An Adaptive Lossly Quantization Technique for Key Extraction Applied in Vehicular Communication

Abstract Security in vehicular ad hoc network (VANET) is one of the major challenging topics and the secure key interchange between two legitimate vehicles is an important issue. The multi-environment of VANET has been exploited to extract the secret key and employed security services in VANET. Howe...
Ausführliche Beschreibung

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Autor*in:	Abdelazeem, Ibraheem [verfasserIn] Zhang, Weibin Zeng, Zhenping Abdeldime, M. S

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	Vehicular ad hoc networks Key extraction Mobile ad hoc networks Quantization RSS

Anmerkung:	© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022

Übergeordnetes Werk:	Enthalten in: Wireless personal communications - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1994, 126(2022), 2 vom: 07. Juni, Seite 1345-1361
Übergeordnetes Werk:	volume:126 ; year:2022 ; number:2 ; day:07 ; month:06 ; pages:1345-1361

Links:	Volltext

DOI / URN:	10.1007/s11277-022-09794-9

Katalog-ID:	SPR048155187

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520			\|a Abstract Security in vehicular ad hoc network (VANET) is one of the major challenging topics and the secure key interchange between two legitimate vehicles is an important issue. The multi-environment of VANET has been exploited to extract the secret key and employed security services in VANET. However, it offered more excellence randomness owed to fading, noise multi-path, and velocity difference. Some of the factors like Bit-rate, complication and memory requests are reduced by using a process known as quantization. This paper proposes a new quantization method to extract the secret key for vehicular communications that uses a lossy quantizer in combination with information reconciliation and privacy amplification. Our work focuses on the quantization phase for the secret generation procedure. The comprehensive simulations display the propose method increases the zone and number of the quantization levels to utilize the maximum number of measurements to reduce reasonably the wasted measurements.
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allfields	10.1007/s11277-022-09794-9 doi (DE-627)SPR048155187 (SPR)s11277-022-09794-9-e DE-627 ger DE-627 rakwb eng Abdelazeem, Ibraheem verfasserin (orcid)0000-0001-9607-1441 aut An Adaptive Lossly Quantization Technique for Key Extraction Applied in Vehicular Communication 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 Abstract Security in vehicular ad hoc network (VANET) is one of the major challenging topics and the secure key interchange between two legitimate vehicles is an important issue. The multi-environment of VANET has been exploited to extract the secret key and employed security services in VANET. However, it offered more excellence randomness owed to fading, noise multi-path, and velocity difference. Some of the factors like Bit-rate, complication and memory requests are reduced by using a process known as quantization. This paper proposes a new quantization method to extract the secret key for vehicular communications that uses a lossy quantizer in combination with information reconciliation and privacy amplification. Our work focuses on the quantization phase for the secret generation procedure. The comprehensive simulations display the propose method increases the zone and number of the quantization levels to utilize the maximum number of measurements to reduce reasonably the wasted measurements. Vehicular ad hoc networks (dpeaa)DE-He213 Key extraction (dpeaa)DE-He213 Mobile ad hoc networks (dpeaa)DE-He213 Quantization (dpeaa)DE-He213 RSS (dpeaa)DE-He213 Zhang, Weibin aut Zeng, Zhenping aut Abdeldime, M. S aut Enthalten in Wireless personal communications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1994 126(2022), 2 vom: 07. Juni, Seite 1345-1361 (DE-627)271179120 (DE-600)1479327-1 1572-834X nnns volume:126 year:2022 number:2 day:07 month:06 pages:1345-1361 https://dx.doi.org/10.1007/s11277-022-09794-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 126 2022 2 07 06 1345-1361
spelling	10.1007/s11277-022-09794-9 doi (DE-627)SPR048155187 (SPR)s11277-022-09794-9-e DE-627 ger DE-627 rakwb eng Abdelazeem, Ibraheem verfasserin (orcid)0000-0001-9607-1441 aut An Adaptive Lossly Quantization Technique for Key Extraction Applied in Vehicular Communication 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 Abstract Security in vehicular ad hoc network (VANET) is one of the major challenging topics and the secure key interchange between two legitimate vehicles is an important issue. The multi-environment of VANET has been exploited to extract the secret key and employed security services in VANET. However, it offered more excellence randomness owed to fading, noise multi-path, and velocity difference. Some of the factors like Bit-rate, complication and memory requests are reduced by using a process known as quantization. This paper proposes a new quantization method to extract the secret key for vehicular communications that uses a lossy quantizer in combination with information reconciliation and privacy amplification. Our work focuses on the quantization phase for the secret generation procedure. The comprehensive simulations display the propose method increases the zone and number of the quantization levels to utilize the maximum number of measurements to reduce reasonably the wasted measurements. Vehicular ad hoc networks (dpeaa)DE-He213 Key extraction (dpeaa)DE-He213 Mobile ad hoc networks (dpeaa)DE-He213 Quantization (dpeaa)DE-He213 RSS (dpeaa)DE-He213 Zhang, Weibin aut Zeng, Zhenping aut Abdeldime, M. S aut Enthalten in Wireless personal communications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1994 126(2022), 2 vom: 07. Juni, Seite 1345-1361 (DE-627)271179120 (DE-600)1479327-1 1572-834X nnns volume:126 year:2022 number:2 day:07 month:06 pages:1345-1361 https://dx.doi.org/10.1007/s11277-022-09794-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 126 2022 2 07 06 1345-1361
allfields_unstemmed	10.1007/s11277-022-09794-9 doi (DE-627)SPR048155187 (SPR)s11277-022-09794-9-e DE-627 ger DE-627 rakwb eng Abdelazeem, Ibraheem verfasserin (orcid)0000-0001-9607-1441 aut An Adaptive Lossly Quantization Technique for Key Extraction Applied in Vehicular Communication 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 Abstract Security in vehicular ad hoc network (VANET) is one of the major challenging topics and the secure key interchange between two legitimate vehicles is an important issue. The multi-environment of VANET has been exploited to extract the secret key and employed security services in VANET. However, it offered more excellence randomness owed to fading, noise multi-path, and velocity difference. Some of the factors like Bit-rate, complication and memory requests are reduced by using a process known as quantization. This paper proposes a new quantization method to extract the secret key for vehicular communications that uses a lossy quantizer in combination with information reconciliation and privacy amplification. Our work focuses on the quantization phase for the secret generation procedure. The comprehensive simulations display the propose method increases the zone and number of the quantization levels to utilize the maximum number of measurements to reduce reasonably the wasted measurements. Vehicular ad hoc networks (dpeaa)DE-He213 Key extraction (dpeaa)DE-He213 Mobile ad hoc networks (dpeaa)DE-He213 Quantization (dpeaa)DE-He213 RSS (dpeaa)DE-He213 Zhang, Weibin aut Zeng, Zhenping aut Abdeldime, M. S aut Enthalten in Wireless personal communications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1994 126(2022), 2 vom: 07. Juni, Seite 1345-1361 (DE-627)271179120 (DE-600)1479327-1 1572-834X nnns volume:126 year:2022 number:2 day:07 month:06 pages:1345-1361 https://dx.doi.org/10.1007/s11277-022-09794-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 126 2022 2 07 06 1345-1361
allfieldsGer	10.1007/s11277-022-09794-9 doi (DE-627)SPR048155187 (SPR)s11277-022-09794-9-e DE-627 ger DE-627 rakwb eng Abdelazeem, Ibraheem verfasserin (orcid)0000-0001-9607-1441 aut An Adaptive Lossly Quantization Technique for Key Extraction Applied in Vehicular Communication 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 Abstract Security in vehicular ad hoc network (VANET) is one of the major challenging topics and the secure key interchange between two legitimate vehicles is an important issue. The multi-environment of VANET has been exploited to extract the secret key and employed security services in VANET. However, it offered more excellence randomness owed to fading, noise multi-path, and velocity difference. Some of the factors like Bit-rate, complication and memory requests are reduced by using a process known as quantization. This paper proposes a new quantization method to extract the secret key for vehicular communications that uses a lossy quantizer in combination with information reconciliation and privacy amplification. Our work focuses on the quantization phase for the secret generation procedure. The comprehensive simulations display the propose method increases the zone and number of the quantization levels to utilize the maximum number of measurements to reduce reasonably the wasted measurements. Vehicular ad hoc networks (dpeaa)DE-He213 Key extraction (dpeaa)DE-He213 Mobile ad hoc networks (dpeaa)DE-He213 Quantization (dpeaa)DE-He213 RSS (dpeaa)DE-He213 Zhang, Weibin aut Zeng, Zhenping aut Abdeldime, M. S aut Enthalten in Wireless personal communications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1994 126(2022), 2 vom: 07. Juni, Seite 1345-1361 (DE-627)271179120 (DE-600)1479327-1 1572-834X nnns volume:126 year:2022 number:2 day:07 month:06 pages:1345-1361 https://dx.doi.org/10.1007/s11277-022-09794-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 126 2022 2 07 06 1345-1361
allfieldsSound	10.1007/s11277-022-09794-9 doi (DE-627)SPR048155187 (SPR)s11277-022-09794-9-e DE-627 ger DE-627 rakwb eng Abdelazeem, Ibraheem verfasserin (orcid)0000-0001-9607-1441 aut An Adaptive Lossly Quantization Technique for Key Extraction Applied in Vehicular Communication 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 Abstract Security in vehicular ad hoc network (VANET) is one of the major challenging topics and the secure key interchange between two legitimate vehicles is an important issue. The multi-environment of VANET has been exploited to extract the secret key and employed security services in VANET. However, it offered more excellence randomness owed to fading, noise multi-path, and velocity difference. Some of the factors like Bit-rate, complication and memory requests are reduced by using a process known as quantization. This paper proposes a new quantization method to extract the secret key for vehicular communications that uses a lossy quantizer in combination with information reconciliation and privacy amplification. Our work focuses on the quantization phase for the secret generation procedure. The comprehensive simulations display the propose method increases the zone and number of the quantization levels to utilize the maximum number of measurements to reduce reasonably the wasted measurements. Vehicular ad hoc networks (dpeaa)DE-He213 Key extraction (dpeaa)DE-He213 Mobile ad hoc networks (dpeaa)DE-He213 Quantization (dpeaa)DE-He213 RSS (dpeaa)DE-He213 Zhang, Weibin aut Zeng, Zhenping aut Abdeldime, M. S aut Enthalten in Wireless personal communications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1994 126(2022), 2 vom: 07. Juni, Seite 1345-1361 (DE-627)271179120 (DE-600)1479327-1 1572-834X nnns volume:126 year:2022 number:2 day:07 month:06 pages:1345-1361 https://dx.doi.org/10.1007/s11277-022-09794-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 126 2022 2 07 06 1345-1361
language	English
source	Enthalten in Wireless personal communications 126(2022), 2 vom: 07. Juni, Seite 1345-1361 volume:126 year:2022 number:2 day:07 month:06 pages:1345-1361
sourceStr	Enthalten in Wireless personal communications 126(2022), 2 vom: 07. Juni, Seite 1345-1361 volume:126 year:2022 number:2 day:07 month:06 pages:1345-1361
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Vehicular ad hoc networks Key extraction Mobile ad hoc networks Quantization RSS
isfreeaccess_bool	false
container_title	Wireless personal communications
authorswithroles_txt_mv	Abdelazeem, Ibraheem @@aut@@ Zhang, Weibin @@aut@@ Zeng, Zhenping @@aut@@ Abdeldime, M. S @@aut@@
publishDateDaySort_date	2022-06-07T00:00:00Z
hierarchy_top_id	271179120
id	SPR048155187
language_de	englisch
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author	Abdelazeem, Ibraheem
spellingShingle	Abdelazeem, Ibraheem misc Vehicular ad hoc networks misc Key extraction misc Mobile ad hoc networks misc Quantization misc RSS An Adaptive Lossly Quantization Technique for Key Extraction Applied in Vehicular Communication
authorStr	Abdelazeem, Ibraheem
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topic_title	An Adaptive Lossly Quantization Technique for Key Extraction Applied in Vehicular Communication Vehicular ad hoc networks (dpeaa)DE-He213 Key extraction (dpeaa)DE-He213 Mobile ad hoc networks (dpeaa)DE-He213 Quantization (dpeaa)DE-He213 RSS (dpeaa)DE-He213
topic	misc Vehicular ad hoc networks misc Key extraction misc Mobile ad hoc networks misc Quantization misc RSS
topic_unstemmed	misc Vehicular ad hoc networks misc Key extraction misc Mobile ad hoc networks misc Quantization misc RSS
topic_browse	misc Vehicular ad hoc networks misc Key extraction misc Mobile ad hoc networks misc Quantization misc RSS
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title	An Adaptive Lossly Quantization Technique for Key Extraction Applied in Vehicular Communication
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title_full	An Adaptive Lossly Quantization Technique for Key Extraction Applied in Vehicular Communication
author_sort	Abdelazeem, Ibraheem
journal	Wireless personal communications
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author_browse	Abdelazeem, Ibraheem Zhang, Weibin Zeng, Zhenping Abdeldime, M. S
container_volume	126
format_se	Elektronische Aufsätze
author-letter	Abdelazeem, Ibraheem
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title_sort	adaptive lossly quantization technique for key extraction applied in vehicular communication
title_auth	An Adaptive Lossly Quantization Technique for Key Extraction Applied in Vehicular Communication
abstract	Abstract Security in vehicular ad hoc network (VANET) is one of the major challenging topics and the secure key interchange between two legitimate vehicles is an important issue. The multi-environment of VANET has been exploited to extract the secret key and employed security services in VANET. However, it offered more excellence randomness owed to fading, noise multi-path, and velocity difference. Some of the factors like Bit-rate, complication and memory requests are reduced by using a process known as quantization. This paper proposes a new quantization method to extract the secret key for vehicular communications that uses a lossy quantizer in combination with information reconciliation and privacy amplification. Our work focuses on the quantization phase for the secret generation procedure. The comprehensive simulations display the propose method increases the zone and number of the quantization levels to utilize the maximum number of measurements to reduce reasonably the wasted measurements. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022
abstractGer	Abstract Security in vehicular ad hoc network (VANET) is one of the major challenging topics and the secure key interchange between two legitimate vehicles is an important issue. The multi-environment of VANET has been exploited to extract the secret key and employed security services in VANET. However, it offered more excellence randomness owed to fading, noise multi-path, and velocity difference. Some of the factors like Bit-rate, complication and memory requests are reduced by using a process known as quantization. This paper proposes a new quantization method to extract the secret key for vehicular communications that uses a lossy quantizer in combination with information reconciliation and privacy amplification. Our work focuses on the quantization phase for the secret generation procedure. The comprehensive simulations display the propose method increases the zone and number of the quantization levels to utilize the maximum number of measurements to reduce reasonably the wasted measurements. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022
abstract_unstemmed	Abstract Security in vehicular ad hoc network (VANET) is one of the major challenging topics and the secure key interchange between two legitimate vehicles is an important issue. The multi-environment of VANET has been exploited to extract the secret key and employed security services in VANET. However, it offered more excellence randomness owed to fading, noise multi-path, and velocity difference. Some of the factors like Bit-rate, complication and memory requests are reduced by using a process known as quantization. This paper proposes a new quantization method to extract the secret key for vehicular communications that uses a lossy quantizer in combination with information reconciliation and privacy amplification. Our work focuses on the quantization phase for the secret generation procedure. The comprehensive simulations display the propose method increases the zone and number of the quantization levels to utilize the maximum number of measurements to reduce reasonably the wasted measurements. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022
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title_short	An Adaptive Lossly Quantization Technique for Key Extraction Applied in Vehicular Communication
url	https://dx.doi.org/10.1007/s11277-022-09794-9
remote_bool	true
author2	Zhang, Weibin Zeng, Zhenping Abdeldime, M. S
author2Str	Zhang, Weibin Zeng, Zhenping Abdeldime, M. S
ppnlink	271179120
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doi_str	10.1007/s11277-022-09794-9
up_date	2024-07-03T17:22:46.512Z
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The multi-environment of VANET has been exploited to extract the secret key and employed security services in VANET. However, it offered more excellence randomness owed to fading, noise multi-path, and velocity difference. Some of the factors like Bit-rate, complication and memory requests are reduced by using a process known as quantization. This paper proposes a new quantization method to extract the secret key for vehicular communications that uses a lossy quantizer in combination with information reconciliation and privacy amplification. Our work focuses on the quantization phase for the secret generation procedure. 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