Cyber-attackers, whether criminals, terrorists, or threat actors, often hide behind well-laid, anonymous trails on the internet to cover their tracks and keep their digital footprints close to zero.

Cybercrime is devastating for victims, regardless if they are individuals, companies, or government organizations. Finding out who lies behind the attacks is crucial to take action against the threat actors and to prevent future episodes.

This process is known as cyber attribution, the process of tracking, identifying and holding the threat actor(s) behind a cyberattack or other hacking exploit responsible.

Why Is Cyber Attribution Important?

Cyber attribution is a complicated process since threat actors must be identified, their activities have to be traced, and their affiliation with certain groups detected.

These activities will all aid cyber investigators and analysts in mapping behavior patterns to get insights into their motivation, potential targets and victims, business models, and conducted and planned cyberattacks.

Since most of their activities and communications take place online, threat actors use the internet, specifically the dark web, to remain anonymous and hide their tracks.

This can result in investigators and analysts processing vast amounts of web data from the surface, deep, and dark web to attribute the cyberattacks with a high degree of certainty with limited resources and budgets.

Since threat actors operate across borders and know how to raise false flags by casting suspicion on other actors, an AI-powered WEBINT platform is needed that is easy to use and can handle the quantity and quality of data required for evidence to ensure the integrity of the investigative process.

Innovative Platforms

Cyber forensics software featuring a WEBINT platform will most certainly play a crucial role in cyber attribution. One platform enables investigators and analysts to collect, analyze, and extract public data on all web layers, message boards, and other platforms relating to a cyberattack automatically to provide executable insights.

It also enables analysts and investigators to search for specific threat actors and keywords to investigate online forums and marketplaces on the dark web where threat actors and persons of interest might hide.

One of the best innovations today, the platform utilizes sophisticated machine-learning algorithms and AI to analyze the collected data to de-anonymize the threat actors behind the cyberattack.

The best software functions will feature Natural Language Processing (NL) algorithms for AI text and entities analyses in minutes; AI sentiment analysis, which enables investigators to determine potential cyberattacks by gaining insights into the sentiment of each instance and communication; and a tool which consists of the transformation of unstructured data into structured data that can easily be sorted through.

With a host of other features, such as AI image analysis, trends search and machine learning algorithms to improve AI capabilities, investigators can deliver faster and more reliable results.

It enables investigators to work in real-time regarding certain malicious activities, threat actors, and their social and business networks to prevent cyberattacks and related activities.

Evolving software is now becoming more advanced, enabling investigators to be on the front and to pursue threat actors, and reveal their true identifies.