Abstract
Mining useful patterns from databases is an important research topic. The research in utility mining mostly focuses on discovering patterns of high value in large databases, and analyzing the important factors in a data mining process. This idea is applied to the wireless device identification in this paper. Radio Frequency Fingerprint (RFF) reflects differences between transmitter hardware components. It contains rich non-linear characteristics of the internal components of the transmitter. Small differences and inaccuracies in the manufacturing process determine the unique characteristic contained in the transmitted signal. The device can be identified by the signal transmitted by the wireless device. In this paper, the generation mechanism of RFF is analyzed and two pattern mining algorithms are used to extract useful information from wireless signals for device identification. Then, a real communication transmitter link is established to study the effect of different components of a transmitter. The signals are acquired from the transmitters with different components replaced, including the amplifier, the bandpass filter, and the local oscillator. Finally, the influence of different components and pattern mining methods are evaluated.
Highlights
Pattern mining is a kind of data mining
There are many related research on Radio Frequency (RF) fingerprinting, most of them mainly focus on the use of advanced signal processing methods to extract the difference information of individual characteristics of radiation sources by experience, without selecting effective features based on the generation mechanism of RF fingerprints
THE GENERATION MECHANISM OF Radio Frequency Fingerprint (RFF) At the transmitter side, RFF is rooted in the hardware imperfections of the transmitter device [25], which include clock jitter [26], [27], the digital-to-analog converters (DAC) sampling error [28], the mixer or local frequency synthesizer [29]–[31], the power amplifier (PA) non-linearity [32]–[34], device antenna [35], and so on
Summary
Data mining refers to the analysis process of finding valuable patterns or information from a large amount of data. It includes knowledge such as artificial intelligence, machine learning, statistics, and databases. Pattern mining methods are used to extract useful features form transmitter signals. There are many related research on RF fingerprinting, most of them mainly focus on the use of advanced signal processing methods to extract the difference information of individual characteristics of radiation sources by experience, without selecting effective features based on the generation mechanism of RF fingerprints. This paper starts with the analysis of the generation mechanism of RFF, the utility pattern mining technique is used to better mine features in the problem of device identification to FIGURE 1.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
