Stripe Inc. (20240273535). COMPUTER MODELING FOR FRAUD DETECTION IN BLOCKCHAIN-BASED TRANSACTIONS simplified abstract

COMPUTER MODELING FOR FRAUD DETECTION IN BLOCKCHAIN-BASED TRANSACTIONS

Organization Name

Stripe Inc.

Inventor(s)

Sen Forest Fang of South San Francisco CA (US)

Brendan Ryan of South San Francisco CA (US)

COMPUTER MODELING FOR FRAUD DETECTION IN BLOCKCHAIN-BASED TRANSACTIONS - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240273535 titled 'COMPUTER MODELING FOR FRAUD DETECTION IN BLOCKCHAIN-BASED TRANSACTIONS

Simplified Explanation

The patent application describes systems and methods for detecting fraud in blockchain-based transactions using a computer model trained on transaction protocols.

• The server detects interactions with blockchain transactions and calculates a risk score based on predefined characteristics.
• If the risk score exceeds a threshold, the system alerts the user through a graphical user interface about the potential risk associated with the transaction.

Key Features and Innovation

• Detection of fraud in blockchain transactions.
• Utilization of a computer model trained on transaction protocols to assess risk.
• Real-time alerts to users about potential risks associated with transactions.

Potential Applications

This technology can be applied in various industries such as finance, e-commerce, and supply chain management to enhance security and prevent fraudulent activities in blockchain transactions.

Problems Solved

• Mitigating fraud in blockchain transactions.
• Providing users with real-time risk assessment for their transactions.
• Enhancing security and trust in blockchain-based systems.

Benefits

• Improved security in blockchain transactions.
• Prevention of fraudulent activities.
• Increased trust and transparency in digital transactions.

Commercial Applications

Title: Fraud Detection System for Blockchain Transactions This technology can be utilized by financial institutions, e-commerce platforms, and supply chain companies to safeguard transactions, build trust with customers, and enhance overall security in digital transactions.

Prior Art

Readers can explore prior research on fraud detection in blockchain transactions, machine learning models for risk assessment, and security measures in decentralized systems to gain a deeper understanding of the technology landscape.

Frequently Updated Research

Researchers are continuously exploring advancements in fraud detection algorithms, machine learning models for risk assessment, and blockchain security protocols to further enhance the effectiveness of fraud detection systems in blockchain transactions.

Questions about Blockchain Fraud Detection

How does the computer model determine the risk score for blockchain transactions?

The computer model calculates the risk score based on predefined characteristics of transaction protocols and historical data of electronic transactions.

What are the potential implications of real-time alerts for users in blockchain transactions?

Real-time alerts can help users make informed decisions and take immediate action to prevent potential fraud in their transactions.

Original Abstract Submitted

disclosed herein are systems and methods for identifying fraud in blockchain-based transactions. in one method, a server detects an interaction by a decentralized digital wallet with a first electronic transaction protocol corresponding to a blockchain; executes a computer model (previously trained based on characteristics of electronic transaction protocols corresponding to the blockchain and electronic transactions corresponding to electronic transaction protocols) to determine a risk score; and in response to determining that the risk score for the requested electronic transaction is above a threshold level, causing at least one graphical element of a gui associated with the decentralized digital wallet to provide an indication of a risk associated with the requested electronic transaction.