Distributed Ledger Proof of Integrity for Ransomware Asset Control
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Solution Overview
Problem
Existing cybersecurity measures in computer networks are inadequate in preventing and managing ransomware attacks, particularly in transactions involving cryptocurrencies, as they often disrupt legitimate transactions and lack the subtlety needed for ambiguous scenarios, and traditional fraud prevention systems fail to adapt to evolving fraudulent patterns.
Innovation Solution
A proof of integrity (PoI) model integrated into distributed ledger technology (DLT) networks that embeds a protection parameter into transactions, allowing them to proceed conditionally while monitoring and controlling assets, using smart contracts and protection nodes to enforce compliance with ethical and legal standards, and dynamically update to new threats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional fraud prevention systems are used to block suspicious transactions, then security against ransomware attacks is improved, but legitimate transactions are disrupted and false positives increase
Solution Approach 1:
The system performs preliminary analysis of transaction contexts, user behavior patterns, and device fingerprints before blocking transactions. Protection nodes evaluate multiple dimensions including transaction history, device characteristics, and contextual information to pre-assess risk levels, allowing legitimate transactions to proceed while preparing to block malicious ones
Solution Approach 2:
The fraud prevention system dynamically adjusts its blocking criteria and risk thresholds based on evolving ransomware patterns and transaction contexts. The system continuously learns from new attack vectors and modifies its protection parameters in real-time, transitioning from static rule-based blocking to adaptive, context-aware decision-making
2Measurement precision
If comprehensive fraud detection algorithms are deployed to identify all fraudulent patterns, then detection accuracy is improved, but system complexity and computational resources increase
Solution Approach 1:
The fraud detection system is segmented into specialized protection nodes with distinct responsibilities: some nodes focus on behavioral analysis, others on device fingerprinting, and others on transaction pattern recognition. This modular architecture distributes computational complexity across multiple specialized components rather than requiring one monolithic complex system
Solution Approach 2:
The system introduces protection nodes as intermediary components between transaction participants and the blockchain network. These intermediaries perform complex analysis and filtering, simplifying the overall system architecture by centralizing sophisticated detection logic in dedicated nodes rather than requiring complexity throughout the entire network
3Reliability
If protection parameters are embedded in all transactions to control tainted assets, then ransomware asset control is improved, but transaction processing time and validation overhead increase
Solution Approach 1:
Protection parameters and integrity markers are embedded in transactions during the initial exchange process rather than added later during validation. The system performs preliminary tagging of assets with protection parameters at the source, allowing downstream nodes to quickly verify rather than analyze, reducing validation time while maintaining effective asset control
Solution Approach 2:
The system uses cryptographic hashes and pointers to reference protection parameters rather than embedding full validation logic in every transaction. Protection nodes store comprehensive protection rules and use cryptographic references to verify compliance, reducing the computational burden on each transaction while maintaining security
Data Source
AI summary
Systems, methods, and computer-readable storage media for restricting exchanges using a proof of integrity model. One system includes memory and at least one processing circuit configured to receive, from a node on a first DLT network, an exchange request, the exchange request includes an amount of a digital asset to exchange, a content item, and a destination identifier. The at least one processing circuit is further configured to generate an exchange record and validate the exchange record in the amount of the digital asset based on a protection model. The at least one processing circuit is further configured to authorize, based on a consensus model, the exchange corresponding with the validated exchange record including the appended protection parameter. The at least one processing circuit is further configured to generate a new blockchain block on the first DLT network and transmit, to a second DLT network, an exchange notification.