Classification results for independent trials are presented in terms of mean and standard deviation of classification accuracy as well as confusion matrix
📌 3 Key Takeaways
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Objective & Hypothesis:Physical layer identification systems classify the wireless devices by exploiting some distinctive device characteristics which can be measured from transmissions.
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Key Findings & Data:Classification performance of the features is evaluated through experimental data.
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Conclusion & Impact:Classification results for independent trials are presented in terms of mean and standard deviation of classification accuracy as well as confusion matrix
🔬Design:Article
📍Scope:Comprehensive Sample
⚙️Variables:Wireless device identification · transient signal · descriptive statistics
Abstract
Physical layer identification systems classify the wireless devices by exploiting some distinctive device characteristics which can be measured from transmissions. In this paper, characteristic features based on descriptive statistics are extracted from the transient part of the received WiFi signals for classification purpose. Classification performance of the features is evaluated through experimental data. Feature sets consisting of combinations of descriptive statistics are tested in order to evaluate the distinctiveness of statistics which measures the central tendency and dispersion of data. Classification results for independent trials are presented in terms of mean and standard deviation of classification accuracy as well as confusion matrix
Köse, M., Taşcıoğlu, S., Telatar, Z. (2015). WIRELESS DEVICE IDENTIFICATION USING DESCRIPTIVE STATISTICS. Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering, Volume: 57 Issue: 1. https://doi.org/10.1501/commua1-2_0000000083