اخبار و اعلانات
آمار
| تعداد نشریات | 38 |
| تعداد شماره‌ها | 1,240 |
| تعداد مقالات | 8,992 |
| تعداد مشاهده مقاله | 7,843,213 |
| تعداد دریافت فایل اصل مقاله | 4,704,948 |
تشخیص و آشکارسازی حمله فریب در گیرنده تک فرکانسه GPS مبتنی بر شبکه عصبی چندلایه | ||
| پدافند الکترونیکی و سایبری | ||
| مقاله 6، دوره 3، شماره 1، اردیبهشت 1394، صفحه 69-80 اصل مقاله (1.18 M) | ||
| نویسندگان | ||
| ابراهیم شفیعی1؛ سید محمد رضا موسوی* 2؛ مریم معاضدی3 | ||
| 1دانشجوی کارشناسی ارشد، دانشکده مهندسی برق، دانشگاه علم و صنعت ایران، تهران، ایران | ||
| 2استاد، دانشکده مهندسی برق، دانشگاه علم و صنعت ایران، تهران، ایران | ||
| 3دانشجوی دکتری، دانشکده مهندسی برق، دانشگاه علم و صنعت ایران، تهران، ایران | ||
| تاریخ دریافت: 04 دی 1393، تاریخ بازنگری: 31 خرداد 1402، تاریخ پذیرش: 28 شهریور 1397 | ||
| 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 | ||
| فریب GPS؛ شبکه عصبی؛ تشخیص و آشکارسازی سیگنال فریب | ||
| عنوان مقاله [English] | ||
| Detection of Spoofing Attack Based on Multi-Layer Neural Network in Single-Frequency GPS Receivers | ||
| نویسندگان [English] | ||
| Ebrahim Shafiei1؛ Seyed Mohammad Reza Mousavi2؛ Maryam Moazedi3 | ||
| 1Master's student, Faculty of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran | ||
| 2Professor, Faculty of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran | ||
| 3PhD 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 | ||
| مراجع | ||
|
[1] F. Shafiee and M. R. Mosavi, “Narrowband Interference Suppression for GPS Navigation using Neural Networks,” Journal of GPS Solutions, pp. 1-11, 2015 (DOI 10.1007/s10291-015-0442-8). [2] A. Jovanovic, C. Botteron, and P. A. Farine, “Multi-test Detection and Protection Algorithm Against Spoofing Attacks on GNSS Receivers,” IEEE Position, Location and Navigation Symposium, pp. 1258-1271, May 2014. [3] C. Bonebrake and L. R. O'Neil, “Attacks on GPS Time Reliability,” IEEE Transactions on Security & Privacy, vol. 12, no. 3, pp. 82-85, June 2014. [4] M. R. Mosavi, M. J. Rezaei, N. Hosseinzadeh and R. A. Kiaamiri, “New Intellogent Methods for Detection and Mitigation of Spoofing Signal in GPS Receivers”, Journal of Electronics and Cyber Defense, Vol.2, No.1, pp.71-81, 1393. (in Persian) [5] J. Nielsen, A. Broumandan, and G. Lachapelle, “Spoofing Detection and Mitigation with a Moving Handheld Receiver,” GPS World vol. 21, no. 9, pp. 27-33, 2010. [6] T. E. Humphreys, J. Bhatti, and B. Ledvina, “The GPS Assimilator: a Method for Upgrading Existing GPS User Equipment to Improve Accuracy, Robustness and Resistance to Spoofing,” The 23rd International Technical Meeting of the Satellite Division of the Institute of Navigation, pp. 1-11, Sep. 2010. [7] A. J. Jahromi, A. Broumandan, J. Nielsen, and G. Lachapelle, “GPS Vulnerability to Spoofing Threats and a Review of Anti-spoofing Techniques,” Journal of Navigation and Observation, vol. 20, pp. 1-16, May 2012. [8] A. J. Jahromi, T. Lin, A. Broumandan, J. Nielsen, and G. Lachapelle, “Detection and Mitigation of Spoofing Attacks on a Vector-Based Tracking GPS Receiver,” International Technical Meeting of the Institute of Navigation, pp. 3-8, Jan. 2012. [9] D. P. Shepard and T. E. Humphreys, “Characterization of Receiver Response to Spoofing Attacks,” GPS World, vol. 21, no. 9, pp. 27-33, 2010. [10] A. Cavaleri, B. Motella, M. Pini, and M. Fantino, “Detection of Spoofed GPS Signals at Code and Carrier Tracking Level,” The 5th ESA Workshop on Satellite Navigation Technologies and European Workshop on GNSS Signals and Signal Processing, pp. 1-6, Dec. 2010. [11] K. D. Wesson, B. L. Evans, and T. E. Humphreys, “A Combined Symmetric Difference and Power Monitoring GNSS Anti-Spoofing Technique,” IEEE Global Conference on Signal and Information Processing, pp. 1-4, Dec. 2013. [12] M. Pini, M. Fantino, A. Cavaleri, S. Ugazio, and L. L. Presti, “Signal Quality Monitoring Applied to Spoofing Detection,” The 24th International Technical Meeting of the Satellite Division of the Institute of Navigation, pp. 1-9, Sep. 2011. [13] M. Lashley and D. Bevly, “What About Vector Tracking Loops,” GNSS Solutions, pp. 1-6, May/June 2009. [14] S. C. Lo and P. K. Enge, “Authenticating Aviation Augmentation System Broadcasts,” IEEE/ION Position, Location and Navigation Symposium, pp. 708-717, 2010. [15] M. G. Petovello, “Real-Time Integration of a Tactical-Grade IMU and GPS for High-Accuracy Positioning and Navigation,” Ph.D. Thesis, Department of Geomatics Engineering, University of Calgary, Alberta, Canada, 2003. [16] T. E. Humphreys, M. L. Psiaki, P. M. Kintner and B. M. Ledvina, “GNSS Receiver Implementation on a DSP: Status, Challenges and Prospects”, Proc. ION GNSS, pp. 1-13, 2006. [17] C. E. Mcdowell, “GPS Spoofer and Repeater Mitigation System using Digital Spatial Nulling-US Patent 7250903 B1,” 2007. [18] A. Jafarnia-Jahromi, A. Broumandan, J. Nielsen, and G. Lachapelle, “GPS Spoofer Countermeasure Effectiveness based on Signal Strength, Noise Power and C/N0 Observables,” International Journal of Satellite Communications and Networking, vol. 30, no. 4, pp. 181-191, 2012. [19] P. Y. Montgomery, T. E. Humphreys, and B. M. Ledvina, “Receiver-Autonomous Spoofing Detection: Experimental Results of a Multi-Antenna Receiver Defense Against a Portable Civil GPS Spoofer,” The Institute of International Technical Meeting of the Institute of Navigation, pp. 1-7, Jan. 2009. [20] P. Y. Montgomery, T. E. Humphreys, and B. M. Ledvina, “A Multi-Antenna Defense: Receiver-Autonomous GPS Spoofing Detection,” Inside GNSS Magazine, vol. 4, no. 2, pp. 40-46, March/April 2009. [21] S. C. Lo and P. K. Enge, “Authenticating Aviation Augmentation System Broadcasts,” IEEE/ION Position, Location and Navigation Symposium, pp. 708-717, 2010. [22] B. M. Ledvina, W. J. Bencze, B. Galusha, and I. Miller, “An In-Line Anti-Spoofing Device for Legacy Civil GPS Receivers,” The 23rd International Technical Meeting of the Institute of Navigation, pp. 689-712, Jan. 2010. [23] A. Tabatabaei and M. R. Mosavi, “Rapid and Precise GLONASS GDOP Approximation using Neural Networks,” Journal of Wireless Personal Communications, vol. 77, no. 4, pp. 2675-2685, 2014. [24] H. Azami, M. R. Mosavi, and S. Sanei, “Classification of GPS Satellites using Improved Back Propagation Training Algorithms,” Journal of Wireless Personal Communications, vol. 71, no. 2, pp. 789-803, 2013. [25] M. R. Mosavi, K. Mohammadi, M. H. Refan, and M. Farrokhi, “Prediction of Errors and Improvement of Position Accuracy on Low Cost GPS Receiver with MLP Neural Network,” The 11th Iranian Conference on Electrical Engineering, vol. 3, pp. 513-520, 6-8 May 2003. [26] T. Martin and B. Menhaj, “Training Feedforward Networks with the Marquardt Algorithm,” IEEE Transactions on Neural Networks, vol. 5, no. 6, pp. 989-993, November 1994. [27] M. R. Mosavi, “GPS Receivers Timing Data Processing using Neural Networks: Optimal Estimation and Errors Modeling,” Journal of Neural Systems, vol. 17, no. 5, pp. 383-393, October 2007. [28] R. Pasti and L. N. De Castro, “Bio-Inspired and Gradient based Algorithms to Train MLPs: the Influence of Diversity,” Information Sciences, vol. 179, no. 10, pp. 1441-1453, Apr. 2009. [29] I. Kanellopoulos, A. Varfis, G. Wilkinson, and J. Meiger, “Land Cover Discrimination in SPOT HRV Imagery using Artificial Neural Network 20 Class Experiment,” Journal of Remote Sensing, vol. 13, pp. 917-924, 1992. [30] E. Ochin, L. Dobryakova, and L. Lemieszewski, “Antiterrorism-Design and Analysis of GNSS Anti-spoofing Algorithms,” Scientific Journals Zeszyty Naukowe Maritime University of Szczecin, pp. 93-101, 2012. [31] M. H. Jin, Y. H. Han, H. H. Choi, C. Park, M. B. Heo, and S. J. Lee, “GPS Spoofing Signal Detection and Compensation Method in DGPS Reference Station,” 11th International Conference on Control, Automation and Systems, Korea, 2011. [32] P. Papadimitratos and A. Jovanovic, “GNSS Based Positioning: Attacks and Countermeasures,” IEEE Military Communications Conference (MILCOM), pp. 1-7, 2008. | ||
|
آمار تعداد مشاهده مقاله: 416 تعداد دریافت فایل اصل مقاله: 515 |
||