Network Traffic Analysis for Targeted Household Services
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Solution Overview
Problem
Current solutions lack the capability to provide targeted services to customers based on reliable network traffic data analysis, failing to effectively utilize network traffic data for personalized and optimized service delivery.
Innovation Solution
A method involving network traffic data analysis, where features are engineered from raw data to identify household clusters and associate them with persona identifiers, enabling targeted services by processing and visualizing network traffic data to provide tailored support and security measures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If network traffic data is collected and analyzed to enable targeted services, then service personalization and customer experience are improved, but data privacy and security risks increase
Solution Approach 1:
The patent extracts and removes personally identifiable information from network traffic data through anonymization processes. Personal identifiers are stripped away while retaining behavioral patterns and traffic characteristics necessary for service personalization, thus enabling targeted services while protecting data privacy.
Solution Approach 2:
The patent introduces an intermediary anonymization layer between raw network traffic data and service delivery systems. This intermediary process transforms raw data into anonymized datasets that maintain analytical value for personalization while eliminating direct privacy risks through intermediate processing.
2Productivity
If household clusters are identified through network traffic analysis, then targeted service delivery is improved, but system complexity and processing requirements increase
Solution Approach 1:
The patent segments the population into distinct household clusters based on anonymized network traffic patterns. By dividing the data processing task into cluster-based segments rather than individual-level analysis, the system achieves efficient targeted service delivery while reducing overall processing complexity through aggregation.
Solution Approach 2:
The patent performs preliminary clustering and anonymization of network traffic data before service delivery. By pre-processing and segmenting households into clusters in advance, the system eliminates the need for complex real-time analysis during service delivery, thus improving efficiency while managing processing requirements.
Data Source
AI summary
A method includes receiving network traffic data relating to one or more devices of a plurality of home networks, wherein each home network of the plurality of home networks relates to a respective household. The method further includes determining one or more household related features by feature engineering the network traffic data, wherein the one or more household related features are related to one or more of: a device property, a security threat event, and an application usage, associating, in a database, the one or more household related features with identification data assigned to each household, identifying household clusters that represent groups of households comprising a predetermined number of common household related features, and providing a targeted service to a customer based on a household cluster associated with a household of the customer.