Search results for "Probabilistic inference"

showing 2 items of 2 documents

Generalized Logical Operations among Conditional Events

2018

We generalize, by a progressive procedure, the notions of conjunction and disjunction of two conditional events to the case of n conditional events. In our coherence-based approach, conjunctions and disjunctions are suitable conditional random quantities. We define the notion of negation, by verifying De Morgan’s Laws. We also show that conjunction and disjunction satisfy the associative and commutative properties, and a monotonicity property. Then, we give some results on coherence of prevision assessments for some families of compounded conditionals; in particular we examine the Frechet-Hoeffding bounds. Moreover, we study the reverse probabilistic inference from the conjunction $\mathcal…

FOS: Computer and information sciencesSettore MAT/06 - Probabilita' E Statistica MatematicaComputer Science - Artificial IntelligenceComputer scienceMonotonic functionProbabilistic reasoning02 engineering and technologyCommutative Algebra (math.AC)Conditional random quantitieFréchet-Hoeffding boundCoherent extensionNegationArtificial IntelligenceQuasi conjunction0202 electrical engineering electronic engineering information engineeringFOS: MathematicsCoherent prevision assessmentConditional eventNon-monotonic logicRule of inferenceCommutative propertyAssociative propertyDiscrete mathematicsProbability (math.PR)Probabilistic logicOrder (ring theory)ConjunctionMathematics - LogicCoherence (philosophical gambling strategy)p-entailmentProbabilistic inferenceMathematics - Commutative AlgebraConjunction (grammar)Artificial Intelligence (cs.AI)020201 artificial intelligence & image processingInference ruleNegationLogic (math.LO)Mathematics - ProbabilityDisjunction
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Bayesian Modeling for Differential Cryptanalysis of Block Ciphers: A DES Instance

2023

Encryption algorithms based on block ciphers are among the most widely adopted solutions for providing information security. Over the years, a variety of methods have been proposed to evaluate the robustness of these algorithms to different types of security attacks. One of the most effective analysis techniques is differential cryptanalysis, whose aim is to study how variations in the input propagate on the output. In this work we address the modeling of differential attacks to block cipher algorithms by defining a Bayesian framework that allows a probabilistic estimation of the secret key. In order to prove the validity of the proposed approach, we present as case study a differential att…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniGeneral Computer ScienceGeneral EngineeringGeneral Materials ScienceElectrical and Electronic EngineeringDifferential Cryptanalysis Bayesian Networks Probabilistic Inference DESIEEE Access
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