MEMS Accelerometer Acoustic Injection Defense via Randomized Sampling
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Solution Overview
Problem
MEMS accelerometers are vulnerable to acoustic interference, which can lead to denial of service attacks and unauthorized control of sensor outputs, as existing defense mechanisms are either impractical, not applicable, or insufficient in mitigating these threats.
Innovation Solution
Designing MEMS sensors with secure signal conditioning components and implementing software solutions such as randomized sampling and 180° out-of-phase sampling to mitigate acoustic interference, thereby preventing output biasing and output control attacks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If acoustic dampening materials are applied to sensors, then protection against acoustic interference is improved, but packaging size increases
Solution Approach 1:
The patent replaces mechanical/acoustic defense mechanisms (acoustic dampening materials) with an electronic/software-based solution (randomized sampling). Instead of physically blocking acoustic waves, the system uses randomized sampling frequencies to prevent acoustic resonance from corrupting sensor readings, thereby solving the contradiction by substituting a mechanical defense with an electronic one that consumes no additional physical space.
2Reliability
If secure signal conditioning components are used in MEMS sensor design, then vulnerability to acoustic injection attacks is reduced, but device complexity increases
Solution Approach 1:
The patent changes the sampling frequency parameter dynamically and randomly, rather than using a fixed sampling rate. This parameter change approach prevents acoustic resonance attacks without requiring additional hardware components, as the existing signal conditioning components continue to function normally while the randomized sampling parameter disrupts the resonance condition that attackers exploit.
3Measurement precision
If traditional filtering methods are applied to sensor output, then noise reduction is improved, but ability to filter out all interference is insufficient
Solution Approach 1:
The patent introduces dynamics into the previously static sampling process by continuously varying the sampling frequency in a randomized manner. Traditional filters are static with fixed cutoff frequencies, but the randomized sampling creates a dynamic system that adapts to prevent resonance attacks. This dynamic approach maintains noise reduction capabilities while adding the ability to counteract interference that static filters cannot eliminate.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
These solutions effectively reduce the vulnerability of MEMS accelerometers to acoustic interference, making it harder for attackers to manipulate sensor outputs and ensuring the integrity of motion data in cyber-physical systems.
Implementation Method 1
Acoustic waves propagate through the air, and exhibit forces on physical objects in their path. If the acoustic frequency is tuned correctly, it can vibrate the accelerometer's sensing mass, altering the sensor's output in a predictable way.
Implementation Method 2
If the acoustic frequency is tuned correctly, it can vibrate the accelerometer's sensing mass
Implementation Method 3
sampling the output signal at a sampling frequency, where the sampling frequency is less than or equal to the known resonant frequency and sample time for each sample is chosen randomly
Implementation Method 4
every other sample is taken at 180 degrees phase delay with respect to the known resonant frequency and forms a sample pair; determining an output sample for each sample pair by averaging the samples forming a given sample pair
Data Source
AI summary
Cyber-physical systems depend on sensors to make automated decisions. Resonant acoustic injection attacks are already known to cause malfunctions by disabling MEMS-based gyroscopes. However, an open question remains on how to move beyond denial of service attacks to achieve full adversarial control of sensor outputs. This work investigates how analog acoustic injection attacks can damage the digital integrity of a popular type of sensor: the capacitive MEMS accelerometer. Spoofing such sensors with intentional acoustic interference enables an out-of-spec pathway for attackers to deliver chosen digital values to microprocessors and embedded systems that blindly trust the unvalidated integrity of sensor outputs. Two software-based solutions are presented for mitigating acoustic interference with output of a MEMS accelerometer and other types of motion sensors.