The Experts below are selected from a list of 264 Experts worldwide ranked by ideXlab platform

Olivier Markowitch - One of the best experts on this subject based on the ideXlab platform.

  • The bias–variance decomposition in profiled attacks
    Journal of Cryptographic Engineering, 2015
    Co-Authors: Liran Lerman, Gianluca Bontempi, Olivier Markowitch
    Abstract:

    The profiled attacks challenge the security of Cryptographic Devices in the worst case scenario. We elucidate the reasons underlying the success of different profiled attacks (that depend essentially on the context) based on the well-known bias–variance tradeoff developed in the machine learning field. Note that our approach can easily be extended to non-profiled attacks. We show (1) how to decompose (in three additive components) the error rate of an attack based on the bias–variance decomposition, and (2) how to reduce the error rate of a model based on the bias–variance diagnostic. Intuitively, we show that different models having the same error rate require different strategies (according to the bias–variance decomposition) to reduce their errors. More precisely, the success rate of a strategy depends on several criteria such as its complexity, the leakage information and the number of points per trace. As a result, a suboptimal strategy in a specific context can lead the adversary to overestimate the security level of the Cryptographic Device. Our results also bring warnings related to the estimation of the success rate of a profiled attack that can lead the evaluator to underestimate the security level. In brief, certify that a chip leaks (or not) sensitive information represents a hard if not impossible task.

  • the bias variance decomposition in profiled attacks
    Journal of Cryptographic Engineering, 2015
    Co-Authors: Liran Lerman, Gianluca Bontempi, Olivier Markowitch
    Abstract:

    The profiled attacks challenge the security of Cryptographic Devices in the worst case scenario. We elucidate the reasons underlying the success of different profiled attacks (that depend essentially on the context) based on the well-known bias–variance tradeoff developed in the machine learning field. Note that our approach can easily be extended to non-profiled attacks. We show (1) how to decompose (in three additive components) the error rate of an attack based on the bias–variance decomposition, and (2) how to reduce the error rate of a model based on the bias–variance diagnostic. Intuitively, we show that different models having the same error rate require different strategies (according to the bias–variance decomposition) to reduce their errors. More precisely, the success rate of a strategy depends on several criteria such as its complexity, the leakage information and the number of points per trace. As a result, a suboptimal strategy in a specific context can lead the adversary to overestimate the security level of the Cryptographic Device. Our results also bring warnings related to the estimation of the success rate of a profiled attack that can lead the evaluator to underestimate the security level. In brief, certify that a chip leaks (or not) sensitive information represents a hard if not impossible task.

  • COSADE - Semi-Supervised template attack
    Constructive Side-Channel Analysis and Secure Design, 2013
    Co-Authors: Liran Lerman, Gianluca Bontempi, Stephane Fernandes Medeiros, Nikita Veshchikov, Cédric Meuter, Olivier Markowitch
    Abstract:

    Side channel attacks take advantage of information leakages in Cryptographic Devices. Template attacks form a family of side channel attacks which is reputed to be extremely effective. This kind of attacks assumes that the attacker fully controls a Cryptographic Device before attacking a similar one. In this paper, we propose to relax this assumption by generalizing the template attack using a method based on a semi-supervised learning strategy. The effectiveness of our proposal is confirmed by software simulations, by experiments on a 8-bit microcontroller and by a comparison to a template attack as well as to two supervised machine learning methods.

  • Semi-Supervised Template Attack.
    IACR Cryptology ePrint Archive, 2012
    Co-Authors: Liran Lerman, Gianluca Bontempi, Stephane Fernandes Medeiros, Nikita Veshchikov, Cédric Meuter, Olivier Markowitch
    Abstract:

    Side channel attacks take advantage of the information leakage in a Cryptographic Device. A template attack is a family of side channel attacks which is reputed to be extremely effective. This kind of attacks supposes that the attacker can fully control a Cryptographic Device before attacking a similar one. In this paper, we propose a method based on a semi-supervised learning strategy to relax this assumption. The effectiveness of our proposal is confirmed by software simulations as well as by experiments on a 8-bit microcontroller.

Liran Lerman - One of the best experts on this subject based on the ideXlab platform.

  • The bias–variance decomposition in profiled attacks
    Journal of Cryptographic Engineering, 2015
    Co-Authors: Liran Lerman, Gianluca Bontempi, Olivier Markowitch
    Abstract:

    The profiled attacks challenge the security of Cryptographic Devices in the worst case scenario. We elucidate the reasons underlying the success of different profiled attacks (that depend essentially on the context) based on the well-known bias–variance tradeoff developed in the machine learning field. Note that our approach can easily be extended to non-profiled attacks. We show (1) how to decompose (in three additive components) the error rate of an attack based on the bias–variance decomposition, and (2) how to reduce the error rate of a model based on the bias–variance diagnostic. Intuitively, we show that different models having the same error rate require different strategies (according to the bias–variance decomposition) to reduce their errors. More precisely, the success rate of a strategy depends on several criteria such as its complexity, the leakage information and the number of points per trace. As a result, a suboptimal strategy in a specific context can lead the adversary to overestimate the security level of the Cryptographic Device. Our results also bring warnings related to the estimation of the success rate of a profiled attack that can lead the evaluator to underestimate the security level. In brief, certify that a chip leaks (or not) sensitive information represents a hard if not impossible task.

  • the bias variance decomposition in profiled attacks
    Journal of Cryptographic Engineering, 2015
    Co-Authors: Liran Lerman, Gianluca Bontempi, Olivier Markowitch
    Abstract:

    The profiled attacks challenge the security of Cryptographic Devices in the worst case scenario. We elucidate the reasons underlying the success of different profiled attacks (that depend essentially on the context) based on the well-known bias–variance tradeoff developed in the machine learning field. Note that our approach can easily be extended to non-profiled attacks. We show (1) how to decompose (in three additive components) the error rate of an attack based on the bias–variance decomposition, and (2) how to reduce the error rate of a model based on the bias–variance diagnostic. Intuitively, we show that different models having the same error rate require different strategies (according to the bias–variance decomposition) to reduce their errors. More precisely, the success rate of a strategy depends on several criteria such as its complexity, the leakage information and the number of points per trace. As a result, a suboptimal strategy in a specific context can lead the adversary to overestimate the security level of the Cryptographic Device. Our results also bring warnings related to the estimation of the success rate of a profiled attack that can lead the evaluator to underestimate the security level. In brief, certify that a chip leaks (or not) sensitive information represents a hard if not impossible task.

  • COSADE - Semi-Supervised template attack
    Constructive Side-Channel Analysis and Secure Design, 2013
    Co-Authors: Liran Lerman, Gianluca Bontempi, Stephane Fernandes Medeiros, Nikita Veshchikov, Cédric Meuter, Olivier Markowitch
    Abstract:

    Side channel attacks take advantage of information leakages in Cryptographic Devices. Template attacks form a family of side channel attacks which is reputed to be extremely effective. This kind of attacks assumes that the attacker fully controls a Cryptographic Device before attacking a similar one. In this paper, we propose to relax this assumption by generalizing the template attack using a method based on a semi-supervised learning strategy. The effectiveness of our proposal is confirmed by software simulations, by experiments on a 8-bit microcontroller and by a comparison to a template attack as well as to two supervised machine learning methods.

  • Semi-Supervised Template Attack.
    IACR Cryptology ePrint Archive, 2012
    Co-Authors: Liran Lerman, Gianluca Bontempi, Stephane Fernandes Medeiros, Nikita Veshchikov, Cédric Meuter, Olivier Markowitch
    Abstract:

    Side channel attacks take advantage of the information leakage in a Cryptographic Device. A template attack is a family of side channel attacks which is reputed to be extremely effective. This kind of attacks supposes that the attacker can fully control a Cryptographic Device before attacking a similar one. In this paper, we propose a method based on a semi-supervised learning strategy to relax this assumption. The effectiveness of our proposal is confirmed by software simulations as well as by experiments on a 8-bit microcontroller.

Gianluca Bontempi - One of the best experts on this subject based on the ideXlab platform.

  • The bias–variance decomposition in profiled attacks
    Journal of Cryptographic Engineering, 2015
    Co-Authors: Liran Lerman, Gianluca Bontempi, Olivier Markowitch
    Abstract:

    The profiled attacks challenge the security of Cryptographic Devices in the worst case scenario. We elucidate the reasons underlying the success of different profiled attacks (that depend essentially on the context) based on the well-known bias–variance tradeoff developed in the machine learning field. Note that our approach can easily be extended to non-profiled attacks. We show (1) how to decompose (in three additive components) the error rate of an attack based on the bias–variance decomposition, and (2) how to reduce the error rate of a model based on the bias–variance diagnostic. Intuitively, we show that different models having the same error rate require different strategies (according to the bias–variance decomposition) to reduce their errors. More precisely, the success rate of a strategy depends on several criteria such as its complexity, the leakage information and the number of points per trace. As a result, a suboptimal strategy in a specific context can lead the adversary to overestimate the security level of the Cryptographic Device. Our results also bring warnings related to the estimation of the success rate of a profiled attack that can lead the evaluator to underestimate the security level. In brief, certify that a chip leaks (or not) sensitive information represents a hard if not impossible task.

  • the bias variance decomposition in profiled attacks
    Journal of Cryptographic Engineering, 2015
    Co-Authors: Liran Lerman, Gianluca Bontempi, Olivier Markowitch
    Abstract:

    The profiled attacks challenge the security of Cryptographic Devices in the worst case scenario. We elucidate the reasons underlying the success of different profiled attacks (that depend essentially on the context) based on the well-known bias–variance tradeoff developed in the machine learning field. Note that our approach can easily be extended to non-profiled attacks. We show (1) how to decompose (in three additive components) the error rate of an attack based on the bias–variance decomposition, and (2) how to reduce the error rate of a model based on the bias–variance diagnostic. Intuitively, we show that different models having the same error rate require different strategies (according to the bias–variance decomposition) to reduce their errors. More precisely, the success rate of a strategy depends on several criteria such as its complexity, the leakage information and the number of points per trace. As a result, a suboptimal strategy in a specific context can lead the adversary to overestimate the security level of the Cryptographic Device. Our results also bring warnings related to the estimation of the success rate of a profiled attack that can lead the evaluator to underestimate the security level. In brief, certify that a chip leaks (or not) sensitive information represents a hard if not impossible task.

  • COSADE - Semi-Supervised template attack
    Constructive Side-Channel Analysis and Secure Design, 2013
    Co-Authors: Liran Lerman, Gianluca Bontempi, Stephane Fernandes Medeiros, Nikita Veshchikov, Cédric Meuter, Olivier Markowitch
    Abstract:

    Side channel attacks take advantage of information leakages in Cryptographic Devices. Template attacks form a family of side channel attacks which is reputed to be extremely effective. This kind of attacks assumes that the attacker fully controls a Cryptographic Device before attacking a similar one. In this paper, we propose to relax this assumption by generalizing the template attack using a method based on a semi-supervised learning strategy. The effectiveness of our proposal is confirmed by software simulations, by experiments on a 8-bit microcontroller and by a comparison to a template attack as well as to two supervised machine learning methods.

  • Semi-Supervised Template Attack.
    IACR Cryptology ePrint Archive, 2012
    Co-Authors: Liran Lerman, Gianluca Bontempi, Stephane Fernandes Medeiros, Nikita Veshchikov, Cédric Meuter, Olivier Markowitch
    Abstract:

    Side channel attacks take advantage of the information leakage in a Cryptographic Device. A template attack is a family of side channel attacks which is reputed to be extremely effective. This kind of attacks supposes that the attacker can fully control a Cryptographic Device before attacking a similar one. In this paper, we propose a method based on a semi-supervised learning strategy to relax this assumption. The effectiveness of our proposal is confirmed by software simulations as well as by experiments on a 8-bit microcontroller.

Graham Steel - One of the best experts on this subject based on the ideXlab platform.

  • A Generic Security API for Symmetric Key Management on Cryptographic Devices
    2009
    Co-Authors: Véronique Cortier, Graham Steel
    Abstract:

    Security APIs are used to define the boundary between trusted and untrusted code. The security properties of existing APIs are not always clear. In this paper, we give a new generic API for managing symmetric keys on a trusted Cryptographic Device. We state and prove security properties for our API. In particular, our API offers a high level of security even when the host machine is controlled by an attacker. Our API is generic in the sense that it can implement a wide variety of (symmetric key) protocols. As a proof of concept, we give an algorithm for automatically instantiating the API commands for a given key management protocol. We demonstrate the algorithm on a set of key establishment protocols from the Clark-Jacob suite.

  • Synthesising Secure APIs
    2009
    Co-Authors: Véronique Cortier, Graham Steel
    Abstract:

    Security APIs are used to define the boundary between trusted and untrusted code. The security properties of existing API are not always clear. In this paper, we give a new generic API for managing symmetric keys on a trusted Cryptographic Device. We state and prove security properties for the API. In particular, our API offers a high level of security even when the host machine is controlled by an attacker. Our API is generic in the sense that it can implement a wide variety of (symmetric key) protocols. As a proof of concept, we give an algorithm for automatically instantiating the API commands for a given key management protocol. We demonstrate the algorithm on a set of key establishment protocols from the Clark-Jacob suite.

  • ESORICS - A generic security API for symmetric key management on Cryptographic Devices
    Computer Security – ESORICS 2009, 2009
    Co-Authors: Véronique Cortier, Graham Steel
    Abstract:

    Security APIs are used to define the boundary between trusted and untrusted code. The security properties of existing APIs are not always clear. In this paper, we give a new generic API for managing symmetric keys on a trusted Cryptographic Device. We state and prove security properties for our API. In particular, our API offers a high level of security even when the host machine is controlled by an attacker. Our API is generic in the sense that it can implement a wide variety of (symmetric key) protocols. As a proof of concept, we give an algorithm for automatically instantiating the API commands for a given key management protocol. We demonstrate the algorithm on a set of key establishment protocols from the Clark-Jacob suite.

Jean-luc Danger - One of the best experts on this subject based on the ideXlab platform.

  • Analysis of Electromagnetic Information Leakage From Cryptographic Devices With Different Physical Structures
    IEEE Transactions on Electromagnetic Compatibility, 2013
    Co-Authors: Yu-ichi Hayashi, Naofumi Homma, Takafumi Aoki, Takaaki Mizuki, Hideaki Sone, Laurent Sauvage, Jean-luc Danger
    Abstract:

    This paper presents a novel analysis of electromagnetic (EM) information leakage from Cryptographic Devices, based on the electromagnetic interference (EMI) theory. In recent years, side-channel attack using side-channel information (e.g., power consumption and EM radiation) is of major concern for designers of Cryptographic Devices. However, few studies have been conducted to investigate how EM information leakage changes according to Device's physical parameters. In this paper, we introduce a Cryptographic Device model to analyze EM information leakage based on the EMI theory in a systematic manner. This Device model makes it possible to acquire the frequency characteristics of EM radiation depending on physical parameters, such as board size and power-line length, accurately. The analysis results show that EM information leakage can be explained by the major EMI parameters such as board size and cable length attached to the board. In addition, we demonstrate that the intensity of EM information leakage from a generic Device is also explained by board size and cable length.

  • Efficient Evaluation of EM Radiation Associated With Information Leakage From Cryptographic Devices
    IEEE Transactions on Electromagnetic Compatibility, 2013
    Co-Authors: Yu-ichi Hayashi, Naofumi Homma, Takafumi Aoki, Takaaki Mizuki, Hideaki Sone, Laurent Sauvage, Haruki Shimada, Jean-luc Danger
    Abstract:

    This paper presents an efficient map generation technique for evaluating the intensity of electromagnetic (EM) radiation associated with information leakage for Cryptographic Devices at the printed circuit board level. First, we investigate the relation between the intensity of the overall EM radiation and the intensity of EM information leakage on a Cryptographic Device. For this purpose, we prepare a map of the magnetic field on the Device by using an EM scanning system, after which we perform correlation electromagnetic analysis (CEMA) at all measurement points on the Device, including points above the Cryptographic module. The examined Device is a standard evaluation board for Cryptographic modules (side-channel attack standard evaluation board), where a Cryptographic circuit is implemented on one of the field-programmable gate arrays on the board. With this experiment, we demonstrate that both an EM radiation map and an information leakage map can be generated simultaneously by scanning the board only once. We also confirm that the generated map is in good agreement with the corresponding map obtained from exhaustive CEMAs.

  • Efficient mapping of EM radiation associated with information leakage for Cryptographic Devices
    2012
    Co-Authors: Haruki Shimada, Naofumi Homma, Yu-ichi Hayashi, Takafumi Aoki, Takaaki Mizuki, Hideaki Sone, Laurent Sauvage, Jean-luc Danger
    Abstract:

    This paper presents an efficient map generation technique for evaluating the intensity of electromagnetic (EM) radiation associated with information leakage for Cryptographic Devices at the PCB level. First, we investigate the relation between the intensity of the overall EM radiation and the intensity of EM information leakage on a Cryptographic Device. For this purpose, we prepare a map of the magnetic field on the Device by using an EM scanning system, after which we perform correlation electromagnetic analysis (CEMA) at all measurement points on the Device, including points above the Cryptographic module. The examined Device is a standard evaluation board for Cryptographic modules (SASEBO), where a Cryptographic circuit is implemented on one of the FPGAs on the board. With this experiment, we demonstrate that an efficient map of EM radiation associated with information leakage can be generated on the basis of an EM radiation map. We also confirm that the generated map is in fair agreement with the corresponding map obtained from exhaustive CEMA.

  • Characterization of the Information Leakage of Cryptographic Devices by Using EM Anal
    Electromagnetic Radiation, 2012
    Co-Authors: Olivier Meynard, Jean-luc Danger, Yu-ichi Hayashi, Sylvain Guilley, Naofumi Homma
    Abstract:

    Cryptographic modules (software or hardware implementations of Cryptographic algorithms) are widely used in our daily life in different applications in order to secure digital transactions and exchanges. In particular, Cryptographic hardware is essential in smartcards, identification systems, mobile phones, pay television set-top boxes, transportation services and so on. This hardware component embeds Cryptographic algorithms that are deemed safer and unbreakable from a mathematical point of view, and thus increases the confidence and robustness of Cryptographic functions. However, the hardware implementation is still vulnerable to physical attacks. Side Channel Analysis (SCA) is a major threat for crypto-systems as they disclose some information about the internal process and the sensitive data. An electronic circuit needs some time to produce its results (such as a ciphertext in the case of encryption) and an amount of energy to switch states at each clock period. The operating times, the power dissipation, or the electromagnetic radiations are directly modulated by the data that are processed. Consequently the Cryptographic Device leaks some clues about the inner secrets and an attacker can retrieve secrets computed by the Cryptographic Device, just by analysing these externally measurable quantities without touching the component. Thus, those unintentional physical emanations can be analysed in a view to derive some sensitive information from them. Such analyses are altogether referred to as Side-Channel Attacks.

  • Identification of information leakage spots on a Cryptographic Device with an RSA processor
    2011 IEEE International Symposium on Electromagnetic Compatibility, 2011
    Co-Authors: Olivier Meynard, Naofumi Homma, Yu-ichi Hayashi, Sylvain Guilley, Jean-luc Danger
    Abstract:

    This paper investigates a relationship between the intensity of EM radiation and that of EM information leakage on a Cryptographic Device. For this purpose, we first observe an EM-field map on a Cryptographic Device by an EM scanning system, and then perform simple electromagnetic analysis (SEMA) experiments at some distinct points on the Device including over the module. The target Device considered here is a Side-channel Attack Standard Evaluation Board (SASEBO) with an RSA hardware implemented in an FPGA. Through the experiment, we demonstrate which points are effective for EM information leakage. The result suggests that the position of greatest EM intensity is not always the most effective point in EM information leakage.