Sensor Node Compressive Sensing for Energy-Efficient Encryption

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Solution Overview

Problem

Wireless sensor networks face energy efficiency and security challenges due to compute-intensive cryptographic algorithms and the inability to perform local signal analysis, leading to increased energy consumption and vulnerability to malicious attacks.

Innovation Solution

Implementing compressive sensing to enable energy-efficient encryption and inference on sensor nodes, allowing for secure and efficient data transmission by compressively sensing data, analyzing it locally, and then encrypting and hashing before sending to a base station, thereby reducing energy overhead and enhancing security.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If cryptographic algorithms are used for secure communication, then security is improved, but energy consumption increases significantly

Engineering Contradiction:

ImprovesecurityVSAvoidenergy consumption

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The patent applies preliminary action by performing compressive sensing and local inference on sensor data before transmission. This preprocessing reduces the data volume that requires encryption, thereby maintaining security while reducing the energy consumption of cryptographic operations. The compressed and analyzed data is then encrypted and transmitted to the base station.

Inventive Principle:

Principle #10Preliminary action

2Adaptability or versatility

If on-chip inference is performed, then local signal analysis capability is improved, but energy consumption increases

Engineering Contradiction:

Improvelocal signal analysis capabilityVSAvoidenergy consumption

Core Design Contradiction:

Adaptability or versatilityVSUse of energy by moving object

Solution Approach 1:

The patent extracts only the essential features and intelligence from sensor data through compressive sensing and local inference, rather than processing or transmitting all raw data. This extraction approach enables local signal analysis capability while minimizing energy consumption by reducing the computational burden and data transmission requirements.

Inventive Principle:

Principle #2Taking out (Extraction)

3Measurement precision

If data is transmitted without compression, then data quality is maintained, but transmission energy and processing overhead increase

Engineering Contradiction:

Improvedata qualityVSAvoidtransmission energy

Core Design Contradiction:

Measurement precisionVSLoss of energy

Solution Approach 1:

The patent changes the parameter of data representation by applying compressive sensing transformations. This transforms the data from the original domain to a compressed domain while preserving the essential information needed for accurate reconstruction and analysis. The compression reduces transmission energy while maintaining data quality through mathematical transformations that preserve critical signal characteristics.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS11783060B2System and method for energy efficient sensors with compression, artificial intelligence, and security

Publication Date: 2023.10.10 THE TRUSTEES OF PRINCETON UNIV

AI summary

Devices and methods for processing detected signals at a detector using a processor are provided. The system involves (i) a data compressor that implements an algorithm for converting a set of data into a compressed set of data, (ii) a machine learning (ML) module coupled to the data compressor, the ML module transforming the compressed set of data into a vector and filtering the vector, (iii) a data encryptor coupled to the ML module that encrypts the filtered vector, and (iv) an integrity protection module coupled to the ML module, wherein the integrity protection module protects the integrity of the filtered vector.