Intelligent Data Processor for API Personal Information Leakage Detection
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Solution Overview
Problem
Online service providers face challenges in preventing the leakage of sensitive personal information through API calls due to sophisticated hacking and malicious computing attacks, which can lead to data breaches and fraud.
Innovation Solution
An intelligent data processor is configured with rules to detect and mask personal information in computing code, tracing API requests to determine sensitivity levels and applying masking policies to prevent data leakage during API transmissions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If robust detection methods are implemented to prevent data leakage through API calls, then data security is improved, but system complexity increases
Solution Approach 1:
The patent applies preliminary action by implementing code analysis and vulnerability detection before data is actually transmitted through APIs. The system scans computing code configurations, identifies sensitive data elements, and detects potential leakage paths in advance, allowing security measures to be put in place before breaches can occur. This proactive approach improves data security without requiring complex real-time intervention systems.
Solution Approach 2:
The patent introduces an intermediary component that acts as a mediator between the computing code and the data transmission process. This intermediary layer analyzes code configurations, identifies sensitive data, and controls API calls to prevent leakage. By placing this intermediary detection layer, the system achieves robust security without making the entire system fundamentally more complex, as the intermediary operates as a separate modular component.
2Reliability
If sophisticated hacking attacks are anticipated and defended against, then data protection is improved, but detection difficulty increases
Solution Approach 1:
The system performs preliminary code analysis and vulnerability scanning before malicious attacks occur. By pre-identifying sensitive data elements and potential leakage paths in computing code configurations, the system is prepared to detect and prevent sophisticated hacking attempts without needing to complexly analyze attack patterns in real-time. This upfront detection preparation reduces the difficulty of detecting advanced threats during actual attacks.
Data Source
AI summary
There are provided systems and methods for detecting leakage of personal information in computing code configurations. A service provider, such as an electronic transaction processor for digital transactions, may utilize one or more computing systems and architectures to provide services to users. These may utilize applications, decision services, and microservices that invoke different application programming interfaces (APIs). When computing code is provided or changed, use of certain APIs may risk data leakage or misappropriation. Thus, the service provider may utilize an intelligent data processor to determine if these APIs are used in the computing code, and if so, back-trace through the computing code to determine the data objects used in API calls and requests. Thereafter, the service provider may determine whether sensitivity levels of the personal information are impacted by the APIs use of the personal information and may mask data that may be impacted.