23 research outputs found

    Defending embedded systems against control flow attacks

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    ABSTRACT This paper presents a control flow enforcement technique based on an Instruction Based Memory Access Control (IB-MAC) implemented in hardware. It is specifically designed to protect low-cost embedded systems against malicious manipulation of their control flow as well as preventing accidental stack overflows. This is achieved by using a simple hardware modification to divide the stack in a data and a control flow stack (or return stack). Moreover access to the control flow stack is restricted only to return and call instructions, which prevents control flow manipulation. Previous solutions tackled the problem of control flow injection on general purpose computing devices and are rarely applicable to the simpler low-cost embedded devices, that lack for example of a Memory Management Unit (MMU) or execution rings. Our approach is binary compatible with legacy applications and only requires minimal changes to the tool-chain. Additionally, it does not increase memory usage, allows an optimal usage of stack memory and prevents accidental stack corruption at run-time. We have implemented and tested IBMAC on the AVR micro-controller using both a simulator and an implementation of the modified core on a FPGA. The implementation on reconfigurable hardware showed a small resulting overhead in terms of number of gates, and therefore a low overhead of expected production costs

    How Unique and Traceable are Usernames?

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    Suppose you find the same username on different online services, what is the probability that these usernames refer to the same physical person? This work addresses what appears to be a fairly simple question, which has many implications for anonymity and privacy on the Internet. One possible way of estimating this probability would be to look at the public information associated to the two accounts and try to match them. However, for most services, these information are chosen by the users themselves and are often very heterogeneous, possibly false and difficult to collect. Furthermore, several websites do not disclose any additional public information about users apart from their usernames (e.g., discus- sion forums or Blog comments), nonetheless, they might contain sensitive information about users. This paper explores the possibility of linking users profiles only by looking at their usernames. The intuition is that the probability that two usernames refer to the same physical person strongly depends on the "entropy" of the username string itself. Our experiments, based on crawls of real web services, show that a significant portion of the users' profiles can be linked using their usernames. To the best of our knowledge, this is the first time that usernames are considered as a source of information when profiling users on the Internet

    Exécution sécurisée de code sur systèmes embarqués

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    Embedded devices are currently used in many critical systems, ranging from automotive to medical devices and industrial control systems. Most of the research on such devices has focused on improving their reliability against unintentional failures, while fewer efforts have been spent to prevent intentional and malicious attacks. These devices are increasingly being connected via wireless and connected to the Internet for remote administration, this increases the risk of remote exploits and malicious code injected in such devices. Failures in such devices might cause physical damage and health and safety risks. Therefore, protecting embedded devices from attacks is of the utmost importance. In this thesis we present novel attacks and defenses against low-end embedded devices. We present several attacks against software-based attestation techniques used in embedded devices. Furthermore we design and implement a novel software-based attestation technique that is immune to the aforementioned attacks. Finally, we design a hardware solution to attest and establish a dynaLes systèmes embarqués sont utilisés dans de nombreux systèmes critiques, depuis les automobiles jusqu'aux les systèmes de contrôle industriels. La plupart des recherches sur ces systèmes embarqués se sont concentrés sur l'amélioration de leur fiabilité face à des fautes ou erreurs de fonctionnent non intentionnelles, moins de travaux on été réalisés considérant les attaques intentionnelles. Ces systèmes embarqués sont de plus en plus connectés, souvent à Internet, via des réseaux sans fils, par exemple pour leur administration à distance. Cela augmente les risques d'attaques à distance ou d'injection de code malicieux. Les fautes de fonctionnement de ces équipements peuvent causer des dommages physiques comme par example rendre des appareils médicaux dangereux. Par conséquent, il est primordial de protéger ces systèmes embarqués contre les attaques. Dans cette thèse nous présentons des attaques et défenses contre les systèmes embarqués contraints. Nous présentons plusieurs attaques contre des techniques d'attestation logicielle utilisées dans les systèmes embarqués. Puis nous présentons la conception et l'implémentation d'une technique d'attestation logicielle qui est résistante aux attaque présentées précédemment. Finalement, nous présentons la conception d'une solution permettant de réaliser l'attestation de code ainsi que la création d'une racine de confiance dynamique (dynamic root of trust) pour les systèmes embarqués. Cette solution est prouvée sure et ne dépend pas d'assomptions fortes faites dans le cas de l'attestation logicielle

    Adaptive Password-Strength Meters from Markov Models

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    International audienceMeasuring the strength of passwords is crucial to ensure the security of password-based authentication. However, current methods to measure password strength have limited accuracy, first, because they use rules that are too simple to capture the complexity of passwords, and second, because password frequencies widely differ from one application to another. In this paper, we present the concept of adaptive password strength meters that estimate password strength using Markov-models. We propose a secure implementation that greatly improves on the accuracy of current techniques
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