Detect ransomware attacks using NDR and AI
The first Trojan was sent on a floppy disk to research institutions around the globe in 1989. Since then, software attacks with an extortionate background have become the norm for many companies. Malicious computer software, often disguised as completely harmless programs, has caused billions of dollars in damage to private users, companies and government agencies.
While Trojans, worms and other malware cause significant damage to those affected, ransomware works even more insidiously than other malware. This is due to their effective camouflage and extortionate nature. Anyone who catches ransomware usually has to expect a total digital loss.
What escapes the human eye can be detected and combated using artificial intelligence. But how to protect yourself from ransomware? And how can AI help to locate and neutralize digital intruders quickly and in real time? Vectra AI, an expert in AI/ML-based malware detection, explains which methods can help to identify ransomware at an early stage and contain damage.
Ransomware – a race against time
In essence, the ransomware infiltration process is similar to that of other malware: the attackers gain access to computers and servers via a vulnerability in the network. Once the ransomware has established itself in the network, a race against time begins. The task of those affected is to contain the damage as quickly as possible if they do not want to pay a ransom for the recovery of their data. Nowadays, the ransomware extortionists also accept payments in the form of Bitcoin, as WannaCry has demonstrated.
Especially annoying for network administrators are the irreversible damage caused by a ransomware infection. Therefore, a ransomware attack is often considered a major digital disaster. In 2020 alone, data theft, espionage and sabotage caused damage of over 220 billion euros. For example, almost 88 percent of companies in Germany stated that they had already been the target of a cyber attack. Effective protection against ransomware is essential for every company and a challenge for the IT department. This also applies to every private person, because recently more and more ransomware attacks are targeting private systems.
A key factor that makes it so difficult to defend against ransomware is the way the malware gains access to the system. Not infrequently, the programs hide behind relatively harmless names or in e-mail attachments. On its way to infecting important files, the ransomware usually bypasses any malware protection. Therefore, blaming users for opening emails and clicking on attachments is quite short-sighted.
Cybercriminals are becoming more and more skilled in their craft. In addition to fake e-mails, there are now numerous ways in which ransomware can penetrate your own network. At first glance, innovative technologies such as NFC seem to be a big step forward, but they also represent another entry point for malware. So far, there is no really effective way to prevent the penetration of ransomware. Instead, users are dependent on responding to an infection.
How should end users and administrators keep track? So far, the fight against cybercrime has followed a fairly uniform pattern: attackers create a new malware and deploy it. The security teams notice the suspicious activities and isolate the files in question. The security experts in the IT department then develop an effective antidote to the digital plague. As a rule, the result is a new rule or policy that is built into the firewall.
This cat-and-mouse game has been around for more than three decades now. But what if AI-supported systems could detect these attacks in advance? What if automated anti-ransomware tools could expose the malware at an early stage and effectively combat it – even before it can cause damage?
How NDR Exposes Malicious Ransomware Attacks
This is exactly the approach of NDR technology. Network Detection and Response (NDR) is a highly effective cybersecurity solution that automatically searches for unauthorized or suspicious network access. To achieve this, the NDR program uses machine learning. It monitors the activities and checks whether they match the usual behavior pattern of the network.
The advantages for network operators and administrators are obvious. The less time you have to invest in actively searching for data leaks or loopholes, the better. Once the damage is there, the repair is not only labor–intensive, but also costs money – and nerves. It is precisely this part of the work that an AI-based NDR software is to take over in the future in order to relieve IT security officers and administrators.
With the right configuration, NDR can provide effective protection against ransomware. Often the unauthorized accesses are detected immediately after their occurrence. For this purpose, the software uses the behavior patterns from the database: if an activity appears suspicious, the NDR software observes the following steps with a watchful eye. As soon as a potentially malicious behavior is detected, the software sounds the alarm: either by notifying the user or by automatically isolating the questionable guests.