MVNOs, CSPs, and device OEMs are currently hampered by legacy security applications that do not provide the AI-enabled cyber-status visualization required to provide real-time or proactive protection of networks, devices, and customers from an increasingly insidious array of threats. A sampling of current challenges would include:
Telecom ecosystems are exposed to an ever-increasing volume of cyber intrusions. Conservative estimates are that that attacks are increasing at annual rates of 60 – 70%.
The ubiquitous nature of the smart device has not come without risk. Recent studies have shown that the average IoT ecosystem can be probed for weakness several thousand times per week.
As threat surfaces continue to expand it becomes increasingly difficult to provide consistent levels of security and monitoring across the entire threat landscape.
Network asset stakeholders have no ability to predict potential cyber threats or to take preventive action.
provides rapid synthesis of large volumes of network data. AI-enabled regression analysis closes existing gaps in threat assessment accuracy and provides continuous insights into current and future threats.
ensure that the right data, goes to the right recipient, at the right time. The generation of data-induced notifications and alerts are fully automated and tightly controlled.
via endpoint and edge AL/ML algorithms that provide the active learning, scenario analysis, and virtual triage needed to accurately predict the most effective reactions to potential network cyber intrusions.
supported by MicroAI’s analytics, workflows, and visualization technologies provides a comprehensive, self-contained, engine for at-a-glance visualization of cyber status across the interconnected landscape.
Supported by lightweight AI-enabled analytics, workflows, and visualization technologies, MicroAI provides a comprehensive suite of products and solutions to enable a Zero-Trust security state. Network security that delivers:
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