Business Logic Protection via Tracking Code Analysis

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Solution Overview

Problem

Existing business logic protection methods are inefficient and resource-intensive due to complex authentication processes, failing to effectively prevent vulnerabilities in complex business systems.

Innovation Solution

A big-data-based business logic learning method and apparatus that identifies and updates procedure direction tables by parsing network requests, distributing tracking codes with request identifiers and timestamps, and restarting business logic processes when deviations are detected, thereby improving protection efficiency and adaptability.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If multiple verifying or manual verifying measures are used to protect business logic, then security protection is provided, but resource consumption increases and protection efficiency decreases

Engineering Contradiction:

Improvebusiness logic protectionVSAvoidprotection efficiency

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system performs preliminary learning of normal business logic procedures in advance through tracking codes and procedure direction tables. By pre-establishing what constitutes normal behavior patterns, the system can quickly validate requests without complex real-time verification, thus improving protection efficiency while maintaining security.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system creates a virtual model of normal business logic procedures by copying and analyzing tracking data from multiple requests. This virtual model (procedure direction table) serves as a reference for validation, replacing the need for complex manual verification processes while maintaining protection reliability.

Inventive Principle:

Principle #26Copying

2Reliability

If multiple verifying or manual verifying measures are used to protect business logic, then security protection is provided, but resource consumption increases

Engineering Contradiction:

Improvebusiness logic protectionVSAvoidresource consumption

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The system automatically learns and updates normal business logic patterns through tracking codes embedded in requests. This self-learning mechanism eliminates the need for continuous manual verification configuration, reducing resource consumption while maintaining protection effectiveness.

Inventive Principle:

Principle #25Self-service

3Reliability

If complex authentication processes are used for business logic protection, then security is improved, but user experience is degraded

Engineering Contradiction:

Improvebusiness logic protectionVSAvoiduser experience

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The system extracts only the essential validation logic from complex authentication processes. By separating the core procedure validation from unnecessary authentication steps, the system maintains security while significantly improving user experience through simpler, faster request processing.

Inventive Principle:

Principle #2Taking out (Extraction)

4Adaptability or versatility

If big data-based learning is performed to obtain normal requesting procedures, then adaptability to changing business logic is improved, but system complexity increases

Engineering Contradiction:

Improveadaptability to business logic changesVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentEP3585034B1Big data-based method for learning and protecting service logic and device for learning and protection

Publication Date: 2021.04.07 CHINANETCENT TECH

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AI summary

The present disclosure discloses methods and apparatuses for learning and protecting business logic based on big data. The learning method includes: receiving a network request sent by a requester, recognizing a current request identifier of the network request, and parsing procedure information of the network request; extracting a reference request identifier from the procedure information, determining whether a direction from the reference request identifier to the current request identifier exists in a procedure direction table, and updating the procedure direction table based on a determination result; and distributing tracking code for the network request, where the tracking code includes the current request identifier and a timestamp for distributing the tracking code. The technical solutions provided in the present disclosure can improve efficiency of protecting business logic based on big data, can be applied to various business logic scenarios, and can flexibly adapt to various changes in business logic requirements.