The protection of data should be a priority for all organisations, however, the increase in cyber and ransomware attacks over the past two years has meant that now, more than ever, our data has never been at greater risk. In fact, 80 percent of ransomware attacks involves data exfiltration. This could be customer data, employee information, patient data, intellectual property or financial information- the list goes on. It also doesn’t end with the one attack. Often, the data stolen in a ransomware attack is used in a double extortion whereby the attackers not only steal the data, but then threaten to publish it online for other cyber criminals to use in further attacks. They can also demand ransom from the victim’s clients or suppliers, making it a triple extortion. There is no end to how attackers will use our data in a ransom attack.

Ransomware is a genuine threat to all organisations and with the attack method being so prolific in its exfiltration of data, organisations need to look at what more they can do to protect their customers from being the target of an attack and having their valuable and personal information stolen.

All too often, we are taught the best way to respond to a cyber attack is to mitigate it. By doing this, we are settling for the scenario that the attacker has already entered the network and is looking to deploy malware, or launch a ransomware attack and steal data. By this time of course, it is already too late and the damage may well have been done. It also becomes much harder for security teams to work out what the attacker has accessed and infected in order to respond to, and mitigate the damage caused.

Fortunately, there is a way in which organisations can guarantee that their data is secure from ransomware and other cyber attacks, but in order to ensure protection, they need to shift their mindset from mitigation to prevention.

Organisations can do this by implementing deep learning. Deep learning learns in a much more complex way than traditional systems like machine learning (ML) via a deep neural network inspired by the human brain. The neural network is left to process large quantities of raw, unlabelled data which it then determines as malicious or benign. Because deep learning tools learn independently, they can process vast amounts of data compared to traditional ML tools that require manual input.

As a result, the technology is not only able to accurately identify more complex patterns than traditional ML, but it operates at exponentially higher speeds. The bleeding edge of the technology can detect and block malware in just 20 milliseconds. At this speed, we effectively move from prevention to prediction as attacks are stopped before they can truly begin.

With complete preventative options available, businesses who choose to stick with mitigation solutions are providing attackers with the opportunity to gain access to their customer’s data which can be used in further attacks or held hostage in a ransom attack. We have witnessed a somewhat terrifying growth in cyber attacks in the past couple of years and trying to find a solution to stopping them can feel hopeless. However, with a shift in mindset and a recognition that in fact there are solutions that can completely stop a cyber attack from even entering a network, we have a much higher chance of our data being safe and protected.