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Performance of Orthogonal Frequency Division Multiplexing Based Advanced Encryption Standard

2020· article· en· W3157716736 on OpenAlexaboutno aff
Duc-Tai Truong, Quoc-Tuan Nguyen, Thai-Mai Thi Dinh

Bibliographic record

VenueVNU Journal of Science Computer Science and Communication Engineering · 2020
Typearticle
Languageen
FieldComputer Science
TopicCoding theory and cryptography
Canadian institutionsnot available
Fundersnot available
KeywordsOrthogonal frequency-division multiplexingComputer scienceEncryptionAdvanced Encryption StandardComputer networkPhysical layerWirelessTelecommunicationsChannel (broadcasting)

Abstract

fetched live from OpenAlex

Currently, there are a lot of secure communication schemes have been proposed to hide secret contents. In this work, one of the methods deploying encryption to cipher data is represented. The primary object of this project is applying Advanced Encryption Standard (AES) in communications based Orthogonal Frequency Division Multiplexing (OFDM). This article discusses the security of the method encrypting directly QAM symbols instead of input bit-stream. This leads to improving the security of transmitting data by utilization of authentication key between the mobile and base station. The archived results demonstrate that the performance of the AES-OFDM system is completely acceptable to compare with the criteria for 4G.
 Keywords:
 Orthogonal Frequency Division Multiplexing (OFDM), Advanced Encryption Standard (AES), Quadrature Amplitude Modulation (QAM), Authentication Key, Cellular Network, Encryption, Physical Layer, 4G, LTE.
 References
 [1] M.A. Jessen, “Wireless communication security: Physical-Layer techniques exploiting radio and propagation characteristics”, Wireless Information Technology and Systems (ICWITS), IEEE International Conference, 2012.[2] M. Kim, M. Lee, S. Kim, D. Won, “Weakness and Improvements of a One-time Password Authentication Scheme”, International Journal of Future Generation Communication and Networking, 2009.
 [3] Alabaichi, Ashwaq, Salih, Adnan, “Enhance security of advance encryption standard algorithm based on key-dependent S-box”, 2015, pp. 44-53.
 [4] S. Xiao, W. Gong, D. Towsley, “Secure Wireless Communication with Dynamic secrets”, IEEE INFOCOM, 2010.[5] N.U. Rehman, L. Zhang, M.Z. Hammad, “ICI cancellation in OFDM system by frequency offset reduction”, Journal of Information Engineering and Applications, 2014.
 [6] Nikita Agrawal, Neelesh Gupta, “Security of OFDM through Steganography”, International Journal of Computer Applications 121(20) (2015) 41-43.
 [7] A. Al-Dweik, M. Mirahmadi, A. Sharmi, Z. Ding, R. Hamila, “Joint Secured and Robust technique for OFDM systems”, Western University, Canada, IEEE ICC 2013.
 [8] G.R. Tsouri, D. Wulich, “Securing OFDM over Wireless Time-varying channel using subcarrier overloading with Joint signal constellations”, Hindawi Publishing Corporation, EURASIP Journal on Wireless Communication and Networking, 2009.
 [9] D. Rajaveerappa, A. Almarimi, A., “RSA/Shift secured IFFT/FFT based OFDM wireless system,” Fifth International Conference on Information Assurance and Security, 2009.
 [10] M. Hilmey, S. Elhalafwy, M. Zein Eldin, “Efficient transmission of chaotic and AES encrypted images with OFDM over an AWGN channel”, 2009 International Conference on Computer Engineering & Systems, Cairo, 2009, pp. 353-358.
 [11] B.V. Naik, N.L.K. Sai, C.M. Kumar, “Efficient transmission of encrypted images with OFDM system”, 2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI), Chennai, 2017, pp. 2383-2388.
 [12] S.M.S. Eldin, “Optimized OFDM Transmission of Encrypted Image Over Fading Channel”, An International Journal on Sensing and Imaging 15(1) (2014), pp. 1-14.
 [13] C. Akbar, H. Mahmood, Q. Minhas, I. Mustafa, “Secure AES OFDM with channel reciprocity exploitation through relative calibration”, 2016 International Conference on Open Source Systems & Technologies (ICOSST), Lahore, 2016, pp. 54-61.
 [14] Y. Liang, J. Ren, T. Li, “Secure OFDM System Design and Capacity Analysis Under Disguised Jamming”, in IEEE Transactions on Information Forensics and Security 15 (2020) 738-752.
 [15] Westlund, B. Harold, “NIST reports measurable success of Advanced Encryption Standard”,Journal of Research of the National Institute of Standards and Technology, 2002.
 [16] B. Schneier, J. Kelsey, D. Whiting, D. Wagner, C. Hall, N. Ferguson, Performance Comparison of the AES Submissions, Proceedings of the Second AES Candidate Conference, 1999.
 [17] S. He, A. Tang, H. Zhang, “A high-performance Implementation of OFDM-MIMO base-band in wireless video system”, Information Technology Journal 13 (2014), pp. 1678-1685.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.724
Threshold uncertainty score0.539

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.003
Open science0.0030.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.219
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

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