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Cryptology and Network Security with Machine Learning

Über Cryptology and Network Security with Machine Learning

The book features original papers from International Conference on Cryptology & Network Security with Machine Learning (ICCNSML 2022), organized by PSIT, Kanpur, India during 16 ¿ 18 December 2022. This conference proceeding will provide the understanding of core concepts of Cryptology & Network Security with ML in data communication. The book covers research papers in public key cryptography, elliptic curve cryptography, post quantum cryptography, lattice based cryptography, non-commutative ring based cryptography, cryptocurrency, authentication, key agreement, Hash functions, block/stream ciphers, polynomial based cryptography, code based cryptography, NTRU cryptosystems, security and privacy in machine learning, block chain, IoT security, wireless security protocols, cryptanalysis, number theory, quantum computing, cryptographic aspects of network security, complexity theory, and cryptography with machine learning.

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  • Sprache:
  • Englisch
  • ISBN:
  • 9789819922284
  • Einband:
  • Gebundene Ausgabe
  • Seitenzahl:
  • 484
  • Veröffentlicht:
  • 18. Oktober 2023
  • Ausgabe:
  • 23001
  • Abmessungen:
  • 160x30x241 mm.
  • Gewicht:
  • 975 g.
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Beschreibung von Cryptology and Network Security with Machine Learning

The book features original papers from International Conference on Cryptology & Network Security with Machine Learning (ICCNSML 2022), organized by PSIT, Kanpur, India during 16 ¿ 18 December 2022. This conference proceeding will provide the understanding of core concepts of Cryptology & Network Security with ML in data communication. The book covers research papers in public key cryptography, elliptic curve cryptography, post quantum cryptography, lattice based cryptography, non-commutative ring based cryptography, cryptocurrency, authentication, key agreement, Hash functions, block/stream ciphers, polynomial based cryptography, code based cryptography, NTRU cryptosystems, security and privacy in machine learning, block chain, IoT security, wireless security protocols, cryptanalysis, number theory, quantum computing, cryptographic aspects of network security, complexity theory, and cryptography with machine learning.

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