NoisFre: Noise-Tolerant Memory Fingerprints from Commodity Devices for Security Functions

by   Yansong Gao, et al.

Given the ubiquity of memory in commodity electronic devices, fingerprinting memory is a compelling proposition, especially for low-end Internet of Things (IoT) devices where cryptographic modules are often unavailable. However, the use of fingerprints in security functions is challenged by the inexact reproductions of fingerprints from the same device at different time instances due to various noise sources causing, small, but unpredictable variations in fingerprint measurements. Our study formulates a novel and pragmatic approach to achieve the elusive goal of affording highly reliable fingerprints from device memories. We investigate the transformation of raw fingerprints into a noise-tolerant space where the generation of fingerprints from memory biometrics is intrinsically highly reliable. Further, we derive formal performance bounds to support practitioners to adopt our methods for practical applications. Subsequently, we demonstrate the expressive power of our formalization by using it to investigate the practicability of extracting noise-tolerant fingerprints from commodity devices. We have employed a set of 38 memory chips including SRAM (69,206,016 cells), Flash (3,902,976 cells) and EEPROM (32,768 cells) ubiquitously embedded in low-end commodity devices from 6 different manufacturers for extensive experimental validations. Our results demonstrate that noise-tolerant fingerprints – achieving a key failure rate less than 10^-6 – can always be efficiently afforded from tested memories with a solely fingerprint snap-shot enrollment. Further, we employ a low-cost wearable Bluetooth inertial sensor and demonstrate a practical, end-to-end implementation of a remote attestation security function built upon a root key from noise-tolerant SRAM fingerprints generated on demand and at run-time.



There are no comments yet.


page 4

page 11

page 15


Building Secure SRAM PUF Key Generators on Resource Constrained Devices

A securely maintained key is the premise upon which data stored and tran...

Injecting Reliable Radio Frequency Fingerprints Using Metasurface for The Internet of Things

In Internet of Things, where billions of devices with limited resources ...

A Proof of Concept SRAM-based Physically Unclonable Function (PUF) Key Generation Mechanism for IoT Devices

This paper provides a proof of concept for using SRAM based Physically U...

A lightweight cryptography (LWC) framework to secure memory heap in Internet of Things

The extensive networking of devices and the large amount of data generat...

RBNN: Memory-Efficient Reconfigurable Deep Binary Neural Network with IP Protection for Internet of Things

Though deep neural network models exhibit outstanding performance for va...

Hardware Implementation of Keyless Encryption Scheme for Internet of Things Based on Image of Memristors

The Internet of Things (IoT) is rapidly increasing the number of connect...

Radio Frequency Fingerprint Identification Based on Denoising Autoencoders

Radio Frequency Fingerprinting (RFF) is one of the promising passive aut...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.