Blockchain Network Function Request Security Scanning
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Solution Overview
Problem
Decentralized peer-to-peer (P2P) networks face challenges in detecting unexpected data and irregularities, such as fraudulent data and malware, within their blockchain data structures, which can compromise network integrity and operation.
Innovation Solution
A computing device within the P2P network scans network function requests against security criteria, flags suspicious requests, and updates flag ratings for associated wallets, while parsing smart contracts to identify malicious operations, ensuring only secure data is added to the blockchain.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If decentralized P2P networks store and process blockchain data without centralized control, then network autonomy and distributed operation are improved, but vulnerability to fraudulent data and malware infiltration increases
Solution Approach 1:
The system performs preliminary scanning of network function requests against security criteria before they are executed or stored in the blockchain. This preventive approach identifies and flags suspicious data patterns, wallet addresses, or contract operations before they can compromise the network, thus maintaining both autonomy and security.
Solution Approach 2:
The patent introduces an intermediary security scanning mechanism that acts as a mediator between incoming network requests and the blockchain execution environment. This intermediary layer analyzes requests against security criteria without centralizing control, allowing the network to maintain decentralization while filtering harmful data through an additional security checkpoint.
2Measurement precision
If comprehensive security scanning is performed on all network function requests, then detection precision of fraudulent data is improved, but processing time and computational overhead increase
Solution Approach 1:
The security scanning system applies different levels of inspection to different parts of the blockchain data structure. Critical elements such as wallet addresses, smart contract bytecode, and transaction patterns receive intensive scanning with detailed security criteria, while other less critical data elements receive lighter or selective scanning, optimizing the balance between detection precision and processing time.
Solution Approach 2:
The system dynamically adjusts scanning parameters such as the depth of analysis, types of security criteria applied, and flagging thresholds based on the risk profile of the data being scanned. High-risk transactions or unfamiliar patterns trigger more comprehensive scanning, while routine transactions receive faster, lighter validation, thus adapting processing intensity to actual security needs.
3Reliability
If multiple security criteria are applied to scan network function requests, then reliability of security detection is improved, but device complexity of the scanning system increases
Solution Approach 1:
The security criteria are segmented into distinct, modular categories such as wallet address validation rules, smart contract security checks, transaction pattern analysis, and data format verification. Each segment can be independently configured, executed, and maintained, allowing the system to apply multiple criteria reliably while managing complexity through modular architecture.
Solution Approach 2:
The scanning system employs universal security criteria that can be applied across multiple types of blockchain operations and data structures. A single security criterion framework serves multiple functions by validating different elements (transactions, contracts, wallets) using consistent rules, thereby improving reliability through uniform application while reducing overall system complexity through reuse.
4Stability of the object's composition
If suspicious data is flagged and isolated before blockchain addition, then integrity of the blockchain is improved, but productivity of network operations decreases
Solution Approach 1:
The system performs preliminary flagging and isolation of suspicious data elements before they are committed to the blockchain. By identifying and quarantining potentially fraudulent transactions, wallet addresses, or contract operations in advance, the system ensures that only validated data enters the blockchain, maintaining integrity while allowing legitimate operations to proceed without delay through parallel processing of confirmed safe transactions.
Data Source
AI summary
Methods, systems, and apparatuses for blockchain-based unexpected data detection are described herein. In some arrangements, a node within a decentralized peer-to-peer (e.g., P2P) network may receive a plurality of network function requests corresponding to the decentralized network. The node may analyze the plurality of network function requests to identify whether the requests included unexpected data and/or irregular data, and/or are associated with flagged wallets and/or smart contracts.