A synthesis of side-channel attacks on elliptic curve cryptography in smart-cards

2013 ◽  
Vol 3 (4) ◽  
pp. 241-265 ◽  
Author(s):  
Jean-Luc Danger ◽  
Sylvain Guilley ◽  
Philippe Hoogvorst ◽  
Cédric Murdica ◽  
David Naccache
2018 ◽  
Vol 7 (3.27) ◽  
pp. 421
Author(s):  
M Maheswari ◽  
R A. Karthika ◽  
Anuska Chatterjee

Elliptic Curve Cryptography (ECC) is a form of public-key cryptography. This implies that there is the involvement of a private key and a public key for the purpose of cryptography. ECC can be used for a wide range of applications. The keys used are much smaller than the non-ECC cryptographic algorithms. 256 bit and 384 bit ECC are used by NSA for storage of classified intel as ECC is considered to be a part of suit B cryptography by the NSA. When it comes to normal usage, other versions of ECC are used. So, many of the applications protected by ECC are vulnerable to side channel attacks. So, the objective is to modify the existing method of implementation of ECC is some regular domains like media, smart grid, etc., such that the side-channel attacks [7], [3] vulnerabilities are fixed.  


2021 ◽  
Vol 21 (3) ◽  
pp. 1-20
Author(s):  
Mohamad Ali Mehrabi ◽  
Naila Mukhtar ◽  
Alireza Jolfaei

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.


2009 ◽  
Vol 35 (2) ◽  
pp. 329-338 ◽  
Author(s):  
Santosh Ghosh ◽  
Monjur Alam ◽  
Dipanwita Roy Chowdhury ◽  
Indranil Sen Gupta

2000 ◽  
Author(s):  
Adam D. Woodbury ◽  
Daniel V. Bailey ◽  
Christof Paar

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