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Most cybersecurity vulnerabilities today are unknown until an attack takes place, as conventional cybersecurity measures can only detect and prevent known threats. AI-based anomaly detection is the last word in cybersecurity. It deals with the identification of rare items, events or observations which raise suspicions by differing significantly from the majority of the data.

Almost nowhere is it more important than in connected cars. Any threat that harms the operation of the vehicle’s steering, brakes, or any one of dozens of other critical systems, could mean tragedy. As manufacturers venture further into the realm of connected, and eventually self-driving, vehicles, a solution that catches vulnerabilities before they can cause any damage becomes a vital security requirement, according to automotivetestingtechnologyinternational.com.

Perhaps the most difficult cloud-based attacks to counter are those that rely on social engineering, since they involve deceiving employees into handing over their credentials and other lucrative information voluntarily (phishing attacks). In these cases, artificial intelligence (AI) anomaly detection is the optimal security strategy, as thwarting a social engineering threat before it’s too late means protecting employees from their own mistakes, as reported by techradar.com.

Anomaly detection and predictive analytics have helped British Telecommunications (BT) move from hundreds of alarms being monitored by analysts to a prioritized view of those the company thinks are going to cause a potential outage. 

They’ve also moved from maintenance teams having to manually inspect network equipment for potential failures to capturing photos during routine work which AI tools can use to classify the state of repair and prioritize maintenance schedules, according to publictechnology.net.