5,012 research outputs found
Secure and Efficient RNS Approach for Elliptic Curve Cryptography
Scalar multiplication, the main operation in elliptic
curve cryptographic protocols, is vulnerable to side-channel
(SCA) and fault injection (FA) attacks. An efficient countermeasure
for scalar multiplication can be provided by using alternative
number systems like the Residue Number System (RNS). In RNS,
a number is represented as a set of smaller numbers, where each
one is the result of the modular reduction with a given moduli
basis. Under certain requirements, a number can be uniquely
transformed from the integers to the RNS domain (and vice
versa) and all arithmetic operations can be performed in RNS.
This representation provides an inherent SCA and FA resistance
to many attacks and can be further enhanced by RNS arithmetic
manipulation or more traditional algorithmic countermeasures.
In this paper, extending our previous work, we explore the
potentials of RNS as an SCA and FA countermeasure and provide
an description of RNS based SCA and FA resistance means. We
propose a secure and efficient Montgomery Power Ladder based
scalar multiplication algorithm on RNS and discuss its SCAFA
resistance. The proposed algorithm is implemented on an
ARM Cortex A7 processor and its SCA-FA resistance is evaluated
by collecting preliminary leakage trace results that validate our
initial assumptions
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
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