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Iranian Journal of Electrical and Electronic Engineering، جلد ۱۹، شماره ۱، صفحات ۲۵۸۴-۲۵۸۴
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عنوان انگلیسی Improving Cross Ambiguity Function Using Image Processing Approach to Detect GPS Spoofing Attacks
چکیده انگلیسی مقاله The Global Positioning System (GPS) is vulnerable to various deliberate and unintentional interferences. Therefore, identifying and coping with various interferences in this system is essential. This paper analyzes a method of reducing the dimensions of Cross Ambiguity Function (CAF) images in improving the identification of spoofing interference at the GPS using Multi-Layer Perceptron Neural Network (MLP NN) and Convolutional Neural Network (CNN). Using the proposed method reduces data complexity, which can reduce the number of learning data requirements. The simulation results indicate that, by applying the proposed image processing algorithm for different dimensions of CAF images, the CNN performs better than MLP NN in terms of training accuracy; the MLP NN is superior to CNN in terms of convergence speed of training. In addition, the results demonstrate that the operation of the proposed method is appropriate in the case of small-delay spoofed signals. Therefore, for the intervals above 0.25 code chip, the proposed method detects spoofing attacks with a correct detection probability close to one.
کلیدواژه‌های انگلیسی مقاله CAF, GPS, GPS Spoofing Attack, Latent Semantic Analysis, Neural Networks.
نویسندگان مقاله | K. Zarrinnegar
School of Electrical Engineering, Iran University of Science and Technology (IUST), Narmak, Tehran 16846-13114, Iran.


| S. Tohidi
School of Electrical Engineering, Iran University of Science and Technology (IUST), Narmak, Tehran 16846-13114, Iran.


| M. R. Mosavi
School of Electrical Engineering, Iran University of Science and TechnologySchool of Electrical Engineering, Iran University of Science and Technology (IUST), Narmak, Tehran 16846-13114, Iran.


| A. Sadr
School of Electrical Engineering, Iran University of Science and Technology (IUST), Narmak, Tehran 16846-13114, Iran.


| D. M. de Andrés
ETSI de Telecomunicación, Universidad Politécnica de Madrid, Av. Complutense 30, 28040 Madrid, Spain.
نشانی اینترنتی http://ijeee.iust.ac.ir/browse.php?a_code=A-10-78-29&slc_lang=en&sid=1
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کد مقاله (doi)
زبان مقاله منتشر شده en
موضوعات مقاله منتشر شده 2-Automotive and Consumer Electronics
نوع مقاله منتشر شده Research Paper
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