Predictive AI Detects Mass Encryption and Shapes Zero Trust
Predictive AI can detect both ransomware and mass encryption-type events. Rubrik has observed that ransomware impacts and encrypts the hypervisor, an application allowing agencies to run multiple virtual devices on a single device, in about 60% of cases. This figure falls short of what endpoint security typically detects and provides to federal security operations centers. However, predictive AI can help agencies find early signals of mass encryption within their networks or predict ransomware attacks.
Alongside behavioral analytics and user intelligence, predictive AI will also impact how agencies build zero-trust architectures. Having complete visibility of the systems, users, devices and security postures, as well as the network and data, should be an essential step for agencies. These tools enable monitoring of data access and can identify anomalous behavior before cybercriminals strike, such as unauthorized users accessing sensitive data or systems or escalating their privileges.
Additionally, agencies can deploy predictive AI to find links between suspicious activity on disparate systems and user interfaces by looking at backup data, including monitoring unauthorized activity and continuously identifying who is accessing what. Essentially, predictive AI is a catalyst for alerting agencies to abnormalities as they occur with speed and accuracy.
Agencies find themselves at a crossroads for transforming their cybersecurity tactics, with predictive AI supporting their zero-trust architectures; real-time threat detection; and data security, backup and recovery. This, in turn, will advance their missions of safeguarding national security in the face of evolving foreign and domestic threats and improving the quality of their service delivery.
UP NEXT: Operationalizing cyber defense is as important as zero trust.
