Guard Table Hash Index for Network Security Query Optimization
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Solution Overview
Problem
Network security systems face processing and transmission delays when searching for information not stored in datastores, which can compromise performance and lead to issues like denial of service attacks.
Innovation Solution
Implementing a guard table with a hash index to quickly determine the presence or absence of information, allowing for reduced CPU and network resource usage by checking the guard table before querying the datastore.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a datastore is queried for information not present, then complete security verification is performed, but processing time increases significantly
Solution Approach 1:
A guard table is pre-populated with hash values of all expected keys before queries are processed. When a query arrives, the system first checks the guard table to determine if the key exists before performing a full datastore search. This preliminary check prevents unnecessary expensive searches for non-existent keys, reducing processing time while maintaining security verification for valid keys.
Solution Approach 2:
The guard table acts as an intermediary layer between the query interface and the main datastore. It provides a fast O(1) lookup mechanism that filters out queries for non-existent keys before they reach the slower datastore. This intermediary structure maintains the reliability of security verification by ensuring all valid keys are still checked, while dramatically improving performance by eliminating searches for absent information.
2Reliability
If CPU resources are allocated to search for absent information, then query completeness is maintained, but processor load increases
Solution Approach 1:
The guard table is pre-computed with hash values for all possible keys that should exist in the system. This preliminary action creates a lightweight reference structure that enables the system to quickly determine whether a query is for an existing or non-existing key, avoiding the need to allocate CPU resources for searching absent information while maintaining query completeness for valid entries.
Solution Approach 2:
The existence verification function is extracted from the main datastore search process and placed in a separate guard table structure. This extraction isolates the expensive search operation, allowing the system to quickly reject queries for absent information without involving the main datastore processing resources, thereby reducing overall processor load while maintaining query completeness.
3Reliability
If network resources are used to transmit query results for absent information, then response completeness is maintained, but network bandwidth is consumed
Solution Approach 1:
The guard table performs preliminary existence verification before triggering any datastore search or network response generation. By checking the guard table first, the system can immediately determine whether a query is for an existing key, preventing unnecessary network transmissions for absent information while maintaining response completeness for valid queries through selective network communication.
Data Source
AI summary
Guard tables including absence information are used in a security system to limit the processing of negative queries. A key corresponding to a request to access a network resource is hashed and the output of the hash is a bit position in a guard table. The bit value at the bit position in the guard table is checked to determine if the information to which the key corresponds is absent from a datastore. Further processing of the request can be based on the indicated presence or absence information.