Machine learning (ML) and artificial intelligence (AI) have emerged as critical tools for dealing with the ever-growing volume and complexity of cybersecurity threats.
Machines can recognize patterns to detect malware and unusual activity better than humans and classic software. The technology also predicts potential attacks and automatically responds to threats by identifying specific trends and cycles.
Indeed, it’s not uncommon to have similar incidents that generally require the same response. Instead of repeating the same procedure, sometimes manually, the system can detect the attack, report and categorize the incident, and then apply the fix automatically.
Even better, security tools like behavioral analytics can spot attacks simply by noticing anomalous activity, important technology for catching zero-day threats and adversarial attacks.
It’s an excellent asset for cyber defense, but adversaries have learned to trick algorithms and even use similar technology to compromise targeted systems. It’s the latest chapter in the ongoing cybersecurity arms race, with attackers and defenders locked in a never-ending struggle, each adapting to the other’s innovations to try…
