Today’s complex and advanced network environments deal with huge amount of information on a constant basis. This makes the job of IT and security teams challenging to figure out about the actual threats. Artificial intelligence (AI) is being applied across this spectrum. Internet users tend to do things out of negligence as clicking on malicious sites or store sensitive information in unsecured places, which lead to security vulnerabilities. This ends up with generating thousands of anomalies that set off alerts on a daily basis. Security teams face difficulties in figuring out the actual threats. AI and machine learning help teams to identify which anomalies require concerns and which don’t. Organizations need a smart framework to focus on which anomalies should matter to them. They also need their campaigns to contain three elemental behaviors as,
Reconnaissance: It says to learn about the structure of network and services, and location to store valuable data.
Collection: It says to learn about gathering and moving important data in preparation for exfiltration.
Exfiltration: It is about hiding data movement from the network to external destinations.
These behaviors help organizations to have an actual security picture to look at anomalies. Also, help to see if they correlate with the behaviors.
AI and machine learning help organizations to find out important security alerts. AI accelerates human professionals with uses of AI-tools. AI should not be left to its own devices. It should have human interaction and training to learn and improve to provide with the safety from frauds and cybercriminal innovations. The IT departments across organizations have garnered this human-machine approach as a valuable asset to work efficiently against threats. AI helps teams and personnel to look at the network from the threat actor's perspective to spot their activities that harm the networks. Also, supports to eliminate confusions, focus on security expertise, and keeps networks safe.