8 research outputs found
Lightweight Protocols and Applications for Memory-Based Intrinsic Physically Unclonable Functions on Commercial Off-The-Shelve Devices
We are currently living in the era in which through the ever-increasing dissemination of inter-connected embedded devices, the Internet-of-Things manifests. Although such end-point devices are commonly labeled as ``smart gadgets'' and hence they suggest to implement some sort of intelligence, from a cyber-security point of view, more then often the opposite holds. The market force in the branch of commercial embedded devices leads to minimizing production costs and time-to-market. This widespread trend has a direct, disastrous impact on the security properties of such devices. The majority of currently used devices or those that will be produced in the future do not implement any or insufficient security mechanisms. Foremost the lack of secure hardware components often mitigates the application of secure protocols and applications.
This work is dedicated to a fundamental solution statement, which allows to retroactively secure commercial off-the-shelf devices, which otherwise are exposed to various attacks due to the lack of secure hardware components. In particular, we leverage the concept of Physically Unclonable Functions (PUFs), to create hardware-based security anchors in standard hardware components. For this purpose, we exploit manufacturing variations in Static Random-Access Memory (SRAM) and Dynamic Random-Access Memory modules to extract intrinsic memory-based PUF instances and building on that, to develop secure and lightweight protocols and applications.
For this purpose, we empirically evaluate selected and representative device types towards their PUF characteristics. In a further step, we use those device types, which qualify due to the existence of desired PUF instances for subsequent development of security applications and protocols. Subsequently, we present various software-based security solutions which are specially tailored towards to the characteristic properties of embedded devices. More precisely, the proposed solutions comprise a secure boot architecture as well as an approach to protect the integrity of the firmware by binding it to the underlying hardware. Furthermore, we present a lightweight authentication protocol which leverages a novel DRAM-based PUF type. Finally, we propose a protocol, which allows to securely verify the software state of remote embedded devices
Towards trustworthy computing on untrustworthy hardware
Historically, hardware was thought to be inherently secure and trusted due to its
obscurity and the isolated nature of its design and manufacturing. In the last two
decades, however, hardware trust and security have emerged as pressing issues.
Modern day hardware is surrounded by threats manifested mainly in undesired
modifications by untrusted parties in its supply chain, unauthorized and pirated
selling, injected faults, and system and microarchitectural level attacks. These threats,
if realized, are expected to push hardware to abnormal and unexpected behaviour
causing real-life damage and significantly undermining our trust in the electronic and
computing systems we use in our daily lives and in safety critical applications. A
large number of detective and preventive countermeasures have been proposed in
literature. It is a fact, however, that our knowledge of potential consequences to
real-life threats to hardware trust is lacking given the limited number of real-life
reports and the plethora of ways in which hardware trust could be undermined. With
this in mind, run-time monitoring of hardware combined with active mitigation of
attacks, referred to as trustworthy computing on untrustworthy hardware, is proposed
as the last line of defence. This last line of defence allows us to face the issue of live
hardware mistrust rather than turning a blind eye to it or being helpless once it occurs.
This thesis proposes three different frameworks towards trustworthy computing
on untrustworthy hardware. The presented frameworks are adaptable to different
applications, independent of the design of the monitored elements, based on
autonomous security elements, and are computationally lightweight. The first
framework is concerned with explicit violations and breaches of trust at run-time,
with an untrustworthy on-chip communication interconnect presented as a potential
offender. The framework is based on the guiding principles of component guarding,
data tagging, and event verification. The second framework targets hardware elements
with inherently variable and unpredictable operational latency and proposes a
machine-learning based characterization of these latencies to infer undesired latency
extensions or denial of service attacks. The framework is implemented on a DDR3
DRAM after showing its vulnerability to obscured latency extension attacks. The
third framework studies the possibility of the deployment of untrustworthy hardware
elements in the analog front end, and the consequent integrity issues that might arise
at the analog-digital boundary of system on chips. The framework uses machine
learning methods and the unique temporal and arithmetic features of signals at this
boundary to monitor their integrity and assess their trust level