Cryptocurrency Malware and Ransomware Detection via Risk Databases
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Solution Overview
Problem
Existing systems lack effective methods to detect and prevent cryptocurrency-based malware and ransomware attacks, particularly in real-time, and to comply with anti-money laundering regulations through comprehensive blockchain transaction analysis.
Innovation Solution
A system and method that analyzes malware and ransomware attacks to determine cryptocurrency payment addresses, builds a database of such addresses, and identifies and denies suspicious transactions using machine learning and blockchain transaction analysis to prevent malware and ransomware attacks, while providing real-time risk scoring and compliance with anti-money laundering regulations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If blockchain transaction analysis is performed to detect cryptocurrency-based malware and ransomware attacks, then detection capability is improved, but processing time and computational resources increase
Solution Approach 1:
The system pre-builds a database of known malicious cryptocurrency addresses and patterns before attacks occur. When a transaction is detected, the system queries this pre-prepared database rather than analyzing all transactions from scratch, enabling real-time detection while reducing computational burden through preliminary data preparation.
Solution Approach 2:
The patent introduces an intermediary database layer between the blockchain transaction data and the detection algorithm. This database stores pre-processed information about malicious addresses, patterns, and relationships, allowing the detection system to query and match transactions against known threats without re-analyzing the entire blockchain, thus reducing processing time while maintaining detection accuracy.
2Reliability
If comprehensive blockchain transaction analysis is conducted to prevent ransomware attacks, then prevention effectiveness is improved, but system complexity increases
Solution Approach 1:
The system segments the blockchain analysis process into distinct modules: transaction monitoring, database querying, pattern matching, and alert generation. Each module handles a specific aspect of the analysis independently, making the overall system more manageable and easier to maintain while providing comprehensive prevention capabilities through coordinated operation of these segmented functions.
Solution Approach 2:
The patent employs an intermediary database structure that simplifies the complexity of blockchain analysis by pre-organizing malicious address information, transaction patterns, and risk assessments. This intermediary layer abstracts the complexity of comprehensive blockchain analysis, allowing the prevention system to operate with simplified query operations while maintaining thorough analysis capabilities.
3Speed
If real-time cryptocurrency transaction monitoring is implemented, then response speed is improved, but computational resources and energy consumption increase
Solution Approach 1:
The system performs preliminary actions by pre-processing and storing blockchain transaction data, malicious address lists, and risk patterns in optimized database structures. When real-time monitoring detects a transaction, the system can quickly query this pre-prepared data without re-analyzing the entire blockchain history, enabling fast response while reducing real-time computational resource requirements through preliminary data preparation.
Solution Approach 2:
The patent employs lightweight data structures and indexed database queries that consume minimal computational resources for real-time lookups. By using efficient data indexing and pre-computed risk scores, the system can perform rapid transaction analysis with low energy consumption compared to comprehensive re-analysis approaches, making real-time monitoring economically viable.
Data Source
AI summary
Cryptocurrency based malware and ransomware detection systems and methods are disclosed herein. An example method includes analyzing a plurality of malware or ransomware attacks to determine cryptocurrency payment address of malware or ransomware attacks, building a malware or ransomware attack database with the cryptocurrency payment addresses of the plurality of malware or ransomware attacks, identifying a proposed cryptocurrency transaction that includes an address that is included in the malware or ransomware attack database, and denying the proposed cryptocurrency transaction.