A security strategy that focuses too much on prevention can also tie up resources if the attackers get stuck. Security teams spend hours working manually validating, correlating and verifying the large number of alerts that occur every day. Isolating a newly discovered threat can lead to a tedious day of sifting through a huge thicket of data. Qualified analysts are also required to understand the logs of security appliances and tools. The shortage of skilled workers is expected to increase.
The Ability To Detect Threats In Real Time
Companies must therefore shift their focus away from prevention to the detection and defusing of active threats. This is the only way they can close the current cybersecurity gap and reduce the chances of an intruder staying in the network for months and remaining undetected. One of the most important steps in this is the ability to detect threats in real time. Due to the high demands that this work places on qualified and experienced security staff, the greatest possible automation of this process is essential.
Recent years have seen breakthrough innovations in data science and behavior analysis. These advances have in turn made it possible to establish highly efficient and reliable automated threat detection solutions. A good automated threat management system can identify the phases of an active cyberattack as it is being developed. Typical behavior patterns here are command and control, internal scouting, lateral movement in the network, misuse of authorizations, data exfiltration as well as cryptomining activities.
As the number and complexity of cyberattacks increases, perhaps the most useful feature of an automated solution is the sheer amount of data it can handle. Searching through warnings and logs to discover the hidden details that indicate a threat is extremely tedious for a person. However, an automated solution can sift through large amounts of data without tiring or making mistakes.
In particular, analyzing the behavior of attackers is becoming increasingly valuable in order to identify threats. This focused approach means that even if the attacker uses previously unknown malware and hides his traces using encrypted data traffic, certain malicious behaviors can always be observed. This applies provided that it is known what to look for and the ability to reliably find these traces. It is crucial that the internal network traffic is analyzed. By focusing solely on the traffic that crosses the perimeter, intruders are overlooked, internal network intelligence is carried out or malware is distributed and access rights are acquired.