Adapted Bloom Filter for Network Packet Tracking
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Solution Overview
Problem
Current networking protocols face challenges in efficiently handling and processing data packet/frames, particularly in tracking retries and maintaining communication integrity, especially under high traffic and cyberattack conditions, due to hardware limitations in processing and storage speed.
Innovation Solution
The implementation of an adapted Bloom filter system that utilizes multiple memory words with specific bit configurations for Flags, Timestamp, and Counter fields, allowing for efficient tracking of data packet/frame attempts and retries over a sliding window of time, while also mitigating false positives through re-initialization processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional networking protocols are used to track data packet attempts and retries, then communication reliability is maintained, but processing speed and storage efficiency deteriorate under high traffic conditions
Solution Approach 1:
The patent segments the tracking state into multiple independent Bloom filters (one for each communication partner), allowing parallel processing of multiple connections without sequential overhead. Each Bloom filter operates independently, enabling simultaneous updates and queries across different communication sessions, thus improving processing speed while maintaining reliability through distributed state management.
Solution Approach 2:
The patent changes the data structure parameter from traditional sequential state tracking to a probabilistic Bloom filter representation. This parameter change allows constant-time operations for adding and querying connection states, transforming the time complexity from O(n) to O(1), thereby dramatically improving processing speed while maintaining the reliability needed for communication protocol handshaking and retry tracking.
2Measurement precision
If traditional data structures are used to track communication attempts, then accurate tracking is achieved, but storage requirements increase
Solution Approach 1:
The patent applies partial action by using Bloom filters that provide probabilistic rather than deterministic tracking. This allows the system to accept a small probability of false positives in exchange for dramatically reduced storage requirements. The Bloom filter uses bit arrays and hash functions to represent connection states with minimal space, achieving efficient tracking of communication attempts and retries without requiring full-precision data structures for each connection state.
Solution Approach 2:
The patent uses multiple copies of the same Bloom filter data structure (one per communication partner) instead of a single complex state machine. This copying approach allows parallel tracking of multiple connections using identical, space-efficient templates, reducing overall storage requirements while maintaining tracking accuracy through replicated state representation across different communication sessions.
3Reliability
If comprehensive tracking of all communication attempts is performed, then communication integrity is ensured, but processing overhead increases
Solution Approach 1:
The Bloom filter structure provides self-service through its inherent probabilistic properties, automatically handling the tracking of communication attempts without requiring complex validation logic or extensive processing. The hash-based structure naturally manages state updates and queries with minimal computational overhead, reducing the energy consumption associated with comprehensive tracking while maintaining communication integrity through its probabilistic guarantee of state accuracy.
Data Source
AI summary
A method and system are disclosed for handling a received content word in a system comprising a memory of memory words, wherein: each memory word comprises Bloom Filter structures. The method comprises hashing the content word into a fixed-size word, pointing to the memory word corresponding to an address of the fixed-size word, pointing to, and reading, the Bloom Filter structure in the pointed memory word corresponding to an address in the fixed-size word, and reading and writing the content of the Bloom Filter structures so as to keep track of a number of occurrences of the received content word over a sliding window of time.