AI policy statistics in Secure Workload
The AI Policy Statistics feature in Secure Workload offers key functionalities:
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Policy trend analysis: You can view the performance trends of policies over a specific time period. They can compare the expected number of flows with the actual performance of the policies.
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Policy conditions: The AI engine identifies and flags policies that meet specific conditions and require user attention.
Note
A policy condition rule cannot be in more than one condition at a time. For example, a rule can be in either the Broad or Overshadowed condition at a time, but not both simultaneously.
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No Traffic—A policy that does not affect any flow for a configured period.
Figure 1. Policy condition–No Traffic
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Overshadowed—A policy that overshadows another policy.
Figure 2. Policy Condition–Overshadowed
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Broad—A policy source filter or destination filter that has underutilized policy filters. For example, if a filter consists of ten inventories and only two out of the ten inventories participate in the flows that are affected by the policy, the filter will be at only 20 percent utilization.
Figure 3. Policy Condition–Broad
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AI policy statistics on traffic flows
AI Policy Statistics are numeric measures that
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reflect the impact of each policy on network traffic flows,
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provide insights into policy effectiveness, and
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focus on deployed policies, excluding drafts or unpublished versions.
Note |
The First Scanned On and Last Used On columns shows the timestamp of the first time the AI engine scanned a policy, and the timestamp of the last time it scanned a policy. |
High volume trends in traffic flows
Traffic pattern analysis is a monitoring method that:
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Uses an AI engine to process historical data and focuses on current traffic patterns,
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Establishes a baseline of normal traffic for comparison, and
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Flags deviations from this baseline as potential anomalies.
During peak events, the system processes data in real-time to effectively identify anomalous traffic flows. Insights into policies provide real-time data on policy performance to monitor and respond to traffic spikes. System analysis algorithms consider the dynamic nature of network traffic to accurately identify and report anomalies without generating false positives.
Calculate policy statistics
A policy statistic is a performance measurement that:
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depends on flows matching a policy's criteria,
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updates every six hours for one week, and
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includes AI algorithms to analyze data and identify patterns beyond simple hit counts.
Machine learning algorithms are used to analyze and identify patterns, and trends in hit counts, providing a detailed overview of policy performance compared to simple firewall hit counts.
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