Overview
Intelligent policy recommendation is an advanced capability of Zscaler AI-Powered App Segmentation that streamlines your zero trust journey. It delivers precise user-to-app segmentation and tailored access policies recommendations, ensuring secure and efficient connectivity for users across your organization.
Why Use AI-Powered Intelligent Policy Recommendations?
Transforming Security with Zero Trust
In today’s dynamic digital landscape, traditional security models are no longer sufficient to protect against sophisticated threats. Organizations need to transition to a zero trust approach, where implicit trust is eliminated, and every access request is continuously validated.
The intelligent policy recommendation is crucial in this transition, as it analyzes application traffic to intelligently segment apps and recommend policies tailored to your organization’s needs. This ensures secure, efficient, and seamless connectivity for users, no matter where they are or which devices they use. Embrace this solution to fortify your security posture and pave the way for a robust zero trust architecture.
The Zscaler Innovations
What makes AI-Powered Intelligent Policy Recommendations stand out?
Granular App Segmentation
Sophisticated machine learning techniques are employed to comprehensively analyze users and applications behavior by scrutinizing transactional logs. By leveraging techniques like sequential access patterns between applications and adjusted domain name similarities, this approach yields refined application segments that offer enhanced security through granular access control.
Customer-Preferred User Grouping
The recommendation system utilizes customer-preferred user groups to generate policies. This process not only streamlines policy configuration, enhancing efficiency, but also simplifies management by aligning with customer needs, resulting in a more intuitive and user-friendly experience.
Optimized Policy Generation
Policy generation algorithm optimizes to ensure all legitimate users who need access to the application are included while minimizing the number of users with unnecessary access, thereby decreasing the potential attack surface. The algorithm also leverages user groups that exhibit similar access patterns to predict potential future users and cover them proactively.
Benefits of using AI-Powered Intelligent Policy Recommendation
Reduced Attack Surface
Our solution prioritizes application segments and policy recommendations that offer the highest reduction in attack surface, ensuring your network is more secure from potential threats.
Ranked Recommendations
We provide you with ranked recommendations that have high confidence scores from our machine learning models. These scores are based on multiple quality metrics, helping you implement the most effective policies first.
Recommendation Insights
Each recommendation includes detailed insights about the relevant applications and users, enabling you to make informed decisions on whether to configure the recommended app segment and policy.
Flexible User Grouping Options
Easily switch between Department and SCIM Group data for user group recommendations, allowing you to tailor the configuration to your organizational structure and preferences.
Recommendation Explainability
Each app segment recommendation comes with a clear explanation of the grouping rationale, helping you understand the reasoning behind the segmentation and ensuring transparency in the policy configuration process.
Understand how AI-Powered App Segmentation helps in eliminating lateral threat movements through this webinar (explains about the technology, demo, and customer perspective input).
For more information on intelligent policy recommendations read the reference architecture white paper, watch the demo of AI-Powered App Segmentation, and schedule a demo.
Overview
Intelligent policy recommendation is an advanced capability of Zscaler AI-Powered App Segmentation that streamlines your zero trust journey. It delivers precise user-to-app segmentation and tailored access policies recommendations, ensuring secure and efficient connectivity for users across your organization.
Why Use AI-Powered Intelligent Policy Recommendations?
Transforming Security with Zero Trust
In today’s dynamic digital landscape, traditional security models are no longer sufficient to protect against sophisticated threats. Organizations need to transition to a zero trust approach, where implicit trust is eliminated, and every access request is continuously validated.
The intelligent policy recommendation is crucial in this transition, as it analyzes application traffic to intelligently segment apps and recommend policies tailored to your organization’s needs. This ensures secure, efficient, and seamless connectivity for users, no matter where they are or which devices they use. Embrace this solution to fortify your security posture and pave the way for a robust zero trust architecture.
The Zscaler Innovations
What makes AI-Powered Intelligent Policy Recommendations stand out?
Granular App Segmentation
Sophisticated machine learning techniques are employed to comprehensively analyze users and applications behavior by scrutinizing transactional logs. By leveraging techniques like sequential access patterns between applications and adjusted domain name similarities, this approach yields refined application segments that offer enhanced security through granular access control.
Customer-Preferred User Grouping
The recommendation system utilizes customer-preferred user groups to generate policies. This process not only streamlines policy configuration, enhancing efficiency, but also simplifies management by aligning with customer needs, resulting in a more intuitive and user-friendly experience.
Optimized Policy Generation
Policy generation algorithm optimizes to ensure all legitimate users who need access to the application are included while minimizing the number of users with unnecessary access, thereby decreasing the potential attack surface. The algorithm also leverages user groups that exhibit similar access patterns to predict potential future users and cover them proactively.
Benefits of using AI-Powered Intelligent Policy Recommendation
Reduced Attack Surface
Our solution prioritizes application segments and policy recommendations that offer the highest reduction in attack surface, ensuring your network is more secure from potential threats.
Ranked Recommendations
We provide you with ranked recommendations that have high confidence scores from our machine learning models. These scores are based on multiple quality metrics, helping you implement the most effective policies first.
Recommendation Insights
Each recommendation includes detailed insights about the relevant applications and users, enabling you to make informed decisions on whether to configure the recommended app segment and policy.
Flexible User Grouping Options
Easily switch between Department and SCIM Group data for user group recommendations, allowing you to tailor the configuration to your organizational structure and preferences.
Recommendation Explainability
Each app segment recommendation comes with a clear explanation of the grouping rationale, helping you understand the reasoning behind the segmentation and ensuring transparency in the policy configuration process.
Understand how AI-Powered App Segmentation helps in eliminating lateral threat movements through this webinar (explains about the technology, demo, and customer perspective input).
For more information on intelligent policy recommendations read the reference architecture white paper, watch the demo of AI-Powered App Segmentation, and schedule a demo.
[[{“value”:”Overview
Intelligent policy recommendation is an advanced capability of Zscaler AI-Powered App Segmentation that streamlines your zero trust journey. It delivers precise user-to-app segmentation and tailored access policies recommendations, ensuring secure and efficient connectivity for users across your organization.
Why Use AI-Powered Intelligent Policy Recommendations?
Transforming Security with Zero Trust
In today’s dynamic digital landscape, traditional security models are no longer sufficient to protect against sophisticated threats. Organizations need to transition to a zero trust approach, where implicit trust is eliminated, and every access request is continuously validated.
The intelligent policy recommendation is crucial in this transition, as it analyzes application traffic to intelligently segment apps and recommend policies tailored to your organization’s needs. This ensures secure, efficient, and seamless connectivity for users, no matter where they are or which devices they use. Embrace this solution to fortify your security posture and pave the way for a robust zero trust architecture.
The Zscaler Innovations
What makes AI-Powered Intelligent Policy Recommendations stand out?
Granular App Segmentation
Sophisticated machine learning techniques are employed to comprehensively analyze users and applications behavior by scrutinizing transactional logs. By leveraging techniques like sequential access patterns between applications and adjusted domain name similarities, this approach yields refined application segments that offer enhanced security through granular access control.
Customer-Preferred User Grouping
The recommendation system utilizes customer-preferred user groups to generate policies. This process not only streamlines policy configuration, enhancing efficiency, but also simplifies management by aligning with customer needs, resulting in a more intuitive and user-friendly experience.
Optimized Policy Generation
Policy generation algorithm optimizes to ensure all legitimate users who need access to the application are included while minimizing the number of users with unnecessary access, thereby decreasing the potential attack surface. The algorithm also leverages user groups that exhibit similar access patterns to predict potential future users and cover them proactively.
Benefits of using AI-Powered Intelligent Policy Recommendation
Reduced Attack Surface
Our solution prioritizes application segments and policy recommendations that offer the highest reduction in attack surface, ensuring your network is more secure from potential threats.
Ranked Recommendations
We provide you with ranked recommendations that have high confidence scores from our machine learning models. These scores are based on multiple quality metrics, helping you implement the most effective policies first.
Recommendation Insights
Each recommendation includes detailed insights about the relevant applications and users, enabling you to make informed decisions on whether to configure the recommended app segment and policy.
Flexible User Grouping Options
Easily switch between Department and SCIM Group data for user group recommendations, allowing you to tailor the configuration to your organizational structure and preferences.
Recommendation Explainability
Each app segment recommendation comes with a clear explanation of the grouping rationale, helping you understand the reasoning behind the segmentation and ensuring transparency in the policy configuration process.
Understand how AI-Powered App Segmentation helps in eliminating lateral threat movements through this webinar (explains about the technology, demo, and customer perspective input).
For more information on intelligent policy recommendations read the reference architecture white paper, watch the demo of AI-Powered App Segmentation, and schedule a demo.”}]]
