analysing PCAP data, investigators discover that users access encrypted apps, Tor, and VPNs at similar times, often late at night.

Their synchronised digital behaviour, repeated over the days, reveals a coordinated pattern. These anomalies, which surfaced through AI-powered patterns of life analysis, help law enforcement connect the dots and build a case from invisible digital trails.

How AI Builds Patterns of Life from PCAP

PCAP files contain data travelling over a network. These files can reveal device communication, timestamps, protocols, domains accessed, and more. AI uses this data to reconstruct timelines and behaviours.

Here’s how the process unfolds:

Behavioral Analysis

AI examines how individuals interact with digital platforms by analysing:

• Web browsing habits
• Messaging patterns
• App usage trends
• Social media activity

This builds a baseline for each suspect's “normal” looks.

Timeline and Frequency

When does the person go online? Is their behaviour consistent? AI tracks the frequency and timing of activities to detect irregularities that could indicate operational shifts or planning.

Comprehensive Profiling

Solutions like CARBN.AI™ leverage deep packet inspection to create 360-degree digital profiles. This includes data from both clear-text and encrypted traffic, helping analysts trace hidden connections and behaviours.

With CARBN.AI™, agencies can quickly extract behavioural insights from raw PCAP.

Anomaly Detection

Once a pattern is established, AI detects deviations such as:

• Sudden use of anonymisers or VPNs
• Accessing new or suspicious domains
• Changes in communication volume or format

Such anomalies often serve as early warning signals for potential criminal activity.

Why Pattern of Life Matters

The pattern of life analysis enables agencies to move from data overload to decision-making. It connects the dots in real-time, helping analysts answer:

• Is the suspect acting alone or in a group?
• Are they preparing for coordinated action?
• Are there digital trails leading to other individuals or entities?

Final Thought

In an era where criminals leave digital traces rather than physical ones, the ability to understand and interpret online behaviour is paramount. AI-driven pattern-of-life analysis transforms raw, overwhelming network data into meaningful, actionable intelligence.