Data Anonymization Module for Cloud Transmission Security
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Solution Overview
Problem
As more enterprises use third-party hosted applications, there is a need for efficient data security measures to protect data from unauthorized access, particularly in cloud computing environments where data is transmitted and stored across networks.
Innovation Solution
A method and system for anonymizing data transmitted to a destination computing device by modifying clear data to include a delimiter and pad data, ensuring a predefined character length, and using an anonymization module to generate anonymized data, which can be de-anonymized upon retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If data is transmitted in clear format to third-party hosted applications, then data transmission is simple and fast, but data security and protection from unauthorized access deteriorates
Solution Approach 1:
The system performs preliminary anonymization of data before transmission to the third-party hosted application. The anonymization module transforms clear data into anonymized data in advance, so that when data is transmitted, it is already protected. This resolves the contradiction by preparing security measures beforehand without slowing down the actual transmission process.
Solution Approach 2:
The anonymization module acts as an intermediary between the data source and the third-party application. It sits in the data flow path, transforming clear data into anonymized data before it reaches the destination. This intermediary layer provides security protection while maintaining the simplicity and speed of data transmission to the hosted application.
2Object-affected harmful factors
If data is anonymized before transmission, then data security is improved, but data processing complexity and transmission time increases
Solution Approach 1:
The system creates a copy of the data structure for anonymization purposes. The anonymization module works on a copy of the clear data, transforming it into anonymized data without affecting the original data structure. This copying approach simplifies the processing complexity by allowing independent transformation while maintaining data integrity.
Solution Approach 2:
The anonymization process changes parameters of the data such as formatting, encoding, or transformation rules rather than fundamentally altering the data structure. By modifying data parameters in a controlled manner, the system achieves security enhancement with minimal increase in processing complexity.
3Object-affected harmful factors
If data is anonymized before transmission, then data security is improved, but the ability to retrieve and use original data deteriorates
Solution Approach 1:
The system implements a feedback mechanism where anonymized data is transmitted to the third-party application, processed, and then returned. The original clear data can be retrieved through the feedback loop, allowing the system to maintain both security during transmission and usability for retrieval. The feedback mechanism ensures that information loss does not occur.
Solution Approach 2:
The anonymization is performed preliminarily before transmission, allowing the original clear data to be preserved and retrieved later. By preparing the anonymized version in advance without destroying the original, the system maintains the ability to retrieve and use the original data when needed, thus preventing information loss.
Data Source
AI summary
A method and system for anonymizing data to be transmitted to a destination computing device is disclosed. Anonymization strategy for data anonymization is provided. Data to be transmitted is received from a user computer. Selective anonymization of the data is performed, based on the anonymization strategy, using an anonymization module. The data includes a plurality of characters and defines a clear data. A modified clear data with number of characters greater than the clear data is formed using the clear data, a delimiter data and a pad data. The modified clear data is anonymized to derive an anonymized data. The anonymized data is transmitted to the destination computer over a network. In one embodiment, a portion of the pad data is selected as a seed value to generate an initialization vector to anonymize the clear data.