1,899 research outputs found
TrustShadow: Secure Execution of Unmodified Applications with ARM TrustZone
The rapid evolution of Internet-of-Things (IoT) technologies has led to an
emerging need to make it smarter. A variety of applications now run
simultaneously on an ARM-based processor. For example, devices on the edge of
the Internet are provided with higher horsepower to be entrusted with storing,
processing and analyzing data collected from IoT devices. This significantly
improves efficiency and reduces the amount of data that needs to be transported
to the cloud for data processing, analysis and storage. However, commodity OSes
are prone to compromise. Once they are exploited, attackers can access the data
on these devices. Since the data stored and processed on the devices can be
sensitive, left untackled, this is particularly disconcerting.
In this paper, we propose a new system, TrustShadow that shields legacy
applications from untrusted OSes. TrustShadow takes advantage of ARM TrustZone
technology and partitions resources into the secure and normal worlds. In the
secure world, TrustShadow constructs a trusted execution environment for
security-critical applications. This trusted environment is maintained by a
lightweight runtime system that coordinates the communication between
applications and the ordinary OS running in the normal world. The runtime
system does not provide system services itself. Rather, it forwards requests
for system services to the ordinary OS, and verifies the correctness of the
responses. To demonstrate the efficiency of this design, we prototyped
TrustShadow on a real chip board with ARM TrustZone support, and evaluated its
performance using both microbenchmarks and real-world applications. We showed
TrustShadow introduces only negligible overhead to real-world applications.Comment: MobiSys 201
Device-Based Isolation for Securing Cryptographic Keys
In this work, we describe an eective device-based isolation
approach for achieving data security. Device-based isolation
leverages the proliferation of personal computing devices to
provide strong run-time guarantees for the condentiality of
secrets. To demonstrate our isolation approach, we show its
use in protecting the secrecy of highly sensitive data that
is crucial to security operations, such as cryptographic keys
used for decrypting ciphertext or signing digital signatures.
Private key is usually encrypted when not used, however,
when being used, the plaintext key is loaded into the memory
of the host for access. In our threat model, the host may
be compromised by attackers, and thus the condentiality of
the host memory cannot be preserved. We present a novel
and practical solution and its prototype called DataGuard to
protect the secrecy of the highly sensitive data through the
storage isolation and secure tunneling enabled by a mobile
handheld device. DataGuard can be deployed for the key
protection of individuals or organizations
CamFlow: Managed Data-sharing for Cloud Services
A model of cloud services is emerging whereby a few trusted providers manage
the underlying hardware and communications whereas many companies build on this
infrastructure to offer higher level, cloud-hosted PaaS services and/or SaaS
applications. From the start, strong isolation between cloud tenants was seen
to be of paramount importance, provided first by virtual machines (VM) and
later by containers, which share the operating system (OS) kernel. Increasingly
it is the case that applications also require facilities to effect isolation
and protection of data managed by those applications. They also require
flexible data sharing with other applications, often across the traditional
cloud-isolation boundaries; for example, when government provides many related
services for its citizens on a common platform. Similar considerations apply to
the end-users of applications. But in particular, the incorporation of cloud
services within `Internet of Things' architectures is driving the requirements
for both protection and cross-application data sharing.
These concerns relate to the management of data. Traditional access control
is application and principal/role specific, applied at policy enforcement
points, after which there is no subsequent control over where data flows; a
crucial issue once data has left its owner's control by cloud-hosted
applications and within cloud-services. Information Flow Control (IFC), in
addition, offers system-wide, end-to-end, flow control based on the properties
of the data. We discuss the potential of cloud-deployed IFC for enforcing
owners' dataflow policy with regard to protection and sharing, as well as
safeguarding against malicious or buggy software. In addition, the audit log
associated with IFC provides transparency, giving configurable system-wide
visibility over data flows. [...]Comment: 14 pages, 8 figure
Autoscopy Jr.: Intrusion Detection for Embedded Control Systems
Securing embedded control systems within the power grid presents a unique challenge: on top of the resource restrictions inherent to these devices, SCADA systems must also accommodate strict timing requirements that are non-negotiable, and their massive scale greatly amplifies costs such as power consumption. These constraints make the conventional approach to host intrusion detection--namely, employing virtualization in some manner--too costly or impractical for embedded control systems within critical infrastructure. Instead, we take an in-kernel approach to system protection, building upon the Autoscopy system developed by Ashwin Ramaswamy that places probes on indirectly-called functions and uses them to monitor its host system for behavior characteristic of control-flow-altering malware, such as rootkits. In this thesis, we attempt to show that such a method would indeed be a viable method of protecting embedded control systems. We first identify several issues with the original prototype, and present a new version of the program (dubbed Autoscopy Jr.) that uses trusted location lists to verify that control is coming from a known, trusted location inside our kernel. Although we encountered additional performance overhead when testing our new design, we developed a kernel profiler that allowed us to identify the probes responsible for this overhead and discard them, leaving us with a final probe list that generated less than 5% overhead on every one of our benchmark tests. Finally, we attempted to run Autoscopy Jr. on two specialized kernels (one with an optimized probing framework, and another with a hardening patch installed), finding that the former did not produce enough performance benefits to preclude using our profiler, and that the latter required a different method of scanning for indirect functions for Autoscopy Jr. to operate. We argue that Autoscopy Jr. is indeed a feasible intrusion detection system for embedded control systems, as it can adapt easily to a variety of system architectures and allows us to intelligently balance security and performance on these critical devices
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