Dynamic Security Rule Balancing in Database Protection
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Solution Overview
Problem
Current database protection systems (DPS) face challenges in maintaining high availability and scalability, particularly in handling large numbers of simultaneous database connections, leading to inefficiencies in security rule validation throughput and potential delays in real-time validation.
Innovation Solution
The DPS is enhanced with multiple security rules engines (SREs) that dynamically optimize security rule validation by analyzing resource consumption data to determine which rules to prioritize or deactivate, using an optimizer and distributor to ensure efficient resource allocation and maximize throughput.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the DPS validates all security rules for every database connection, then security coverage is improved, but validation throughput deteriorates under high connection loads
Solution Approach 1:
The system dynamically adjusts which security rules are active at each SRE based on real-time resource consumption data. The optimizer continuously monitors resource usage and redistributes rule validation across multiple SREs, allowing the system to adapt its security validation strategy to current load conditions and maintain throughput while preserving security coverage.
Solution Approach 2:
The system divides the security rule validation workload across multiple Security Rules Engines (SREs). Instead of a single engine handling all rules, the optimizer distributes different subsets of rules to different SREs based on resource consumption patterns, enabling parallel processing and improved overall throughput while maintaining comprehensive security coverage.
2Reliability
If the DPS increases the number of security rules to cover more security scenarios, then security comprehensiveness is improved, but resource consumption deteriorates
Solution Approach 1:
Different SREs are assigned different subsets of security rules based on their resource consumption characteristics and performance. The optimizer analyzes resource usage patterns and distributes rules strategically, allowing each SRE to operate within its resource capacity while collectively providing comprehensive security coverage across the system.
Solution Approach 2:
The system changes the operational parameters of security rule validation by dynamically adjusting which rules are active at each SRE. The optimizer modifies rule activation states based on resource consumption data, enabling the system to handle a comprehensive set of security rules while controlling overall resource usage through parameter optimization.
3Adaptability or versatility
If the DPS processes more simultaneous database connections, then system scalability is improved, but validation performance deteriorates
Solution Approach 1:
The system segments the validation workload across multiple SREs to handle increased connection loads. Each SRE processes a subset of rules for incoming connections, enabling the system to scale handling capacity linearly with the number of engines while maintaining validation performance through distributed parallel processing.
Solution Approach 2:
The optimizer continuously collects resource consumption data from SREs and uses this feedback to dynamically adjust rule distribution. This closed-loop control allows the system to maintain optimal validation performance even as connection counts fluctuate, automatically adapting the validation strategy to current system state and load conditions.
Data Source
AI summary
A database protection system (DPS) is configured to dynamically-optimize security rule validation throughput based on evaluating resource consumption data collected from prior validations. In particular, the DPS analyzes collected resource consumption information and determines which security rules in a set should then be active. To this end, the DPS is configured with multiple security rules engines (SREs), and each is configured to evaluate the same set of security rules. When an SRE applies a validation (to a request or response flow), an associated collector collects and analyzes associated resource consumption data. This data is provided to an optimizer, which receives similar resource consumption data from other SREs. Based on the resource consumption data collected from the SRE collector(s), the optimizer dynamically optimizes security rules validation in real-time, e.g., by dynamically switching on or off given security rule(s) in the set of security rules at given one(s) of the SREs.