6,623 research outputs found
DR.SGX: Hardening SGX Enclaves against Cache Attacks with Data Location Randomization
Recent research has demonstrated that Intel's SGX is vulnerable to various
software-based side-channel attacks. In particular, attacks that monitor CPU
caches shared between the victim enclave and untrusted software enable accurate
leakage of secret enclave data. Known defenses assume developer assistance,
require hardware changes, impose high overhead, or prevent only some of the
known attacks. In this paper we propose data location randomization as a novel
defensive approach to address the threat of side-channel attacks. Our main goal
is to break the link between the cache observations by the privileged adversary
and the actual data accesses by the victim. We design and implement a
compiler-based tool called DR.SGX that instruments enclave code such that data
locations are permuted at the granularity of cache lines. We realize the
permutation with the CPU's cryptographic hardware-acceleration units providing
secure randomization. To prevent correlation of repeated memory accesses we
continuously re-randomize all enclave data during execution. Our solution
effectively protects many (but not all) enclaves from cache attacks and
provides a complementary enclave hardening technique that is especially useful
against unpredictable information leakage
On Making Emerging Trusted Execution Environments Accessible to Developers
New types of Trusted Execution Environment (TEE) architectures like TrustLite
and Intel Software Guard Extensions (SGX) are emerging. They bring new features
that can lead to innovative security and privacy solutions. But each new TEE
environment comes with its own set of interfaces and programming paradigms,
thus raising the barrier for entry for developers who want to make use of these
TEEs. In this paper, we motivate the need for realizing standard TEE interfaces
on such emerging TEE architectures and show that this exercise is not
straightforward. We report on our on-going work in mapping GlobalPlatform
standard interfaces to TrustLite and SGX.Comment: Author's version of article to appear in 8th Internation Conference
of Trust & Trustworthy Computing, TRUST 2015, Heraklion, Crete, Greece,
August 24-26, 201
Design and implementation of robust embedded processor for cryptographic applications
Practical implementations of cryptographic algorithms are vulnerable to side-channel analysis and fault attacks. Thus, some masking and fault detection algorithms must be incorporated into these implementations. These additions further increase the complexity of the cryptographic devices which already need to perform computationally-intensive operations. Therefore, the general-purpose processors are usually supported by coprocessors/hardware accelerators to protect as well as to accelerate cryptographic applications. Using a configurable processor is just another solution. This work designs and implements robust execution units as an extension to a configurable processor, which detect the data faults (adversarial or otherwise) while performing the arithmetic operations. Assuming a capable adversary who can injects faults to the cryptographic computation with high precision, a nonlinear error detection code with high error detection capability is used. The designed units are tightly integrated to the datapath of the configurable processor using its tool chain. For different configurations, we report the increase in the space and time complexities of the configurable processor. Also, we present performance evaluations of the software implementations using the robust execution units. Implementation results show that it is feasible to implement robust arithmetic units with relatively low overhead in an embedded processor
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