Work

Intrusion Detection for IoT Devices based on RF Fingerprinting using Deep Learning

Year: 2019

Type: conference-paper

Source: International Conference on Fog and Mobile Edge Computing (FMEC)

DOI: 10.1109/fmec.2019.8795319

Authors: Joshua Bassey, Damilola Adesina, Xiangfang Li, Lijun Qian, Alexander Aved, Timothy Kroecker

Institutions: Texas A&M University System, United States Air Force Research Laboratory, Rome Laboratory, U.S. Air Force Research Laboratory Information Directorate

Language: English

Topic: Wireless Signal Modulation Classification

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: closed

OpenAlex ID: W2968197850

FWCI: 2.529

Cites: 20

Cited by: 66

Related to: 10