Compressive sensing chaotic encryption algorithms for OFDM-PON data transmission
In this paper, we propose chaotic compressive sensing (CS) encryption algorithms for orthogonal frequency division multiplexing passive optical network (OFDM-PON), aiming at compressing the transmitted data and enhancing the security of data transmission. Bitstream transmission using CS directly is...
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| Vydané v: | Optics express Ročník 29; číslo 3; s. 3669 |
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| Hlavní autori: | , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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01.02.2021
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| ISSN: | 1094-4087, 1094-4087 |
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| Abstract | In this paper, we propose chaotic compressive sensing (CS) encryption algorithms for orthogonal frequency division multiplexing passive optical network (OFDM-PON), aiming at compressing the transmitted data and enhancing the security of data transmission. Bitstream transmission using CS directly is restricted due to its inability to satisfy the sparsity in neither time nor frequency domain. While the sparsity of the transmitted data can be constructed when transmitting the multimedia. A sensor can be then used to identify whether the data is multimedia. If it is, the CS technique is used, and the sensor’s result is set as side information inserted into the pilot and transmitted to the terminal simultaneously. For encryption processing, a 2-dimensional logistic-sine-coupling map (2D-LSCM) is used to generate pseudo-random numbers to construct the first row of a measurement matrix to encrypt the system. Four transform formats are then applied to generate the sparsity of the transmitted data. Due to the restriction of data transmission in the physical layer, the discrete cosine transform (DCT) is chosen to conduct the CS technique. Four approximation algorithms are also proposed to optimize the performance of compressing the length of bits. We find that ‘
Round + Set negative to 0
’ shows the best performance. The combination of this chaotic CS encryption technique with the OFDM-PON systems saves the bandwidth and improves the security. |
|---|---|
| AbstractList | In this paper, we propose chaotic compressive sensing (CS) encryption algorithms for orthogonal frequency division multiplexing passive optical network (OFDM-PON), aiming at compressing the transmitted data and enhancing the security of data transmission. Bitstream transmission using CS directly is restricted due to its inability to satisfy the sparsity in neither time nor frequency domain. While the sparsity of the transmitted data can be constructed when transmitting the multimedia. A sensor can be then used to identify whether the data is multimedia. If it is, the CS technique is used, and the sensor’s result is set as side information inserted into the pilot and transmitted to the terminal simultaneously. For encryption processing, a 2-dimensional logistic-sine-coupling map (2D-LSCM) is used to generate pseudo-random numbers to construct the first row of a measurement matrix to encrypt the system. Four transform formats are then applied to generate the sparsity of the transmitted data. Due to the restriction of data transmission in the physical layer, the discrete cosine transform (DCT) is chosen to conduct the CS technique. Four approximation algorithms are also proposed to optimize the performance of compressing the length of bits. We find that ‘
Round + Set negative to 0
’ shows the best performance. The combination of this chaotic CS encryption technique with the OFDM-PON systems saves the bandwidth and improves the security. In this paper, we propose chaotic compressive sensing (CS) encryption algorithms for orthogonal frequency division multiplexing passive optical network (OFDM-PON), aiming at compressing the transmitted data and enhancing the security of data transmission. Bitstream transmission using CS directly is restricted due to its inability to satisfy the sparsity in neither time nor frequency domain. While the sparsity of the transmitted data can be constructed when transmitting the multimedia. A sensor can be then used to identify whether the data is multimedia. If it is, the CS technique is used, and the sensor's result is set as side information inserted into the pilot and transmitted to the terminal simultaneously. For encryption processing, a 2-dimensional logistic-sine-coupling map (2D-LSCM) is used to generate pseudo-random numbers to construct the first row of a measurement matrix to encrypt the system. Four transform formats are then applied to generate the sparsity of the transmitted data. Due to the restriction of data transmission in the physical layer, the discrete cosine transform (DCT) is chosen to conduct the CS technique. Four approximation algorithms are also proposed to optimize the performance of compressing the length of bits. We find that 'Round + Set negative to 0' shows the best performance. The combination of this chaotic CS encryption technique with the OFDM-PON systems saves the bandwidth and improves the security. In this paper, we propose chaotic compressive sensing (CS) encryption algorithms for orthogonal frequency division multiplexing passive optical network (OFDM-PON), aiming at compressing the transmitted data and enhancing the security of data transmission. Bitstream transmission using CS directly is restricted due to its inability to satisfy the sparsity in neither time nor frequency domain. While the sparsity of the transmitted data can be constructed when transmitting the multimedia. A sensor can be then used to identify whether the data is multimedia. If it is, the CS technique is used, and the sensor's result is set as side information inserted into the pilot and transmitted to the terminal simultaneously. For encryption processing, a 2-dimensional logistic-sine-coupling map (2D-LSCM) is used to generate pseudo-random numbers to construct the first row of a measurement matrix to encrypt the system. Four transform formats are then applied to generate the sparsity of the transmitted data. Due to the restriction of data transmission in the physical layer, the discrete cosine transform (DCT) is chosen to conduct the CS technique. Four approximation algorithms are also proposed to optimize the performance of compressing the length of bits. We find that 'Round + Set negative to 0' shows the best performance. The combination of this chaotic CS encryption technique with the OFDM-PON systems saves the bandwidth and improves the security.In this paper, we propose chaotic compressive sensing (CS) encryption algorithms for orthogonal frequency division multiplexing passive optical network (OFDM-PON), aiming at compressing the transmitted data and enhancing the security of data transmission. Bitstream transmission using CS directly is restricted due to its inability to satisfy the sparsity in neither time nor frequency domain. While the sparsity of the transmitted data can be constructed when transmitting the multimedia. A sensor can be then used to identify whether the data is multimedia. If it is, the CS technique is used, and the sensor's result is set as side information inserted into the pilot and transmitted to the terminal simultaneously. For encryption processing, a 2-dimensional logistic-sine-coupling map (2D-LSCM) is used to generate pseudo-random numbers to construct the first row of a measurement matrix to encrypt the system. Four transform formats are then applied to generate the sparsity of the transmitted data. Due to the restriction of data transmission in the physical layer, the discrete cosine transform (DCT) is chosen to conduct the CS technique. Four approximation algorithms are also proposed to optimize the performance of compressing the length of bits. We find that 'Round + Set negative to 0' shows the best performance. The combination of this chaotic CS encryption technique with the OFDM-PON systems saves the bandwidth and improves the security. |
| Author | Wu, Tingwei Zhao, Xiong Qiu, Kun Zhang, Chongfu Chen, Yuhang Huang, Huan Zhang, Zhi Wen, Heping Cui, Mengwei |
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| Cites_doi | 10.1109/JLT.2018.2789435 10.1364/OE.26.022857 10.1109/JPHOT.2017.2661581 10.1007/s11071-016-2648-x 10.1109/JLT.2018.2851568 10.1364/OE.27.030450 10.1016/j.sigpro.2018.02.007 10.1109/JLT.2019.2938789 10.1109/JPHOT.2017.2754407 10.1109/LPT.2015.2466092 10.1109/JIOT.2018.2847731 10.1109/ACCESS.2019.2938910 10.1109/TII.2019.2924083 10.1016/j.sigpro.2018.12.007 10.1109/LPT.2017.2702159 10.1109/JPHOT.2018.2852299 10.3390/s20010206 10.1166/jmihi.2020.2691 10.1109/JLT.2012.2212180 10.1109/3.502371 10.1016/j.sigpro.2018.03.010 10.1364/OE.21.015627 10.1109/LPT.2016.2522965 10.1364/OE.27.027946 10.1016/j.optcom.2015.05.043 10.1016/j.compeleceng.2015.03.011 10.1016/j.sigpro.2019.107318 10.1109/LPT.2015.2414717 10.1364/OE.24.029198 10.1007/s11227-016-1850-4 10.1109/LPT.2013.2290041 10.1109/JLT.2017.2669909 |
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| References | Zhang (oe-29-3-3669-R15) 2017; 9 Hua (oe-29-3-3669-R31) 2018; 149 Annovazzi-Lodi (oe-29-3-3669-R8) 1996; 32 Li (oe-29-3-3669-R29) 2020; 167 Hu (oe-29-3-3669-R21) 2015; 27 Carvalho (oe-29-3-3669-R7) 2015; 27 Kang (oe-29-3-3669-R11) 2019; 27 Wang (oe-29-3-3669-R13) 2015; 46 Zhou (oe-29-3-3669-R30) 2015; 354 Liu (oe-29-3-3669-R16) 2014; 26 Zhang (oe-29-3-3669-R23) 2017; 29 Zhang (oe-29-3-3669-R19) 2016; 28 Deng (oe-29-3-3669-R4) 2019; 157 Winzer (oe-29-3-3669-R10) 2012; 30 Zhang (oe-29-3-3669-R18) 2017; 35 Liu (oe-29-3-3669-R1) 2019; 6 Wu (oe-29-3-3669-R20) 2019; 27 Wei (oe-29-3-3669-R24) 2019; 7 Wu (oe-29-3-3669-R22) 2018; 26 Qu (oe-29-3-3669-R2) 2019; 37 Chai (oe-29-3-3669-R3) 2018; 148 Wang (oe-29-3-3669-R28) 2019; 15 AlHayani (oe-29-3-3669-R6) 2020; 10 Zhang (oe-29-3-3669-R17) 2013; 21 Chen (oe-29-3-3669-R5) 2019; 20 Bi (oe-29-3-3669-R25) 2017; 9 Zhang (oe-29-3-3669-R27) 2018; 10 Jung (oe-29-3-3669-R9) 2016; 24 Singh (oe-29-3-3669-R12) 2019; 75 Tong (oe-29-3-3669-R32) 2016; 84 Zhang (oe-29-3-3669-R14) 2018; 36 Li (oe-29-3-3669-R26) 2018; 36 |
| References_xml | – volume: 36 start-page: 1706 year: 2018 ident: oe-29-3-3669-R14 publication-title: J. Lightwave Technol. doi: 10.1109/JLT.2018.2789435 – volume: 26 start-page: 22857 year: 2018 ident: oe-29-3-3669-R22 publication-title: Opt. Express doi: 10.1364/OE.26.022857 – volume: 9 start-page: 1 year: 2017 ident: oe-29-3-3669-R25 publication-title: IEEE Photonics J. doi: 10.1109/JPHOT.2017.2661581 – volume: 84 start-page: 2333 year: 2016 ident: oe-29-3-3669-R32 publication-title: Nonlinear Dyn. doi: 10.1007/s11071-016-2648-x – volume: 36 start-page: 3824 year: 2018 ident: oe-29-3-3669-R26 publication-title: J. Lightwave Technol. doi: 10.1109/JLT.2018.2851568 – volume: 27 start-page: 30450 year: 2019 ident: oe-29-3-3669-R11 publication-title: Opt. Express doi: 10.1364/OE.27.030450 – volume: 148 start-page: 124 year: 2018 ident: oe-29-3-3669-R3 publication-title: Signal Processing doi: 10.1016/j.sigpro.2018.02.007 – volume: 37 start-page: 5766 year: 2019 ident: oe-29-3-3669-R2 publication-title: J. Lightwave Technol. doi: 10.1109/JLT.2019.2938789 – volume: 9 start-page: 1 year: 2017 ident: oe-29-3-3669-R15 publication-title: IEEE Photonics J. doi: 10.1109/JPHOT.2017.2754407 – volume: 27 start-page: 2429 year: 2015 ident: oe-29-3-3669-R21 publication-title: IEEE Photonics Technol. Lett. doi: 10.1109/LPT.2015.2466092 – volume: 6 start-page: 5962 year: 2019 ident: oe-29-3-3669-R1 publication-title: IEEE Internet Things J. doi: 10.1109/JIOT.2018.2847731 – volume: 7 start-page: 124452 year: 2019 ident: oe-29-3-3669-R24 publication-title: IEEE Access doi: 10.1109/ACCESS.2019.2938910 – volume: 15 start-page: 6560 year: 2019 ident: oe-29-3-3669-R28 publication-title: IEEE Trans. Ind. Info. doi: 10.1109/TII.2019.2924083 – volume: 157 start-page: 280 year: 2019 ident: oe-29-3-3669-R4 publication-title: Signal Processing doi: 10.1016/j.sigpro.2018.12.007 – volume: 29 start-page: 1023 year: 2017 ident: oe-29-3-3669-R23 publication-title: IEEE Photonics Technol. Lett. doi: 10.1109/LPT.2017.2702159 – volume: 10 start-page: 1 year: 2018 ident: oe-29-3-3669-R27 publication-title: IEEE Photonics J. doi: 10.1109/JPHOT.2018.2852299 – volume: 20 start-page: 206 year: 2019 ident: oe-29-3-3669-R5 publication-title: Sensors doi: 10.3390/s20010206 – volume: 10 start-page: 160 year: 2020 ident: oe-29-3-3669-R6 publication-title: J. Med. Imaging & Health Info. doi: 10.1166/jmihi.2020.2691 – volume: 30 start-page: 3824 year: 2012 ident: oe-29-3-3669-R10 publication-title: J. Lightwave Technol. doi: 10.1109/JLT.2012.2212180 – volume: 32 start-page: 953 year: 1996 ident: oe-29-3-3669-R8 publication-title: IEEE J. Quantum Electron. doi: 10.1109/3.502371 – volume: 149 start-page: 148 year: 2018 ident: oe-29-3-3669-R31 publication-title: Signal Processing doi: 10.1016/j.sigpro.2018.03.010 – volume: 21 start-page: 15627 year: 2013 ident: oe-29-3-3669-R17 publication-title: Opt. Express doi: 10.1364/OE.21.015627 – volume: 28 start-page: 1 year: 2016 ident: oe-29-3-3669-R19 publication-title: IEEE Photonics Technol. Lett. doi: 10.1109/LPT.2016.2522965 – volume: 27 start-page: 27946 year: 2019 ident: oe-29-3-3669-R20 publication-title: Opt. Express doi: 10.1364/OE.27.027946 – volume: 354 start-page: 112 year: 2015 ident: oe-29-3-3669-R30 publication-title: Opt. Commun. doi: 10.1016/j.optcom.2015.05.043 – volume: 46 start-page: 433 year: 2015 ident: oe-29-3-3669-R13 publication-title: Comput. Electr. Eng. doi: 10.1016/j.compeleceng.2015.03.011 – volume: 167 start-page: 107318 year: 2020 ident: oe-29-3-3669-R29 publication-title: Signal Processing doi: 10.1016/j.sigpro.2019.107318 – volume: 27 start-page: 1193 year: 2015 ident: oe-29-3-3669-R7 publication-title: IEEE Photonics Technol. Lett. doi: 10.1109/LPT.2015.2414717 – volume: 24 start-page: 29198 year: 2016 ident: oe-29-3-3669-R9 publication-title: Opt. Express doi: 10.1364/OE.24.029198 – volume: 75 start-page: 4543 year: 2019 ident: oe-29-3-3669-R12 publication-title: J. Supercomput. doi: 10.1007/s11227-016-1850-4 – volume: 26 start-page: 127 year: 2014 ident: oe-29-3-3669-R16 publication-title: IEEE Photonics Technol. Lett. doi: 10.1109/LPT.2013.2290041 – volume: 35 start-page: 1524 year: 2017 ident: oe-29-3-3669-R18 publication-title: J. Lightwave Technol. doi: 10.1109/JLT.2017.2669909 |
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