Prefetchers speculatively fetch memory using predictions on future memory use by applications. Different CPUs may use different prefetcher types, and two implementations of the same prefetcher can differ in details of their characteristics, leading to distinct runtime behavior. For a few implementations, security researchers showed through manual analysis how to exploit specific prefetchers to leak data. Identifying such vulnerabilities required tedious reverse-engineering, as prefetcher implementations are proprietary and undocumented. So far, no systematic study of prefetchers in common CPUs is available, preventing further security assessment.

The complexity of modern processor architectures has given rise to sophisticated interactions among their components. Such interactions may result in potential attack vectors in terms of side channels, possibly available to userland exploits to leak secret data. Exploitation and countering of such side channels requires a detailed understanding of the target component. However, such detailed information is commonly unpublished for many CPUs.

Real-time autonomous systems are becoming pervasive in many application domains such as vehicular ad-hoc networks, smart factories and delivery drones. The correct functioning of these real-time systems is timing-critical with hard deadlines. However, although they interact with other systems and exchange inputs/outputs with the physical world, they usually lack security mechanisms, which makes them susceptible to a wide range of attacks with critical consequences. Typically, this is because security mechanisms usually violate the real-time requirements of these systems and cannot be adjusted at runtime to provide the adequate security without compromising performance. In this paper, we propose a consolidated runtime-configurable hardware-assisted security extension called CHASE that supports different levels of security at runtime. Depending on the desired security level and the system real-time, availability or functionality requirements, CHASE can be configured accordingly at runtime, thus enabling the calibration of the security vs. performance trade-off. We analyze CHASE's effectiveness in providing different security guarantees against various adversarial capabilities, and show how this is achieved with reasonable logic overhead and minimal performance overhead.

Networks of and embedded (IoT) devices are becoming increasingly popular, particularly, in settings such as smart homes, factories and vehicles. These networks can include numerous (potentially diverse) devices that collectively perform certain tasks. In order to guarantee overall safety and privacy, especially in the face of remote exploits, software integrity of each device must be continuously assured. This can be achieved by Remote Attestation (RA) - a security service for reporting current software state of a remote and untrusted device. While RA of a single device is well understood, collective RA of large numbers of networked embedded devices poses new research challenges. In particular, unlike single-device RA, collective RA has not benefited from any systematic treatment. Thus, unsurprisingly, prior collective RA schemes are designed in an ad hoc fashion. Our work takes the first step toward systematic design of collective RA, in order to help place collective RA onto a solid ground and serve as a set of design guidelines for both researchers and practitioners. We explore the design space for collective RA and show how the notions of security and effectiveness can be formally defined according to a given application domain. We then present and evaluate a concrete collective RA scheme systematically designed to satisfy these goals.

The Internet-of-Things (IoT) is a large and complex domain. These systems are often constructed using a very diverse set of hardware, software and protocols. This, combined with the ever increasing number of IoT solutions/services that are rushed to market means that most such systems are rife with security holes. Recent incidents (e.g., the Mirai botnet) further highlight such security issues. With emerging technologies such as blockchain and software-defined networks (SDNs), new security solutions are possible in the IoT domain. In this paper we will explore future trends in IoT security: (a) the use of blockchains in IoT security, (b) data provenance for sensor information, (c) reliable and secure transport mechanisms using SDNs (d) scalable authentication and remote attestation mechanisms for IoT devices and (e) threat modeling and risk/maturity assessment frameworks for the domain.

Unlike traditional processors, embedded Internet of Things (IoT) devices lack resources to incorporate protection against modern sophisticated attacks resulting in critical consequences. Remote attestation (RA) is a security service to establish trust in the integrity of a remote device. While conventional RA is static and limited to detecting malicious modification to software binaries at load-time, recent research has made progress towards runtime attestation, such as attesting the control flow of an executing program. However, existing control-flow attestation schemes are inefficient and vulnerable to sophisticated data-oriented programming (DOP) attacks subvert these schemes and keep the control flow of the code intact. In this paper, we present LiteHAX, an efficient hardware-assisted remote attestation scheme for RISC-based embedded devices that enables detecting both control-flow attacks as well as DOP attacks. LiteHAX continuously tracks both the control-flow and data-flow events of a program executing on a remote device and reports them to a trusted verifying party. We implemented and evaluated LiteHAX on a RISC-V System-on-Chip (SoC) and show that it has minimal performance and area overhead.

Embedded devices, personal gadgets and networks thereof are becoming increasingly pervasive, mainly due the advent of, and hype surrounding, the so-called Internet of Things (IoT). Such devices often perform critical actuation tasks, as well as collect, store and process sensitive data. Therefore, as confirmed by recent examples (such as the Mirai botnet), they also represent very attractive attack targets. To mitigate attacks, remote attestation (RA) has emerged as a distinct security service that aims at detecting malware presence on an embedded device. Most prior RA schemes focus on attesting a single devices and do not scale. In recent years, schemes for collective (group or swarm) RA have been designed. However, none is applicable to autonomous and dynamic network settings. This paper presents US-AID - the first collective attestation schemes for large autonomous dynamic networks of embedded devices. AID verifies overall network integrity by combining continuous in-network attestation with a key exchange mechanism and Proofs-of-non-Absence. Using device absence detection US-AID defends against physical attacks that require disconnecting attacked devices form the network for a non-negligible time. We demonstrate feasibility of US-AID with proof-of-concept implementation on state-of-the-art security architectures for low-end embedded devices and on an autonomous testbed formed of six drones. We also assess its scalability and practicality via extensive simulations.

Embedded devices are increasingly permeating our environment to collect data and act on the insight derived. Examples of such devices include smart environments and autonomous systems. The increasing ability to connect, communicate with, and remotely control such devices via the legacy internet has raised considerable security and privacy concerns. One key mechanism to protect the software integrity of these devices is attestation. In this dissertation, we devise attestation schemes that are scalable and applicable for large networks of embedded devices. In particular, we present attestation schemes that are capable of detecting remote malware infestation, physical, and run-time attacks in different settings including smart environments and autonomous systems.

Remote attestation is an important security service that allows a trusted party (verifier) to verify the integrity of a software running on a remote and potentially compromised device (prover). The security of existing remote attestation schemes relies on the assumption that attacks are software-only and that the prover's code cannot be modified at runtime. However, in practice, these schemes can be bypassed in a stronger and more realistic adversary model that is hereby capable of controlling and modifying code memory to attest benign code but execute malicious code instead - leaving the underlying system vulnerable to Time of Check Time of Use (TOCTOU) attacks. In this work, we first demonstrate TOCTOU attacks on recently proposed attestation schemes by exploiting physical access to prover's memory. Then we present the design and proof-of-concept implementation of ATRIUM, a runtime remote attestation system that securely attests both the code's binary and its execution behavior under memory attacks. ATRIUM provides resilience against both software- and hardware-based TOCTOU attacks, while incurring minimal area and performance overhead.

Remote attestation is a security service that is typically realized by an interactive challenge-response protocol that allows a trusted verifier to capture the state of a potentially untrusted remote device. However, existing attestation schemes are vulnerable to Denial of Service (DoS) attacks, which can be carried out by swamping the targeted device with fake attestation requests.

Large numbers of smart connected devices, also named as the Internet of Things (IoT), are permeating our environments (homes, factories, cars, and also our body - with wearable devices) to collect data and act on the insight derived. Ensuring software integrity (including OS, apps, and configurations) on such smart devices is then essential to guarantee both privacy and safety. A key mechanism to protect the software integrity of these devices is remote attestation: A process that allows a remote verifier to validate the integrity of the software of a device. This process usually makes use of a signed hash value of the actual device's software, generated by dedicated hardware. While individual device attestation is a well-established technique, to date integrity verification of a very large number of devices remains an open problem, due to scalability issues. In this paper, we present SANA, the first secure and scalable protocol for efficient attestation of large sets of devices that works under realistic assumptions. SANA relies on a novel signature scheme to allow anyone to publicly verify a collective attestation in constant time and space, for virtually an unlimited number of devices. We substantially improve existing swarm attestation schemes by supporting a realistic trust model where: (1) only the targeted devices are required to implement attestation; (2) compromising any device does not harm others; and (3) all aggregators can be untrusted. We implemented SANA and demonstrated its efficiency on tiny sensor devices. Furthermore, we simulated SANA at large scale, to assess its scalability. Our results show that SANA can provide efficient attestation of networks of 1,000,000 devices, in only 2.5 seconds.

Large numbers of smart devices are permeating our environment to collect data and act on the insight derived. Examples of such devices include smart homes, factories, cars, or wearables. For privacy, security, and safety, ensuring correctness of the configuration of these devices is essential. One key mechanism to protect the software integrity of these devices is attestation.

As embedded devices (under the guise of "smart-whatever") rapidly proliferate into many domains, they become attractive targets for malware. Protecting them from software and physical attacks becomes both important and challenging. Remote attestation is a basic tool for mitigating such attacks. It allows a trusted party (verifier) to remotely assess software integrity of a remote, untrusted, and possibly compromised, embedded device (prover).

Today, large numbers of smart interconnected devices provide safety and security critical services for energy grids, industrial control systems, gas and oil search robots, home/office automation, transportation, and critical infrastructure. These devices often operate in swarms -- large, dynamic, and self-organizing networks. Software integrity verification of device swarms is necessary to ensure their correct and safe operation as well as to protect them against attacks. However, current device attestation schemes assume a single prover device and do not scale to swarms. We present SEDA, the first attestation scheme for device swarms. We introduce a formal security model for swarm attestation and show security of our approach in this model. We demonstrate two proof-of-concept implementations based on two recent (remote) attestation architectures for embedded systems, including an Intel research platform. We assess performance of SEDA based on these implementations and simulations of large swarms. SEDA can efficiently attest swarms with dynamic and static topologies common in automotive, avionic, industrial control and critical infrastructures settings.