Distributed Data Scanning Near Storage for Security Compliance
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Solution Overview
Problem
Conventional data storage systems face security risks and resource inefficiencies due to centralized data scanning and profiling, which require significant computational power and network bandwidth, and expose sensitive data to potential leaks.
Innovation Solution
Implementing serverless applications on local computing devices near data storage components to perform scanning and profiling operations, reducing reliance on centralized systems and minimizing network traffic, latency, and computational costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If centralized data scanning and profiling is used, then data security can be maintained through centralized control, but network bandwidth consumption increases and latency increases
Solution Approach 1:
The patent segments the centralized scanning function into distributed serverless applications deployed at multiple locations near data storage components. This segmentation allows scanning operations to occur locally without requiring all data to be transmitted to a central system, thereby reducing network bandwidth consumption while maintaining security through distributed control.
Solution Approach 2:
The patent implements local quality by deploying scanning and profiling capabilities locally near data storage components rather than centrally. Each local serverless application performs scanning operations on data in its vicinity, reducing the need for data transmission over the network and lowering bandwidth consumption while maintaining security through localized processing.
2Reliability
If centralized data scanning and profiling is used, then data security can be maintained through centralized control, but processing time increases due to network latency
Solution Approach 1:
The patent segments the centralized scanning function into distributed serverless applications deployed at multiple locations near data storage components. This segmentation allows scanning operations to occur locally without requiring all data to be transmitted to a central system, thereby reducing network latency and processing time while maintaining security through distributed control.
Solution Approach 2:
The patent implements local quality by deploying scanning and profiling capabilities locally near data storage components rather than centrally. Each local serverless application performs scanning operations on data in its vicinity, reducing the need for data transmission over the network and lowering processing time through localized processing.
3Reliability
If centralized data scanning and profiling is used, then comprehensive data security can be ensured, but computational resources are excessively consumed
Solution Approach 1:
The patent segments the centralized scanning function into distributed serverless applications deployed at multiple locations near data storage components. This segmentation allows scanning operations to occur locally without requiring all data to be transmitted to a central system, thereby reducing computational power consumption while maintaining security through distributed control.
Solution Approach 2:
The patent implements self-service by enabling local serverless applications to autonomously perform scanning and profiling operations on data in their vicinity without requiring constant centralized processing. Each local application serves itself by executing scanning tasks locally, reducing overall computational resource consumption while maintaining security through distributed autonomy.
4Measurement precision
If data is transmitted to centralized systems for scanning, then comprehensive analysis can be performed, but sensitive data exposure to potential leaks increases
Solution Approach 1:
The patent segments the centralized scanning function into distributed serverless applications deployed at multiple locations near data storage components. This segmentation allows scanning operations to occur locally without requiring all data to be transmitted to a central system, thereby reducing data exposure to potential leaks while maintaining analysis accuracy through distributed processing.
Solution Approach 2:
The patent implements local quality by deploying scanning and profiling capabilities locally near data storage components rather than centrally. Each local serverless application performs scanning operations on data in its vicinity, reducing the need for data transmission over the network and lowering data leak risk through localized processing while maintaining analysis accuracy.
Data Source
AI summary
Techniques are disclosed for performing scanning and profiling of stored data to identify the location of data entries that comprise sensitive data that require storage in accordance with enhanced security requirements. The techniques advantageously move a portion of the scanning and profiling operations closer to the data storage locations, and involve deploying processing resources near the locations at which the data is stored rather than relying solely upon centralizing processing at a separate location. This approach has the advantages of reducing network traffic and latency, which can help improve performance and reduce costs, and may also facilitate organizations to better take advantage of distributed computing architectures, which can scale more effectively than centralized processing.