21 research outputs found
Side-channel based intrusion detection for industrial control systems
Industrial Control Systems are under increased scrutiny. Their security is
historically sub-par, and although measures are being taken by the
manufacturers to remedy this, the large installed base of legacy systems cannot
easily be updated with state-of-the-art security measures. We propose a system
that uses electromagnetic side-channel measurements to detect behavioural
changes of the software running on industrial control systems. To demonstrate
the feasibility of this method, we show it is possible to profile and
distinguish between even small changes in programs on Siemens S7-317 PLCs,
using methods from cryptographic side-channel analysis.Comment: 12 pages, 7 figures. For associated code, see
https://polvanaubel.com/research/em-ics/code
Similar operation template attack on RSA-CRT as a case study
A template attack, the most powerful side-channel attack methods, usually first builds the leakage profiles from a controlled profiling device, and then uses these profiles to recover the secret of the target device. It is based on the fact that the profiling device shares similar leakage characteristics with the target device. In this study, we focus on the similar operations in a single device and propose a new variant of the template attack, called the similar operation template attack (SOTA). SOTA builds the models on public variables (e.g., input/output) and recovers the values of the secret variables that leak similar to the public variables. SOTA’s advantage is that it can avoid the requirement of an additional profiling device. In this study, the proposed SOTA method is applied to a straightforward RSA-CRT implementation. Because the leakage is (almost) the same in similar operations, we reduce the security of RSA-CRT to a hidden multiplier problem (HMP) over GF(q), which can be solved byte-wise using our proposed heuristic algorithm. The effectiveness of our proposed method is verified as an entire prime recovery procedure in a practical leakage scenario
Recommended from our members
Efficient, portable template attacks
Template attacks recover data values processed by tamper-resistant
devices from side-channel waveforms, such as supply-current
fluctuations (power analysis) or electromagnetic emissions. They
first profile a device to generate multivariate statistics of the
waveforms emitted for each of a set of known processed values, which
then identify maximum-likelihood candidates of unknown processed
values during an attack. We identify several practical obstacles
arising in the implementation of template attacks, ranging from
numerical errors to the incompatibility of templates across
different devices, and propose and compare several solutions. We
identify pooled covariance matrices and prior dimensionality
reduction through Fisher's Linear Discriminant Analysis as
particularly efficient and effective, especially where many attack
traces can be acquired. We evaluate alternative algorithms not only
for the task of recovering key bytes from a hardware implementation
of the Advanced Encryption Standard; we even reconstruct the value
transferred by an individual byte-load instruction, with success
rates reaching 85% (or a guessing entropy of less than a quarter
bit remaining) after 1000 attack traces, thereby demonstrating
direct eavesdropping of 8-bit parallel data lines. Using different
devices during the profiling and attack phase can substantially
reduce the effectiveness of template attacks. We demonstrate that
the same problem can also occur across different measurement
campaigns with the same device and that DC offsets (e.g. due to
temperature drift) are a significant cause. We improve the
portability of template parameters across devices by manipulating
the DC content of the eigenvectors that form the projection matrix
used for dimensionality reduction of the waveforms
Profiling DPA: Efficacy and efficiency trade-offs
Linear regression-based methods have been proposed as efficient means of characterising device leakage in the training phases of profiled side-channel attacks. Empirical comparisons between these and the `classical\u27 approach to template building have confirmed the reduction in profiling complexity to achieve the same attack-phase success, but have focused on a narrow range of leakage scenarios which are especially favourable to simple (i.e.\ efficiently estimated) model specifications. In this contribution we evaluate---from a theoretic perspective as much as possible---the performance of linear regression-based templating in a variety of realistic leakage scenarios as the complexity of the model specification varies. We are particularly interested in complexity trade-offs between the number of training samples needed for profiling and the number of attack samples needed for successful DPA: over-simplified models will be cheaper to estimate but DPA using such a degraded model will require more data to recover the key. However, they can still offer substantial improvements over non-profiling strategies relying on the Hamming weight power model, and so represent a meaningful middle-ground between `no\u27 prior information and `full\u27 prior information
Auto-tune POIs: Estimation of distribution algorithms for efficient side-channel analysis
Due to the constant increase and versatility of IoT devices that should keep
sensitive information private, Side-Channel Analysis (SCA) attacks on embedded
devices are gaining visibility in the industrial field. The integration and
validation of countermeasures against SCA can be an expensive and cumbersome
process, especially for the less experienced ones, and current certification
procedures require to attack the devices under test using multiple SCA
techniques and attack vectors, often implying a high degree of complexity. The
goal of this paper is to ease one of the most crucial and tedious steps of
profiling attacks i.e. the points of interest (POI) selection and hence assist
the SCA evaluation process. To this end, we introduce the usage of Estimation
of Distribution Algorithms (EDAs) in the SCA field in order to automatically
tune the point of interest selection. We showcase our approach on several
experimental use cases, including attacks on unprotected and protected AES
implementations over distinct copies of the same device, dismissing in this way
the portability issue
Encasing Block Ciphers to Foil Key Recovery Attempts via Side Channel
Providing efficient protection against energy consumption based side channel attacks (SCAs) for block ciphers is a relevant topic for the research community, as current overheads are in the 100×
range. Unprofiled SCAs exploit information leakage from the outmost rounds of a cipher; we propose a solution encasing it between keyed transformations amenable to an efficient SCA protection. Our solution can be employed as a drop in replacement for an unprotected implementation, or be retrofit to an existing one, while retaining communication capabilities with legacy insecure endpoints. Experiments on a Cortex-M4 μC, show performance improvements
in the range of 60×, compared with available solutions