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Selected Areas in Cryptography – SAC 2024 31st International Conference, Montreal, QC, Canada, August 28–30, 2024, Revised Selected Papers, Part II

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Dettagli

Genere:Libro
Lingua: Inglese
Editore:

Springer

Pubblicazione: 03/2025





Trama

This two-volume set LNCS 15516-15517 contains revised selected papers from the 31st International Conference on Selected Areas in Cryptography, SAC 2024, held in Montreal, QC, Canada, in August 2024.

The 25 full papers presented in these proceedings were carefully reviewed and selected from 95 submissions. The papers are organized in the following topical sections:

Part I: Privacy-preserving cryptography; post-quantum cryptography; attacks on public-key cryptography; and identity-based encryption.

Part II: Authenticated encryption; symmetric design strategies; cryptanalysis of arithmetization-oriented primitives; symmetric primitive design; and implementations and side-channel analysis.





Sommario

.- Authenticated Encryption.
.- Generic Security of the Ascon Mode: On the Power of Key Blinding.
.- Fast Parallelizable Misuse-Resistant Authenticated Encryption: Low Latency (Decryption-Fast) SIV.
.- Provably Secure Online Authenticated Encryption and Bidirectional Online Channels.
.- Symmetric Design Strategies.
.- Classical and Quantum Generic Attacks on 6-round Feistel Schemes.
.- Weightwise (almost) perfectly balanced functions based on total orders.
.- Generalized Triangular Dynamical System: An Algebraic System for Constructing Cryptographic Permutations over Finite Fields.
.- Cryptanalysis of Arithmetization-Oriented Primitives.
.- A Univariate Attack against the Limited-Data Instance of Ciminion.
.- Improved Algebraic Attacks on Round-Reduced LowMC with Single-Data Complexity.
.- Symmetric Primitive Design.
.- Minimize the Randomness in Rasta-Like Designs: How Far Can We Go? Application to PASTA.
.- Koala: A Low-Latency Pseudorandom Function.
.- Implementations and Side-Channel Analysis.
.- Modular Multiplication in the AMNS Representation: Hardware Implementation.
.- Train Wisely: Multifidelity Bayesian Optimization Hyperparameter Tuning in Deep Learning-based Side-Channel Analysis.











Altre Informazioni

ISBN:

9783031828409

Condizione: Nuovo
Collana: Lecture Notes in Computer Science
Dimensioni: 235 x 155 mm
Formato: Brossura
Illustration Notes:XII, 318 p. 51 illus., 26 illus. in color.
Pagine Arabe: 318
Pagine Romane: xii


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