Data Packet Classification Using Sender-Recipient Relationship Metrics
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Solution Overview
Problem
Existing data transmission systems face inefficiencies in processing and analyzing data packages due to resource-intensive security checks, leading to user frustration and increased risk of threats.
Innovation Solution
A framework utilizing classifiers and databases to determine relationship metrics between senders and recipients based on communication history, enabling quick and efficient handling of data packages by applying appropriate actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If comprehensive security checks and property analysis are performed on data packages, then security and threat detection are improved, but processing time and resource consumption increase
Solution Approach 1:
The system performs preliminary actions by pre-calculating and storing relationship metrics between senders and recipients in a database before data packages are transmitted. When a data package is received, the system simply queries the pre-computed relationship metric rather than performing comprehensive analysis in real-time, thus resolving the contradiction between thorough security checks and processing speed.
2Reliability
If comprehensive security checks and property analysis are performed on data packages, then security and threat detection are improved, but resource consumption increases
Solution Approach 1:
The system performs the computationally intensive analysis of sender-recipient relationships in advance, storing the results as relationship metrics in a database. This preliminary action eliminates the need to repeat resource-intensive analysis for each incoming data package, significantly reducing real-time resource consumption while maintaining security.
3Productivity
If relationship metrics based on communication history are used to classify data packages, then processing efficiency is improved, but system complexity increases
Solution Approach 1:
The system introduces an intermediary component - a database storing pre-computed relationship metrics between senders and recipients. This intermediary layer simplifies the classification process by providing ready-to-use trust indicators, avoiding the need for complex real-time analysis while improving processing efficiency.
Data Source
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AI summary
A method, system and non-transitory computer-readable medium for classifying a received data package (100), using a framework (200). The framework (200) comprises at least one classifier (230), a processing component (220) for processing the received data package (100) using the at least one classifier (230), and a database (240, 1430) for storing at least relationship data (1320) indicating a plurality of relationships between a sender (1410) and at least one recipient (1480). The classifier is configured to obtain (1210) header data (110) of the received data package (100), the header data (110) comprising at least user identifiers corresponding to at least the sender (1410) and the at least one recipient (1480), and to obtain (1220) data representing a relationship between the sender (1410) and the at least one recipient (1480) from the database (240,1430). A relationship metric is determined (1230) based on the relationship, wherein the relationship is indicative of at least a previous communication history between the sender (1410) and the at least one recipient (1480). A handling action (1340A, 1340B, 1340C) is then applied (1240) to the received data package (100) based on the relationship metric, and the relationship data between the sender (1410) and the at least one recipient (1480) in the database (240, 1430) is updated (1250) based on the received data package (100).