Mobile PRNG Seeding Using Sensor Entropy Accumulation
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Solution Overview
Problem
Mobile devices face challenges in generating high-quality random data due to limited entropy sources, making them vulnerable to cryptanalytic attacks, as existing pseudorandom number generators (PRNGs) rely on insufficient randomization.
Innovation Solution
A method is described for collecting and processing raw sensor data from mobile devices to generate a high-quality seed for PRNGs by combining selected subsets of raw data with accumulated entropy, using cryptographic hash functions and accumulation operations to enhance security and randomness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional pseudorandom number generators are used on mobile devices, then device complexity is reduced, but security strength deteriorates due to limited entropy sources
Solution Approach 1:
The patent combines multiple entropy sources (accelerometer, gyroscope, magnetometer, ambient light sensor, proximity sensor) into a unified entropy pool. This merging of diverse sensor data streams creates high-entropy seed material that overcomes the limitation of individual entropy sources, directly addressing the security strength issue while utilizing existing device components.
Solution Approach 2:
The patent makes existing sensors serve a dual function: their primary measurement function and an additional entropy collection function. By extracting randomization potential from sensors already present in mobile devices, the system achieves enhanced security without adding dedicated hardware entropy sources, thus managing device complexity effectively.
2Reliability
If more entropy sources are added to mobile devices, then security strength is improved, but device complexity increases
Solution Approach 1:
The patent enables mobile devices to generate their own high-quality entropy using their existing sensors and environmental interactions. The device serves itself by collecting entropy from its own operational sensors (accelerometer during movement, gyroscope during rotation, magnetometer detecting field variations) without requiring external entropy sources or additional dedicated hardware, thus improving security while avoiding increased device complexity.
3Reliability
If sensor data is collected continuously for entropy generation, then quality of random data is improved, but energy consumption increases
Solution Approach 1:
The patent implements periodic entropy collection by triggering sensor data acquisition based on device events (screen on/off, app transitions, user interactions) rather than continuous collection. This periodic approach maintains entropy quality by gathering data at meaningful intervals while significantly reducing energy consumption compared to continuous sampling, directly addressing the energy-quality tradeoff.
Data Source
AI summary
A method for operating a pseudorandom generator is disclosed. The method may be implemented by a processor of a mobile computing device. The method includes: collecting raw sensor data from at least one sensor associated with the mobile computing device; selecting a subset of the raw sensor data; retrieving first representation representing accumulated entropy associated with one or more previously acquired raw sensor data sets for the at least one sensor; and generating a seed for a pseudorandom generator based on combining the first representation and the selected subset of raw sensor data.