Physical Layer Dynamic Key Encryption in OFDM-PON System Based on Cellular Neural Network
In this paper, we propose a dynamic key technique based on Cellular Neural Network (CNN) for security improvement in the orthogonal frequency division multiplexing passive optical network (OFDM-PON). To enhance the encryption scheme security, a six-dimensional CNN hyperchaotic system is employed to...
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Photonics Journal |
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| Online Access: | https://ieeexplore.ieee.org/document/9354561/ |
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| author | Yuxin Zhou Meihua Bi Xianhao Zhuo Yunxin Lv Xuelin Yang Weisheng Hu |
| author_facet | Yuxin Zhou Meihua Bi Xianhao Zhuo Yunxin Lv Xuelin Yang Weisheng Hu |
| author_sort | Yuxin Zhou |
| collection | DOAJ |
| description | In this paper, we propose a dynamic key technique based on Cellular Neural Network (CNN) for security improvement in the orthogonal frequency division multiplexing passive optical network (OFDM-PON). To enhance the encryption scheme security, a six-dimensional CNN hyperchaotic system is employed to encrypt the data. And, the keys are divided into the dynamic and static. The dynamic key is randomly extracted from a key set by incorporating the random feature of the input data. Then, the chaotic sequence generated by the dynamic key is served as the synchronous sequence for encryption. Moreover, the chaotic sequences generated by the static keys are used to resist the chosen-plaintext attacks (CPAs) and scramble the phase of QAM symbols on the frequency domain. With these processing techniques, the multi-fold data encryption can create a key space of ∼10<sup>315</sup> to protect against the exhaustive trial. The transmission of 10-Gb/s encrypted 16-QAM-based OFDM signal is demonstrated over 20-km single mode fiber (SMF) by experiment. The results show that our proposed scheme can provide excellent confidentiality of data transmission against the CPAs and brute-force attack. |
| format | Article |
| id | doaj-art-a08ecb291f424042aa935095d208c8e0 |
| institution | DOAJ |
| issn | 1943-0655 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Photonics Journal |
| spelling | doaj-art-a08ecb291f424042aa935095d208c8e02025-08-20T03:15:50ZengIEEEIEEE Photonics Journal1943-06552021-01-0113211410.1109/JPHOT.2021.30593699354561Physical Layer Dynamic Key Encryption in OFDM-PON System Based on Cellular Neural NetworkYuxin Zhou0Meihua Bi1https://orcid.org/0000-0001-8177-1808Xianhao Zhuo2Yunxin Lv3Xuelin Yang4https://orcid.org/0000-0003-0197-7959Weisheng Hu5https://orcid.org/0000-0002-6168-2688College of Communication Engineering, Hangzhou Dianzi University, Hangzhou, Zhe Jiang province, ChinaCollege of Communication Engineering, Hangzhou Dianzi University, Hangzhou, Zhe Jiang province, ChinaCollege of Communication Engineering, Hangzhou Dianzi University, Hangzhou, Zhe Jiang province, ChinaCollege of Communication Engineering, Hangzhou Dianzi University, Hangzhou, Zhe Jiang province, ChinaState Key Laboratory of Advanced Optical Communication System and Networks, Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, ChinaState Key Laboratory of Advanced Optical Communication System and Networks, Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, ChinaIn this paper, we propose a dynamic key technique based on Cellular Neural Network (CNN) for security improvement in the orthogonal frequency division multiplexing passive optical network (OFDM-PON). To enhance the encryption scheme security, a six-dimensional CNN hyperchaotic system is employed to encrypt the data. And, the keys are divided into the dynamic and static. The dynamic key is randomly extracted from a key set by incorporating the random feature of the input data. Then, the chaotic sequence generated by the dynamic key is served as the synchronous sequence for encryption. Moreover, the chaotic sequences generated by the static keys are used to resist the chosen-plaintext attacks (CPAs) and scramble the phase of QAM symbols on the frequency domain. With these processing techniques, the multi-fold data encryption can create a key space of ∼10<sup>315</sup> to protect against the exhaustive trial. The transmission of 10-Gb/s encrypted 16-QAM-based OFDM signal is demonstrated over 20-km single mode fiber (SMF) by experiment. The results show that our proposed scheme can provide excellent confidentiality of data transmission against the CPAs and brute-force attack.https://ieeexplore.ieee.org/document/9354561/Orthogonal frequency-division multiplexing passive optical network (OFDM-PON)Chaotic encryptionDynamic KeyCellular Neural Network |
| spellingShingle | Yuxin Zhou Meihua Bi Xianhao Zhuo Yunxin Lv Xuelin Yang Weisheng Hu Physical Layer Dynamic Key Encryption in OFDM-PON System Based on Cellular Neural Network IEEE Photonics Journal Orthogonal frequency-division multiplexing passive optical network (OFDM-PON) Chaotic encryption Dynamic Key Cellular Neural Network |
| title | Physical Layer Dynamic Key Encryption in OFDM-PON System Based on Cellular Neural Network |
| title_full | Physical Layer Dynamic Key Encryption in OFDM-PON System Based on Cellular Neural Network |
| title_fullStr | Physical Layer Dynamic Key Encryption in OFDM-PON System Based on Cellular Neural Network |
| title_full_unstemmed | Physical Layer Dynamic Key Encryption in OFDM-PON System Based on Cellular Neural Network |
| title_short | Physical Layer Dynamic Key Encryption in OFDM-PON System Based on Cellular Neural Network |
| title_sort | physical layer dynamic key encryption in ofdm pon system based on cellular neural network |
| topic | Orthogonal frequency-division multiplexing passive optical network (OFDM-PON) Chaotic encryption Dynamic Key Cellular Neural Network |
| url | https://ieeexplore.ieee.org/document/9354561/ |
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