تشخیص و آشکارسازی حمله فریب در گیرنده تک فرکانسه GPS مبتنی بر شبکه عصبی چندلایه

شفیعی, ابراهیم; موسوی, سید محمد رضا; معاضدی, مریم

تشخیص و آشکارسازی حمله فریب در گیرنده تک فرکانسه GPS مبتنی بر شبکه عصبی چندلایه

نویسندگان

¹ دانشجوی کارشناسی ارشد، دانشکده مهندسی برق، دانشگاه علم و صنعت ایران، تهران، ایران

² استاد، دانشکده مهندسی برق، دانشگاه علم و صنعت ایران، تهران، ایران

³ دانشجوی دکتری، دانشکده مهندسی برق، دانشگاه علم و صنعت ایران، تهران، ایران

چکیده

فریب GPS تلاشی برای گمراه کردن گیرنده GPS با انتشار سیگنال‌های جعلی است. ساختار سیگنال فریب شبیه به سیگنال‌های معتبر ماهواره‌های GPS و کمی قوی‌تر از آن‌ها می‌‌باشد. در سال‌های اخیر راه‌کارهای متنوعی جهت تشخیص و کاهش فریب ارائه گردیده است. شبکه‌های عصبی، روش‌ محاسباتی نوینی برای‌ یادگیری ماشین و سپس اعمال دانش به‌دست‌آمده در جهت پیش‌بینی پاسخ‌ خروجی سامانه‌های پیچیده می باشند. در مقاله حاضر، استفاده از سیستم هوشمند رویکرد اصلی در الگوریتم پیشنهادی تشخیص فریب GPS قرار داده شده است. با استفاده از مشخصه های همبستگی، سیگنال ها را دسته بندی نموده ایم. شاخص های فاز مقدم و مؤخر، دلتا و سطح کل سیگنال را به‌عنوان ورودی های شبکه عصبی چندلایه اعمال کرده تا سیگنال فریب را در حلقه ردیابی گیرنده GPS شناسایی کند. شبکه عصبی با خطای کمتری نسبت به روش های پیشین سیگنال ها را دسته‌بندی می نماید، زیرا می تواند چندین روش را به‌طور همزمان بکار گیرد. درنهایت، کمترین دقت به‌دست آمده از شبیه سازی گیرنده نرم افزاری مبتنی بر شبکه عصبی، دقت 98.78 درصدی در تشخیص صحیح سیگنال فریب از سیگنال معتبر می‌باشد. همچنین نسبت به روش های پیشین مدت زمان تشخیص کاهش‌یافته است.

کلیدواژه‌ها

20.1001.1.23224347.1394.3.1.12.7

عنوان مقاله [English]

Detection of Spoofing Attack Based on Multi-Layer Neural Network in Single-Frequency GPS Receivers

نویسندگان [English]

Ebrahim Shafiei ¹
Seyed Mohammad Reza Mousavi ²
Maryam Moazedi ³

¹ Master's student, Faculty of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran

² Professor, Faculty of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran

³ PhD student, Faculty of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran

چکیده [English]

A GPS spoofing attack attempts to deceive a GPS receiver by broadcasting counterfeit GPS signals. Structured to
resemble a set of normal GPS signals, but it is a little stronger. In the recent years, there have been presented many
different solutions for detection and reduction of spoofing attack. Neural Networks (NNs) are the modern
computational method for learning machine and then imposing the acquired knowledge for predicting the output response
of complicated systems. This paper presents a main approach to GPS spoofing detection based on intelligent
systems. Signals are classified using auto-correlation features. Indices of early-late phase, delta and total signal level
as inputs of multi-layer NN in order to detect spoofing signal in GPS receiver tracking loop. Authentic and spoof
signals have different statistical pattern in named parameter and NN can detected it. Since NN is able to exploit
multiple features from different methods, it classifies signals with error less than the conventional techniques. Finally,
the least precision obtained from simulation of NN based GPS software receiver is 98.78% in correct detection of
spoofing signal from valid signal. Moreover, the detection time is less than the existing methods.

کلیدواژه‌ها [English]

Detection
GPS
Spoofing Attack
Neural Network

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