Self-Aware Cryptocurrency Wallets Using Bloom Filters for Fraud Detection
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Solution Overview
Problem
Existing cryptocurrency wallets lack the ability to detect potential compromises early, allowing malicious actors to steal funds by hijacking accounts, often unnoticed until significant losses occur.
Innovation Solution
Implementing self-aware cryptocurrency wallets that monitor transactions and utilize probabilistic data structures like Bloom filters, XOR filters, and cuckoo filters to detect unauthorized transactions, alerting users to potential compromises.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional cryptocurrency wallets are used, then users can store and manage their funds, but they cannot detect unauthorized transactions until it is too late
Solution Approach 1:
The wallet performs preliminary actions by maintaining a pre-computed set of all possible transaction hashes that could be generated by the user's private key. This allows the wallet to immediately recognize and alert the user when any of these pre-identified hashes appear on the blockchain, enabling detection before significant losses occur.
Solution Approach 2:
The wallet creates a copy of the transaction monitoring function by computing and storing all possible transaction hashes locally using the user's public key. This copy allows the wallet to independently verify transactions without needing to query the blockchain for each individual transaction, enabling rapid detection of unauthorized activity.
2Reliability
If the wallet monitors all possible transactions by computing hashes, then early detection is enabled, but computational complexity increases
Solution Approach 1:
The system uses a universal approach by generating all possible transaction hashes that could be created with the user's private key, regardless of the specific transaction parameters. This single comprehensive set of hashes covers all possible future transactions, eliminating the need for separate monitoring mechanisms for different transaction types.
Solution Approach 2:
The wallet performs the computationally intensive hash generation in advance, before any transactions occur. By pre-computing the entire set of possible transaction hashes and storing them locally, the system avoids repeated computational work during actual transaction monitoring, reducing real-time computational complexity.
Data Source
AI summary
Systems, methods, and devices described herein can configure a cryptocurrency wallet or other blockchain-based account to be self-aware and alert the owner of the wallet to one or more potentially fraudulent situations occurring with at least one account they own. The wallet may be a hardware-based cryptocurrency wallet or may be a blockchain-based account operating by an external financial institution that allows for the management of cryptocurrency assets. The self-aware wallet can be configured to track all relevant previously known and/or approved transactions associated with a user's private cryptocurrency key. A subsequent scan on one or more blockchains is performed to detect new transactions associated with the user's private key. If a newly detected blockchain transaction is not in the list of previously known or approved user transactions, a potential compromise may be occurring. Once detected, the wallet can generate a notification to the user alerting them to the issue.