Fuzzy Blocklist Random Selection for Large Address Ranges
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Solution Overview
Problem
Existing systems face inefficiencies and computational complexity when selecting random entities from large sample sizes, particularly in processes like IP address scanning, due to the need to exclude undesirable ranges, which becomes time-consuming and resource-intensive, especially in IPv6 address spaces.
Innovation Solution
A system and method utilizing a fuzzy blocklist capability that employs a fuzzy blocklist to exclude undesirable entities by using a range editor, index engine, data chunker, data normalization engine, and advanced random number generator to efficiently select random entities, optimizing the process for large sample sizes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a simple random number generation method is used to select from a large range of entities, then the selection process is computationally simple, but the system cannot effectively exclude undesirable ranges of entities
Solution Approach 1:
The system segments the large entity range into multiple smaller ranges, identifying which ranges are desirable and which are blocked. This segmentation allows the system to maintain computational efficiency while effectively excluding undesirable ranges by only performing random selection within approved segments.
Solution Approach 2:
The system performs preliminary identification and categorization of entity ranges into desirable and blocked categories before the random selection process. This preliminary action enables the random number generator to efficiently skip blocked ranges and directly select from desirable ranges, maintaining both simplicity and reliability.
2Reliability
If a loop-based method is used to check and regenerate random entities until an acceptable one is found, then undesirable ranges can be excluded, but the process becomes time-consuming and computationally expensive
Solution Approach 1:
The system extracts and removes blocked ranges from the selection pool before performing random number generation. Instead of generating random numbers and then checking if they fall in blocked ranges (which requires loops), the system directly generates numbers only from desirable ranges, eliminating the need for iterative checking and regeneration.
Solution Approach 2:
The system performs the action of identifying and separating desirable ranges from blocked ranges before the random selection process. This preliminary separation allows for direct, efficient random selection without requiring loops to check and regenerate values, significantly reducing selection time.
3Reliability
If the entire range of possible entities is scanned and checked against blocklists, then all undesirable entities can be excluded, but the computational cost increases significantly with large sample sizes
Solution Approach 1:
The system segments the entire entity range into manageable ranges and identifies which segments are blocked versus desirable. This segmentation allows the system to maintain complete exclusion of undesirable entities while improving productivity by only performing random selection operations on the smaller subset of desirable ranges rather than scanning the entire space.
Data Source
AI summary
A system and methods for selecting a random entity with a fuzzy blocklist capability, comprising a range editor which acts on data received by either a plurality of databases or a possible address map; and an advanced random number generator. The range editor allows for breaking data into either desirable or blocked chunks which may be normalized and passed to the advanced random number generator. The advanced random number generator may select a random value from within a randomly selected chunk. Various methods for randomly selecting both a chunk and a value may be used to maximize the efficiency of the method and system.