Implicit Cache Lockdown on ARM: An Accidental Countermeasure to Cache-Timing Attacks

As Moore`s law continues to reduce the cost of computation at an exponential rate, embedded computing capabilities spread to ever-expanding application scenarios, such as smartphones, the Internet of Things, and automation, among many others. This trend has naturally caused the underlying technology to evolve and has introduced increasingly complex microarchitectures into embedded processors in attempts to optimize for performance. While other microarchitectures, like those used in personal computers, have been extensively studied, there has been relatively less research done on embedded microarchitectures. This is especially true in terms of their security, which is growing more important as widespread adoption increases. This thesis explores an undocumented cache behavior found in ARM Cortex processors that we call implicit cache lockdown. While it was presumably implemented for performance reasons, it has a large impact on the recently popular class of cybersecurity attacks that utilize cache-timing side-channels. These attacks leverage the underlying hardware, specifically, the small timing differences between algorithm executions due to CPU caches, to glean sensitive information from a victim process. Since the affected processors are found in an overwhelming majority of smart phones, this sensitive information can include cryptographic secrets, credit card information, and passwords. As the name implies, implicit cache lockdown limits the ability for an attacker to evict certain data from a CPU`s cache. Since this is precisely what known cache-timing attacks rely on, they are rendered ineffective in their current form. This thesis analyzes implicit cache lockdown in great detail, including the methodology we used to discover it, its implications on all existing cache-timing attacks, and how it can be circumvented by an attacker

Overcoming the Intuition Wall: Measurement and Analysis in Computer Architecture

These are exciting times for computer architecture research. Today there is significant demand to improve the performance and energy-efficiency of emerging, transformative applications which are being hammered out by the hundreds for new computing platforms and usage models. This booming growth of applications and the variety of programming languages used to create them is challenging our ability as architects to rapidly and rigorously characterize these applications. Concurrently, hardware has become more complex with the emergence of accelerators, multicore systems, and heterogeneity caused by further divergence between processor market segments. No one architect can now understand all the complexities of many systems and reason about the full impact of changes or new applications. To that end, this dissertation presents four case studies in quantitative methods. Each case study attacks a different application and proposes a new measurement or analytical technique. In each case study we find at least one surprising or unintuitive result which would likely not have been found without the application of our method

Fatal attraction: identifying mobile devices through electromagnetic emissions

Smartphones are increasingly augmented with sensors for a variety of purposes. In this paper, we show how magnetic field emissions can be used to fingerprint smartphones. Previous work on identification rely on specific characteristics that vary with the settings and components available on a device. This limits the number of devices on which one approach is effective. By contrast, all electronic devices emit a magnetic field which is accessible either through the API or measured through an external device. We conducted an in-the-wild study over four months and collected mobile sensor data from 175 devices. In our experiments we observed that the electromagnetic field measured by the magnetometer identifies devices with an accuracy of 98.9%. Furthermore, we show that even if the sensor was removed from the device or access to it was discontinued, identification would still be possible from a secondary device in close proximity to the target. Our findings suggest that the magnetic field emitted by smartphones is unique and fingerprinting devices based on this feature can be performed without the knowledge or cooperation of users

Securing Real-Time Internet-of-Things

Modern embedded and cyber-physical systems are ubiquitous. A large number of critical cyber-physical systems have real-time requirements (e.g., avionics, automobiles, power grids, manufacturing systems, industrial control systems, etc.). Recent developments and new functionality requires real-time embedded devices to be connected to the Internet. This gives rise to the real-time Internet-of-things (RT-IoT) that promises a better user experience through stronger connectivity and efficient use of next-generation embedded devices. However RT- IoT are also increasingly becoming targets for cyber-attacks which is exacerbated by this increased connectivity. This paper gives an introduction to RT-IoT systems, an outlook of current approaches and possible research challenges towards secure RT- IoT frameworks

Side-Channel Monitoring of Contactless Java Cards

Smart cards are small, portable, tamper-resistant computers used in security-sensitive applications ranging from identification and access control to payment systems. Side-channel attacks, which use clues from timing, power consumption, or even electromagnetic (EM) signals, can compromise the security of these devices and have been an active research area since 1996. Newer ``contactless'' cards communicate using radio frequency (RF), without physical contact. These contactless smart cards are sometimes grouped with radio frequency identification (RFID) devices in popular usage of the term. This thesis investigates devices that use the ISO 14443 (proximity card) protocol, a large class of contactless/RFID devices. Although contactless smart cards are increasingly common, very few reproducible practical attacks have been published. Presently, there are no known documented side-channel attacks against contactless Java Cards (open standard multi-application cards) using generic unmodified hardware. This thesis develops a research-friendly platform for investigating side-channel attacks on ISO 14443 contactless smart cards. New techniques for measurement and analysis, as well as the first fully documented EM side-channel monitoring procedure, are presented for a contactless Java Card. These techniques use unmodified, commercial off-the-shelf hardware and are both practical and broadly applicable to a wide range of ISO 14443 devices, including many payment cards and electronic passports

Time Protection: the Missing OS Abstraction

Timing channels enable data leakage that threatens the security of computer systems, from cloud platforms to smartphones and browsers executing untrusted third-party code. Preventing unauthorised information flow is a core duty of the operating system, however, present OSes are unable to prevent timing channels. We argue that OSes must provide time protection in addition to the established memory protection. We examine the requirements of time protection, present a design and its implementation in the seL4 microkernel, and evaluate its efficacy as well as performance overhead on Arm and x86 processors

Understanding and Countermeasures against IoT Physical Side Channel Leakage

With the proliferation of cheap bulk SSD storage and better batteries in the last few years we are experiencing an explosion in the number of Internet of Things (IoT) devices flooding the market, smartphone connected point-of-sale devices (e.g. Square), home monitoring devices (e.g. NEST), fitness monitoring devices (e.g. Fitbit), and smart-watches. With new IoT devices come new security threats that have yet to be adequately evaluated. We propose uLeech, a new embedded trusted platform module for next-generation power scavenging devices. Such power scavenging devices are already widely deployed. For instance, the Square point-of-sale reader uses the microphone/speaker interface of a smartphone for communications and as a power supply. Such devices are being used as trusted devices in security-critical applications, without having been adequately evaluated. uLeech can securely store keys and provide cryptographic services to any connected smartphone. Our design also facilitates physical side-channel security analysis by providing interfaces to facilitate the acquisition of power traces and clock manipulation attacks. Thus uLeech empowers security researchers to analyze leakage in next- generation embedded and IoT devices and to evaluate countermeasures before deployment. Even the most secure systems reveal their secrets through secret-dependent computation. Secret- dependent computation is detectable by monitoring a system’s time, power, or outputs. Common defenses to side-channel emanations include adding noise to the channel or making algorithmic changes to mitigate specific side-channels. Unfortunately, existing solutions are not automatic, not comprehensive, or not practical. We propose an isolation-based approach for eliminating power and timing side-channels that is automatic, comprehensive, and practical. Our approach eliminates side-channels by leveraging integrated decoupling capacitors to electrically isolate trusted computation from the adversary. Software has the ability to request a fixed- power/time quantum of isolated computation. By discretizing power and time, our approach controls the granularity of side-channel leakage; the only burden on programmers is to ensure that all secret-dependent execution differences converge within a power/time quantum. We design and implement three approaches to power/time-based quantization and isolation: a wholly-digital version, a hybrid version that uses capacitors for time tracking, and a full- custom version. We evaluate the overheads of our proposed controllers with respect to software implementations of AES and RSA running on an ARM- based microcontroller and hardware implementations AES and RSA using a 22nm process technology. We also validate the effectiveness and real-world efficiency of our approach by building a prototype consisting of an ARM microcontroller, an FPGA, and discrete circuit components. Lastly, we examine the root cause of Electromagnetic (EM) side-channel attacks on Integrated Circuits (ICs) to augment the Quantized Computing design to mitigate EM leakage. By leveraging the isolation nature of our Quantized Computing design, we can effectively reduce the length and power of the unintended EM antennas created by the wire layers in an IC

XDIVINSA: eXtended DIVersifying INStruction Agent to Mitigate Power Side-Channel Leakage

Side-channel analysis (SCA) attacks pose a major threat to embedded systems due to their ease of accessibility. Realising SCA resilient cryptographic algorithms on embedded systems under tight intrinsic constraints, such as low area cost, limited computational ability, etc., is extremely challenging and often not possible. We propose a seamless and effective approach to realise a generic countermeasure against SCA attacks. XDIVINSA, an extended diversifying instruction agent, is introduced to realise the countermeasure at the microarchitecture level based on the combining concept of diversified instruction set extension (ISE) and hardware diversification. XDIVINSA is developed as a lightweight co-processor that is tightly coupled with a RISC-V processor. The proposed method can be applied to various algorithms without the need for software developers to undertake substantial design efforts hardening their implementations against SCA. XDIVINSA has been implemented on the SASEBO G-III board which hosts a Kintex-7 XC7K160T FPGA device for SCA mitigation evaluation. Experimental results based on non-specific t-statistic tests show that our solution can achieve leakage mitigation on the power side channel of different cryptographic kernels, i.e., Speck, ChaCha20, AES, and RSA with an acceptable performance overhead compared to existing countermeasures.This work has been supported in part by EPSRC via grant EP/R012288/1, under the RISE (http://www.ukrise.org) programme.Peer ReviewedPostprint (author's final draft