Anonymized MAC Address Generation for Cloud Privacy
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Solution Overview
Problem
Existing technologies fail to anonymize client identifying information, such as MAC addresses, for transmission outside a local network while ensuring uniqueness and compliance with privacy laws, as they are not allowed to be transmitted externally.
Innovation Solution
A method and system that generate anonymized MAC addresses using a hashing function, combining local network and cloud entity information, along with a random token and offset value, to create unique anonymized MAC addresses for each client station and external network entity, ensuring compliance with privacy laws by preventing the transmission of real MAC addresses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real MAC addresses are transmitted outside the local network, then cloud entities can identify and track client devices, but this violates privacy laws and regulations
Solution Approach 1:
The patent creates anonymized copies of MAC addresses through cryptographic hashing. The original MAC address is transformed into an anonymized version that preserves uniqueness and consistency properties while removing personally identifiable information. This allows cloud entities to track and identify client devices without receiving the actual MAC address, thus complying with privacy laws while maintaining the ability to recognize and differentiate client devices.
Solution Approach 2:
The patent introduces an anonymization function as an intermediary between the local network and external cloud entities. This function acts as a mediator that transforms the MAC address into an anonymized form before transmission. The intermediary preserves the essential identifying characteristics needed for cloud entities to recognize and track devices while filtering out the actual personal information, thus resolving the contradiction between identification and privacy compliance.
2Reliability
If anonymized MAC addresses are generated using hashing functions, then privacy compliance is achieved, but ensuring uniqueness and consistency across multiple cloud entities becomes complex
Solution Approach 1:
The patent employs a universal hashing function that serves multiple purposes simultaneously: it ensures privacy compliance through anonymization, guarantees uniqueness of client device identification, maintains consistency across different cloud entities, and enables deterministic regeneration of the same anonymized address. This single multi-functional approach simplifies the overall system complexity compared to using separate mechanisms for each requirement.
Solution Approach 2:
The patent transforms the MAC address by changing its parameters through cryptographic hashing. The original MAC address parameters are transformed into new parameters that maintain the uniqueness property while removing personally identifiable information. The hashing function changes the representation form while preserving the essential identification characteristics, achieving privacy compliance without sacrificing the ability to uniquely identify devices.
3Reliability
If different anonymized MAC addresses are generated for different cloud entities, then privacy is protected, but cloud entities cannot consistently identify the same client device across multiple networks
Solution Approach 1:
The patent performs preliminary anonymization of the MAC address using a deterministic hashing function before transmission to cloud entities. This preliminary action ensures that the same client device will consistently generate the same anonymized MAC address across different cloud entities and networks. The hashing is performed in advance, and the resulting anonymized address maintains consistency properties that enable cloud entities to recognize and track the same device across multiple contexts while protecting privacy.
Data Source
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AI summary
A method for anonymizing user identifiable information to be transmitted outside of a local network includes generating a network entity hash input based on (i) a first MAC address assigned to a client station of the local network, (ii) a second MAC address assigned to the network gateway device of the local network, and (iii) an identifier of a cloud entity of an external network to which data of the client station is to be transmitted. The method further includes generating a hash value output based on the network entity hash input and a random token value using a hashing function, generating an anonymized MAC address associated with the client station based on the hash value output, and transmitting the anonymized MAC address associated with the client station to the cloud entity of the external network.