In the coming years, IT security companies will face extreme challenges. Hackers are targeting people instead of systems. The most costly cyber attacks (APTs, ransomware) occur due to employee errors or abuse of privileges held by third-party providers, as a social engineering attack is much easier than finding a zero-day.
Traditional IT security perimeter defense tools, such as password authentication, are necessary but insufficient for detecting privileged account abuse or hijacked credentials.
Once attackers are inside the network, using legitimate user accounts to gain access to sensitive data, their behavior alone is the missing link in detecting and preventing intrusion. And this can be done in real time during the attack.
Behavioral security models know how an employee moves their mouse, or how they type, where they usually navigate, and the type of work they do.
The focus of security on the activity of privileged users, who have unlimited access to sensitive data, does not seem to be that helpful with new attacks. The market needs solutions that are able to monitor all important parts of the system, extract as much information as possible from user connections/sessions, learning behaviors.
Due to the amount of data that will be generated, artificial intelligence will play a significant role in the coming years, transforming data into valuable security information.
Self-learning algorithms from Big Data in IT security companies will be able to automate data processing and allow security professionals to focus on real, high-priority risks.
Such behavioral analytics solutions are relatively new to the market, but it seems that their integration into existing IT environments for data processing will be crucial in the near future.
