Finding the differential characteristics of block ciphers with neural networks
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Publication:933659
DOI10.1016/j.ins.2008.02.016zbMath1283.94047OpenAlexW2149552539WikidataQ121435089 ScholiaQ121435089MaRDI QIDQ933659
Babak Sadeghiyan, Reza Safabakhsh, Abbas Ghaemi Bafghi
Publication date: 24 July 2008
Published in: Information Sciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.ins.2008.02.016
simulated annealingblock cipherdifferential cryptanalysisBoltzmann machinechaotic Boltzmann machinechaotic Hopfielddifferential operation modelhopfield network
Related Items (5)
Approximation capabilities of multilayer fuzzy neural networks on the set of fuzzy-valued functions ⋮ Approximation of fuzzy-valued functions by regular fuzzy neural networks and the accuracy analysis ⋮ Passive learning and input-to-state stability of switched Hopfield neural networks with time-delay ⋮ A unified method for finding impossible differentials of block cipher structures ⋮ Security analysis of the public key algorithm based on Chebyshev polynomials over the integer ring \(Z_{N}\)
Uses Software
Cites Work
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- Attacks of simple block ciphers via efficient heuristics
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- OWA trees and their role in security modeling using attack trees
- Serpent: A New Block Cipher Proposal
- Neural networks and physical systems with emergent collective computational abilities.
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