Dynamic Security Policy via Risk Profile Logging
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Solution Overview
Problem
Existing security policies for computer systems are often static and fail to adapt to dynamic environments and user behaviors, leading to security compromises or productivity hindrances.
Innovation Solution
A method that logs risk factors over time to dynamically generate and update a risk profile, which is used to set and adjust security policies accordingly, ensuring security policy aggressiveness aligns with the current risk environment and user behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a static security policy is used, then the security policy is simple to implement, but it cannot adapt to dynamic environments and user behaviors
Solution Approach 1:
The patent implements dynamic security policies that automatically adjust based on real-time risk assessments. The system continuously monitors user behavior, system state, and security events to dynamically modify policy parameters, transitioning from static to adaptive security control without requiring complex manual reconfiguration.
Solution Approach 2:
The system incorporates feedback loops where security events and risk assessments feed back into policy adjustments. The risk assessment module continuously evaluates security conditions and feeds this information back to the policy enforcement mechanism, enabling automatic adaptation to changing threats and behaviors.
2Reliability
If a static security policy is used, then the implementation is straightforward, but it leads to security compromises or productivity hindrances
Solution Approach 1:
The system dynamically changes security parameters such as access control levels, monitoring intensity, and policy strictness based on real-time risk assessments. When risk is low, policies become more permissive to maintain productivity; when risk increases, policies automatically tighten to ensure security reliability.
Solution Approach 2:
The patent enables security policies to dynamically adjust their strictness based on current risk conditions, allowing the system to balance security and productivity automatically rather than requiring fixed, overly restrictive policies that hinder operations.
3Measurement precision
If risk factors are logged and analyzed over time, then the risk profile becomes more accurate, but the data processing complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-defining risk factor categories, weighting schemes, and assessment models before actual security events occur. This preparation work structures the data collection and analysis process, making real-time risk profiling more efficient despite the volume of data being processed.
Solution Approach 2:
The risk assessment system operates autonomously, automatically collecting, analyzing, and interpreting security data without requiring manual intervention. The system self-manages the complexity of data processing through automated algorithms and machine learning models that continuously refine risk profiles based on accumulated data.
Data Source
AI summary
Risk events occurring on a computer system are logged over time and a risk profile is dynamically generated and updated based on the logged risk events. In one embodiment, a security policy is dynamically set and updated based on the risk profile.