Name: PLC Hardware Discrimination Using RF-DNA Fingerprinting (en Inglés)
SKU: 58502994
Price: 44.81 USD
Availability: InStock
Author: Air Force Institute of Technology
ISBN: 9781511581912

portada PLC Hardware Discrimination Using RF-DNA Fingerprinting (en Inglés)

PLC Hardware Discrimination Using RF-DNA Fingerprinting (en Inglés)

Formato

Libro Físico

Autor

Air Force Institute of Technology

Editorial

Createspace

Idioma

Inglés

N° páginas

Encuadernación

Tapa Blanda

Dimensiones

27.9x21.6x0.5 cm

Peso

0.27 kg.

ISBN13

9781511581912

Categorías

Tecnología: cuestiones generales

PLC Hardware Discrimination Using RF-DNA Fingerprinting (en Inglés)

Air Force Institute of Technology (Autor) · Createspace · Tapa Blanda

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Reseña del libro "PLC Hardware Discrimination Using RF-DNA Fingerprinting (en Inglés)"

Programmable Logic Controllers are used to control and monitor automated process in many Supervisory Control and Data Acquisition (SCADA) critical applications. As with virtually all electronic devices, PLCs contain Integrated Circuits (IC) that are often manufactured overseas. ICs that have been unknowingly altered (counterfeited, manufactured with hardware Trojans, etc.) pose a significant security vulnerability. To mitigate this risk, the RF-Distinct Native Attribute (RF-DNA) fingerprinting process is applied to PLC hardware devices to augment bit-level security. RF-DNA fingerprints are generated using two independent signal collection platforms. Two different classifiers are applied for device classification. A verification process is implemented for analysis of Authorized Device Identification and Rogue Device Rejection. Fingerprint feature dimensional reduction is evaluated both Qualitatively and Quantitatively to enhance experimental-to-operational transition potential. The findings of this research are that the higher quality signal collection platform had a classification performance gain of approximately 10dB SNR. Performance of the classifiers varied between signal collection platforms, and alsowith the application of fingerprint dimensional reduction. The lower quality signal collection platform saw a maximum gain of 5dB SNR using reduced dimensional feature sets compared against the full dimensional feature set.