The More You Know: Improving Laser Fault Injection with Prior Knowledge

We consider finding as many faults as possible on the target device in the laser fault injection security evaluation. Since the search space is large, we require efficient search methods. Recently, an evolutionary approach using a memetic algorithm was proposed and shown to find more interesting parameter combinations than random search, which is commonly used. Unfortunately, once a variation on the bench or target is introduced, the process must be repeated to find suitable parameter combinations anew. To negate the effect of variation, we propose a novel method combining a memetic algorithm with a machine learning approach called a decision tree. Our approach improves the memetic algorithm by using prior knowledge of the target introduced in the initial phase of the memetic algorithm. In our experiments, the decision tree rules enhance the performance of the memetic algorithm by finding more interesting faults in different samples of the same target. Our approach shows more than two orders of magnitude better performance than random search and up to 60% better performance than previous state-of-the-art results with a memetic algorithm. Another advantage of our approach is human-readable rules, allowing the first insights into the explainability of target characterization for laser fault injection

Histological discrimination of fresh and frozen/thawed fish meat: European hake (Merluccius merluccius) as a possible model for white meat fish species

The present study aimed at setting up a standard operating histological procedure to discriminate fresh from frozen-thawed fish products of the species Merluccius merluccius (European hake). A preliminary histological analysis of fresh M. merluccius muscle was performed to select the sampling site and highlight possible time-dependent tissue alterations during shelf-life. To set a suitable operational grid for discriminating the freezing process, morphological and morphometrical parameters were assessed on 90 muscle tissue samples collected from 30 fresh, 30 experimentally frozen at -20°31 C and 30 Individual Quick Frozen (IQF) specimens of M. merluccius. Structural score, presence of freezing vacuoles, a number of vacuoles per field higher than 1.12 and the presence of interstitial proteinaceous material, which had achieved statistical significance in group comparisons were chosen as freezing markers. Accuracy and repeatability, assessed on the analysis of two independent operators (on-training and expert), showed high analytical specificity and sensitivity and a concordant diagnostic performance regardless the operators expertise. The grid was finally validated by a single blind test on 30 additional M. merluccius commercial products and allowed the allocation of all the samples to fresh or frozen status without inconclusive results. The method could be profitably applied against fraudulent adulteration practices

Design and development of a recongurable cryptographic co-processor

Nowadays hi-tech secure products need more services and more security. Furthermore the corresponding market is now oriented towards more exibility. In this thesis we propose as novel solution a Multi-algorithm Cryptographic Co-processor called Celator. Celator is able to encrypt or decrypt data blocks using private key encryption algorithms such as Advanced Encryption Standard (AES) [1] or Data Encryption Standard (DES) [2]. Moreover Celator allows condensing data using the Secure Hash Algorithms (SHA) [3]. These algorithms are frequently implemented in hi-tech secure products in software or in hardware mode. Celator belongs to the class of the exible hardware implementations, and allows an user implementing its own cryptographic algorithm under specific conditions. Celator architecture is based on a 4x4 Processing Elements (PE) systolic array, a Controller with a Finite State Machine (FSM) and a local memory. Data are encrypted or decrypted by the PE array. This thesis presents Celator architecture, as well as its AES, DES, and SHA basic operations. Celator performances are then given and compared to other security circuits.Les circuits à haut technologie d'aujourd'hui requièrent toujours plus de services et de sécurité. Le marché correspondant est orienté vers de la reconfigurabilité. Dans cette thèse je propose une nouvelle solution de coprocesseur cryptographique multi-algorithmes, appelé Celator. Celator est capable de crypter et décrypter des blocs de données en utilisant des algorithmes cryptographiques à clé symétrique tel que l'Advanced Encryption Standard (AES) ou le Data Encryption Standard (DES). De plus, Celator permet de hacher des données en utilisant le Secure Hash Algorithm (SHA). Ces algorithmes sont implémentés de façon matérielle ou logicielle dans les produits sécurisés. Celator appartient à la classe des implémentations matérielles flexibles, et permet à son utilisateur, sous certaines conditions, d'exécuter des algorithmes cryptographiques standards ou propriétaires.L'architecture de Celator est basée sur un réseau systolique de 4x4 Processing Elements, nommé réseau de PE, commandé par un Contrôleur réalisé avec une Machine d'États Finis (FSM) et une mémoire locale.Cette thèse présente l'architecture de Celator, ainsi que les opérations de base nécessaires pour qu'il exécute AES, DES et SHA. Les performances de Celator sont également présentées, et comparées à celles d'autres circuits sécurisés

Conception et developpement d'un coprocesseur cryptographique reconfigurable

Nowadays hi-tech secure products need more services and more security. Furthermore the corresponding market is now oriented towards more exibility. In this thesis we propose as novel solution a Multi-algorithm Cryptographic Co-processor called Celator. Celator is able to encrypt or decrypt data blocks using private key encryption algorithms such as Advanced Encryption Standard (AES) or Data Encryption Standard (DES) . Moreover Celator allows condensing data using the Secure Hash Algorithms (SHA). These algorithms are frequently implemented in hi-tech secure products in software or in hardware mode. Celator belongs to the class of the exible hardware implementations, and allows an user implementing its own cryptographic algorithm under specific conditions. Celator architecture is based on a 4x4 Processing Elements (PE) systolic array, a Controller with a Finite State Machine (FSM) and a local memory. Data are encrypted or decrypted by the PE array. This thesis presents Celator architecture, as well as its AES, DES, and SHA basic operations. Celator performances are then given and compared to other security circuitsDans cette thèse, les aspects sécuritaires n'ont pas été analysés. Nous considérons les opérations d'écriture ou de lecture dans les registres ou dans la CRAM comme des opérations sûres. Grâce à la structure de Celator, pendant les procès de cryptage ou décryptage, les données peuvent être masquées : par exemple, les données peuvent être "xorées" une ou plusieurs fois avec des variables aléatoires, afin de les rendre plus difficilement interceptables par des personnes malveillantes, par des attaques de type Side Channel Attacks. Le prochain pas de nos investigations sera l'implémentation d'autres algorithmes dans Celator. L' architecture du réseau de PE sera peut être modifiée, mais sa surface ne sera pas affectée de manière considérable, grâce surtout à sa structure et à son jeu d'instruction génériques. Notre objectif à long terme sera l'étude et le développement de plateformes sûres pour sécuriser les échanges de données entre le CPU et Celator, ainsi que entre le CPU et des sources de données externesAIX-MARSEILLE1-Inst.Médit.tech (130552107) / SudocSudocFranceF

On the Importance of Initial Solutions Selection in Fault Injection

Fault injection attacks require the adversary to select suitable parameters for the attack. In this work, we consider laser fault injection and parameters like the location of the laser shot $(x,\ y)$, delay, pulse width, and intensity of the laser. The parameter selection process can be translated into an optimization problem. A very popular and successful method for various optimization problems is the genetic algorithm. To further improve the performance of a genetic algorithm, it is possible to combine it with local search to obtain a memetic algorithm. We conduct several experiments comparing the performance of the memetic algorithm and the random search algorithm for finding faults. We investigate the influence of different initialization techniques on the performance of the memetic algorithm. In our experiments, the memetic algorithm is significantly better at finding faults than the random search. While evaluating different initialization techniques, we did not observe significant differences when averaging results. However, when considering the stability of the results with a memetic algorithm based on different initialization techniques, we can distinguish preferable techniques, such as LHSMDU and the Taguchi method.Accepted author manuscriptCyber Securit

The More You Know: Improving Laser Fault Injection with Prior Knowledge

We consider finding as many faults as possible on the target device in the laser fault injection security evaluation. Since the search space is large, we require efficient search methods. Recently, an evolutionary approach using a memetic algorithm was proposed and shown to find more interesting parameter combinations than random search, which is commonly used. Unfortunately, once a variation on the bench or target is introduced, the process must be repeated to find suitable parameter combinations anew.To negate the effect of variation, we propose a novel method combining a memetic algorithm with a machine learning approach called a decision tree. Our approach improves the memetic algorithm by using prior knowledge of the target introduced in the initial phase of the memetic algorithm. In our experiments, the decision tree rules enhance the performance of the memetic algorithm by finding more interesting faults in different samples of the same target. Our approach shows more than two orders of magnitude better performance than random search and up to 60% better performance than previous state-of-the-art results with a memetic algorithm. Another advantage of our approach is human-readable rules, allowing the first insights into the explainability of target characterization for laser fault injection.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Cyber Securit

ACFoam Supreme<TM>/Energy Shield(R)

Aussi disponible en fran\ue7aisPeer reviewed: NoNRC publication: Ye