Executive summary

The rise of ransomware as a cybersecurity threat is nothing short of spectacular.

From its almost insignificant creation at least three decades ago to the present day, Ransomware has become the most widespread and profitable attack, so much so that it is also "offered" today as a service.

Current ways of detecting ransomware attacks use static analysis techniques that prove inadequate to intercept the sophistication of the new digital crime.

This white paper describes how to leverage new dynamic, machine-learning-based behavioural analytics techniques to intercept these attacks well before the final "too late; the damage is done" stage.

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Ransomware in layman's terms

Ransomware is a type of malicious software (malware) that, once executed, prevents the user from using the computer or its data, asking for a sum of money to restore it.

Currently, ransomware attacks deploy in three different ways:

1. By blocking access to the device (locker ransomware);
2. Making user data unusable through the use of cryptographic algorithms (crypto-ransomware)
3. A combination of locker and crypto-ransomware prevents users from using their computers while their data is encrypted.

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