scholarly journals Automatic Generation of HCCA Resistant Scalar Multiplication Algorithm by Proper Sequencing of Field Multiplier Operands

10.29007/qszz ◽  
2018 ◽  
Author(s):  
Poulami Das ◽  
Debapriya Basu Roy ◽  
Debdeep Mukhopadhyay
Keyword(s):  
Correlation Analysis ◽  
Elliptic Curve ◽  
Power Analysis ◽  
Experimental Validation ◽  
Information Leakage ◽  
Automatic Generation ◽  
Side Channel ◽  
Multiplication Algorithm ◽  
Elliptic Curve Cryptosystems ◽  
First Time

Horizontal collision correlation analysis (HCCA) imposes a serious threat tosimple power analysis resistant elliptic curve cryptosystems involving unified algorithms, for e.g. Edward curve unified formula. This attack can be mounted even in presence of differential power analysis resistant randomization schemes. In this paper we have designed an effective countermeasure for HCCA protection, where the dependency of side-channel leakage from a school-book multiplication with the underling multiplier operands is investigated. We have shown how changing the sequence in which the operands are passed to the multiplication algorithm introduces dissimilarity in the information leakage. This disparity has been utilized in constructing a zero-cost countermeasure against HCCA. This countermeasure has been shown to help in HCCA resistivity. Additionally we provide experimental validation for our proposed countermeasure technique on a SASEBO platform. To the best of our knowledge, this is the first time that asymmetry in information leakage has been utilized in designing a side channel countermeasure and successfully applied in an ECC-based crypto-module.

Power Side-Channel Analysis of RNS GLV ECC Using Machine and Deep Learning Algorithms

2021 ◽  
Vol 21 (3) ◽  
pp. 1-20
Author(s):  
Mohamad Ali Mehrabi ◽  
Naila Mukhtar ◽  
Alireza Jolfaei
Keyword(s):  
Deep Learning ◽  
Elliptic Curve ◽  
Smart Cities ◽  
Information Leakage ◽  
Side Channel ◽  
Side Channel Attacks ◽  
Public Key Cryptosystems ◽  
Elliptic Curve Cryptosystems ◽  
Hardware Implementations ◽  
Substantial Progress

Many Internet of Things applications in smart cities use elliptic-curve cryptosystems due to their efficiency compared to other well-known public-key cryptosystems such as RSA. One of the important components of an elliptic-curve-based cryptosystem is the elliptic-curve point multiplication which has been shown to be vulnerable to various types of side-channel attacks. Recently, substantial progress has been made in applying deep learning to side-channel attacks. Conceptually, the idea is to monitor a core while it is running encryption for information leakage of a certain kind, for example, power consumption. The knowledge of the underlying encryption algorithm can be used to train a model to recognise the key used for encryption. The model is then applied to traces gathered from the crypto core in order to recover the encryption key. In this article, we propose an RNS GLV elliptic curve cryptography core which is immune to machine learning and deep learning based side-channel attacks. The experimental analysis confirms the proposed crypto core does not leak any information about the private key and therefore it is suitable for hardware implementations.

scholarly journals Side-Channel Vulnerabilities of Unified Point Addition on Binary Huff Curve and Its Countermeasure

2018 ◽  
Vol 8 (10) ◽  
pp. 2002 ◽  
Author(s):  
Sung Cho ◽  
Sunghyun Jin ◽  
HeeSeok Kim
Keyword(s):  
Correlation Analysis ◽  
Power Consumption ◽  
Elliptic Curve ◽  
Equivalence Class ◽  
Trace Analysis ◽  
Power Analysis ◽  
Side Channel ◽  
Addition Method ◽  
Side Channel Attacks ◽  
Single Power

Unified point addition for computing elliptic curve point addition and doubling is considered to be resistant to simple power analysis. Recently, new side-channel attacks, such as recovery of secret exponent by triangular trace analysis and horizontal collision correlation analysis, have been successfully applied to elliptic curve methods to investigate their resistance to side-channel attacks. These attacks turn out to be very powerful since they only require leakage of a single power consumption trace. In this paper, using these side-channel attack analyses, we introduce two vulnerabilities of unified point addition on the binary Huff curve. Also, we propose a new unified point addition method for the binary Huff curve. Furthermore, to secure against these vulnerabilities, we apply an equivalence class to the side-channel atomic algorithm using the proposed unified point addition method.

scholarly journals Towards Efficient and Automated Side Channel Evaluations at Design Time

10.29007/mbf3 ◽  
2018 ◽  
Author(s):  
Danilo Šijačić ◽  
Josep Balasch ◽  
Bohan Yang ◽  
Santosh Ghosh ◽  
Ingrid Verbauwhede
Keyword(s):  
Experimental Validation ◽  
State Of The Art ◽  
Information Leakage ◽  
Design Flow ◽  
Side Channel ◽  
Cell Design ◽  
Standard Cell ◽  
Side Channel Analysis ◽  
Design Time ◽  
Channel Analysis

Models and tools developed by the semiconductor community have matured over decades of use. As a result, hardware simulations can yield highly accurate and easily automated pre-silicon estimates for e.g. timing and area figures. In this work we design, implement, and evaluate CASCADE, a framework that combines a largely automated full-stack standard-cell design flow with the state of the art techniques for side channel analysis. We show how it can be used to efficiently evaluate side channel leakage prior to chip manufacturing. Moreover, it is independent of the underlying countermeasure and it can be applied starting from the earliest stages of the design flow. Additionally, we provide experimental validation through assessment of the side channel security of representative cryptographic circuits. We discuss aspects related to the performance, scalability, and utility to the designers. In particular, we show that CASCADE can evaluate information leakage with 1 million simulated traces in less than 4 hours using a single desktop workstation, for a design larger than 100kGE.

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