IoT Household Association Using Privacy-Preserving Deployment Hashes
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Solution Overview
Problem
Existing IoT devices are often self-installed by users without providing deployment information to the IoT vendor, leading to unknown associations with households, which complicates service management and billing, and may result in security vulnerabilities.
Innovation Solution
IoT devices generate deployment-specific hashes based on network credentials and MAC addresses to approximate a household ID, allowing the IoT vendor to track device associations while maintaining user privacy, and use authorization methods to manage access and detect anomalies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If IoT devices are treated as separate accounts to avoid management complexity, then device tracking becomes simpler, but billing and service optimization become less effective
Solution Approach 1:
The patent introduces a household identifier as an intermediary that links multiple IoT devices to a single household account. This mediator enables the system to track device associations without requiring direct account management for each device, thus maintaining low complexity while enabling effective billing and service optimization at the household level.
Solution Approach 2:
The household identifier serves multiple functions simultaneously: it groups devices for billing purposes, enables service optimization at the household level, and maintains privacy by not exposing individual device accounts. This multi-functionality resolves the contradiction by making the association mechanism versatile rather than specialized for a single purpose.
2Productivity
If deployment information is collected to track device associations, then billing and service optimization improve, but user privacy is compromised
Solution Approach 1:
The patent extracts only the essential deployment information needed for service optimization - specifically the household identifier and device association data - while leaving out sensitive user information. This selective extraction enables service improvement without compromising user privacy, as the collected data is sufficient for billing and optimization but insufficient for identifying individual users.
Solution Approach 2:
The patent transforms sensitive deployment information into anonymized parameters. By converting raw deployment data into household identifiers and hash values, the system changes the parameter representation from personally identifiable information to aggregated statistical data that maintains utility for service optimization while protecting user privacy.
3Device complexity
If multiple IoT devices are considered a single household, then billing becomes simpler, but the IoT vendor remains unaware of device deployment
Solution Approach 1:
The patent segments the information architecture into two distinct layers: a simplified billing layer that treats multiple devices as a single household, and a detailed deployment layer that tracks individual device associations. This segmentation allows the vendor to maintain simple billing processes while simultaneously acquiring comprehensive deployment information through the household identifier mechanism.
Data Source
AI summary
Techniques for enabling the association of client devices to anonymized households during an authorization process is performed at a server including processor(s) and non-transitory memory. The server receives a request for a service or content from a client device that specifies a device identifier, a first hash value approximating a unit in which the client device is deployed, and a second hash value representing a connection to the unit. The server records and evaluates the request based on the device identifier, the first hash value, and the second hash value so that an access token is generated for the client device and bound to the first hash value. The server sends the access token to the client device for access to the service or content via the connection to the unit upon validating the request or reports an anomaly determined based on the recorded data.