Review of Algorithmic Techniques for Improving the Performance of Modular Exponentiation

Author(s):  
Satyanarayana Vollala ◽  
N. Ramasubramanian ◽  
Utkarsh Tiwari
Author(s):  
Johannes Mittmann ◽  
Werner Schindler

AbstractMontgomery’s and Barrett’s modular multiplication algorithms are widely used in modular exponentiation algorithms, e.g. to compute RSA or ECC operations. While Montgomery’s multiplication algorithm has been studied extensively in the literature and many side-channel attacks have been detected, to our best knowledge no thorough analysis exists for Barrett’s multiplication algorithm. This article closes this gap. For both Montgomery’s and Barrett’s multiplication algorithm, differences of the execution times are caused by conditional integer subtractions, so-called extra reductions. Barrett’s multiplication algorithm allows even two extra reductions, and this feature increases the mathematical difficulties significantly. We formulate and analyse a two-dimensional Markov process, from which we deduce relevant stochastic properties of Barrett’s multiplication algorithm within modular exponentiation algorithms. This allows to transfer the timing attacks and local timing attacks (where a second side-channel attack exhibits the execution times of the particular modular squarings and multiplications) on Montgomery’s multiplication algorithm to attacks on Barrett’s algorithm. However, there are also differences. Barrett’s multiplication algorithm requires additional attack substeps, and the attack efficiency is much more sensitive to variations of the parameters. We treat timing attacks on RSA with CRT, on RSA without CRT, and on Diffie–Hellman, as well as local timing attacks against these algorithms in the presence of basis blinding. Experiments confirm our theoretical results.


2021 ◽  
pp. 2050011
Author(s):  
DAVID E. ALLEN ◽  
MICHAEL MCALEER

This paper presents a novel analysis of the global spread of the SARS-CoV-2 virus that causes the COVID-19 disease using the R package “nCov2019”, with an emphasis on the global spread and forecasts of the disease, and the rate of transmission in individual countries at two different points in time, namely, March and September 2020. This throws in sharp relief the relative effectiveness of the attempts to risk manage the spread of the virus by “flattening the curve” (aka planking the curve) of the speed of transmission, and the efficacy of lockdowns in terms of the spread of the disease and death rates. Simple cross-sectional regressions are able to predict quite well both the total number of cases and deaths, which cast doubt on the above measures. The algorithmic techniques, results and analysis presented in the paper should prove useful to the medical and health professions, science advisers and risk management and decision making of healthcare by state, regional and national governments in all countries.


2021 ◽  
Vol 8 (2) ◽  
pp. 1-130
Author(s):  
Michael A. Bekos ◽  
Benjamin Niedermann ◽  
Martin Nöllenburg

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