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Abstract-Security is a major issue nowadays for the embedded systems community. Untrustworthy authorities may use a wide range of attacks in order to retrieve critical information. This paper introduces ARMHEx, a practical solution targeting DIFT (Dynamic Information Flow Tracking) on ARM-based SoCs (e.g. Xilinx Zynq). Current DIFT implementations suffer from two major drawbacks. First, recovering required information for DIFT is generally based on software instrumentation leading to high time overheads. ARMHEx takes profit of ARM CoreSight debug components and static analysis to drastically reduce instrumentation time overhead (up to 90% compared to existing works). Then, security of the DIFT hardware extension itself is not considered in related works. In this work, we tackle this issue by proposing a solution based on ARM Trustzone.

Modern computing systems have grown in complexity, and the attack surface has increased accordingly. Even though system components are generally carefully designed and even verified by different groups of people, the composition of these components is often regarded with less attention. This paves the way for "architectural attacks", a class of security vulnerabilities where the attacker is able to threaten the security of the system even if each of its components continues to act as expected. In this article, we introduce FreeSpec, a formalism built upon the key idea that components can be modelled as programs with algebraic effects to be realized by other components. FreeSpec allows for the modular modelling of a complex system, by defining idealized components connected together, and the modular verification of the properties of their composition. In addition, we have implemented a framework for the Coq proof assistant based on FreeSpec. OSApp Execution Unit MMU Cache APIC IOMMU MCH Management Engine DRAM Controller VGA Controller SENTER Sandman [6], SpeedRacer [5] SMRAM cache poisoning [2,3] DMA Attacks [7] Sinkhole [4]

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National audienceThe purpose of this paper is the modelization and simulation of zombie machines for the evaluation of Network Intrusion Detection Systems (NIDS), used to detect botnets. We propose an automatic method to infer zombies behaviors through the analysis of messages exchanged with their masters. Once computed, a model provides a solution to generate realistic and manageable traffic, which is mandatory for an NIDS evaluation. We propose to use a Stochastic Mealy Machine to model zombies behavior, and an active inference algorithm to learn it. With our approach, it is possible to generate a realistic traffic corresponding to the communications of botnets while ensuring its controllability in the context of an NIDS evaluation

Abstract. Over time, hardware designs have constantly grown in complexity and modern platforms involve multiple interconnected hardware components. During the last decade, several vulnerability disclosures have proven that trust in hardware can be misplaced. In this article, we give a formal definition of Hardware-based Security Enforcement (HSE) mechanisms, a class of security enforcement mechanisms such that a software component relies on the underlying hardware platform to enforce a security policy. We then model a subset of a x86-based hardware platform specifications and we prove the soundness of a realistic HSE mechanism within this model using Coq, a proof assistant system.

Highly privileged software, such as firmware, is an attractive target for attackers. Thus, BIOS vendors use cryptographic signatures to ensure firmware integrity at boot time. Nevertheless, such protection does not prevent an attacker from exploiting vulnerabilities at runtime. To detect such attacks, we propose an event-based behavior monitoring approach that relies on an isolated co-processor. We instrument the code executed on the main CPU to send information about its behavior to the monitor. This information helps to resolve the semantic gap issue. Our approach does not depend on a specific model of the behavior nor on a specific target. We apply this approach to detect attacks targeting the System Management Mode (SMM), a highly privileged x86 execution mode executing firmware code at runtime. We model the behavior of SMM using invariants of its control-flow and relevant CPU registers (CR3 and SMBASE). We instrument two open-source firmware implementations: EDK II and coreboot. We evaluate the ability of our approach to detect state-of-the-art attacks and its runtime execution overhead by simulating an x86 system coupled with an ARM Cortex A5 co-processor. The results show that our solution detects intrusions from the state of the art, without any false positives, while remaining acceptable in terms of performance overhead in the context of the SMM (i.e., less than the 150 µs threshold defined by Intel).

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