State Machine Caching Priorities for Network Traffic Inspection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current cache-based regular expression engines for network traffic inspection are vulnerable to attacks and suffer performance degradation due to high dependency on slower memory access when cache hit rates drop, especially in worst-case scenarios where attackers target all patterns, leading to significant processing rate limitations.
Innovation Solution
A method is introduced to assign caching priorities to states of a state machine based on access frequency, using a test data stream to determine which states to lock in the cache, ensuring high-priority states are maintained in the cache memory, even when accessed remotely from the start state, thereby preventing cache hit rates from dropping to zero during attacks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If cache-based regular expression engines are used for network traffic inspection, then processing speed is improved, but performance degrades significantly when cache hit rates drop due to attacks
Solution Approach 1:
The system performs preliminary analysis of the state machine to identify and prioritize states that are most likely to be accessed during normal operation. By pre-determining which states should be cached based on their importance and access probability, the system ensures that critical states remain in fast cache memory even under attack conditions, thereby maintaining processing speed and reliability.
2Reliability
If all states are cached in fast memory, then cache hit rate is maintained, but hardware cost and complexity increase
Solution Approach 1:
Instead of uniformly caching all states, the system applies local quality by differentiating between high-priority and low-priority states. Fast cache memory is allocated selectively to high-priority states that are most likely to be accessed, while low-priority states are stored in slower, less expensive memory. This differentiated approach maintains cache hit rates for critical operations while reducing overall hardware cost and complexity.
3Productivity
If cache size is increased to maintain hit rates during attacks, then processing continuity is improved, but hardware cost increases
Solution Approach 1:
The system changes the parameter of cache allocation from a static, uniform approach to a dynamic, priority-based approach. By assigning different caching priorities to different states based on their importance and access patterns, the system optimizes cache utilization. This allows maintaining processing continuity during attacks by ensuring critical states are cached, while avoiding the need to increase overall cache size and associated hardware costs.
Data Source
AI summary
Systems and methods for reducing network performance degradation by assigning caching priorities to one or more states of a state machine are disclosed herein. In one embodiment, the method comprises storing, in a memory, a state machine corresponding to one or more patterns to be detected in a data stream, wherein the state machine comprises a plurality of states, generating a test data stream based on the one or more patterns, traversing the state machine with the test data stream, determining a respective hit quantities associated with each of the plurality of states, the hit quantities each indicating a number of accesses to a corresponding state by the traversing, and associating a caching priority to at least some of the plurality of states based on the hit quantities of the respective states.