scholarly journals Provably Secure Hardware Masking in the Transition- and Glitch-Robust Probing Model: Better Safe than Sorry

2021 ◽  
pp. 136-158
Author(s):  
Gaëtan Cassiers ◽  
François-Xavier Standaert
Keyword(s):  
Sufficient Conditions ◽  
Side Channel ◽  
Side Channel Attacks ◽  
Secure Hardware ◽  
Physical Effects ◽  
Provably Secure

There exists many masking schemes to protect implementations of cryptographic operations against side-channel attacks. It is common practice to analyze the security of these schemes in the probing model, or its variant which takes into account physical effects such as glitches and transitions. Although both effects exist in practice and cause leakage, masking schemes implemented in hardware are often only analyzed for security against glitches. In this work, we fill this gap by proving sufficient conditions for the security of hardware masking schemes against transitions, leading to the design of new masking schemes and a proof of security for an existing masking scheme in presence of transitions. Furthermore, we give similar results in the stronger model where the effects of glitches and transitions are combined.

scholarly journals Information Theoretic Security for Broadcasting of Two Encrypted Sources under Side-Channel Attacks †

Entropy ◽  
2019 ◽  
Vol 21 (8) ◽  
pp. 781
Author(s):  
Bagus Santoso ◽  
Yasutada Oohama
Keyword(s):  
Secure Communication ◽  
Side Information ◽  
Physical Phenomenon ◽  
Sufficient Conditions ◽  
Information Leakage ◽  
Side Channel ◽  
Side Channel Attacks ◽  
Additional Information ◽  
Side Channels ◽  
Secret Keys

In this paper, we propose a theoretical framework to analyze the secure communication problem for broadcasting two encrypted sources in the presence of an adversary which launches side-channel attacks. The adversary is not only allowed to eavesdrop the ciphertexts in the public communication channel, but is also allowed to gather additional information on the secret keys via the side-channels, physical phenomenon leaked by the encryption devices during the encryption process, such as the fluctuations of power consumption, heat, or electromagnetic radiation generated by the encryption devices. Based on our framework, we propose a countermeasure against such adversary by using the post-encryption-compression (PEC) paradigm, in the case of one-time-pad encryption. We implement the PEC paradigm using affine encoders constructed from linear encoders and derive the explicit the sufficient conditions to attain the exponential decay of the information leakage as the block lengths of encrypted sources become large. One interesting feature of the proposed countermeasure is that its performance is independent from the type of side information leaked by the encryption devices.

Countermeasure for Cryptographic Chips to Resist Side-Channel Attacks

2009 ◽  
Vol 19 (11) ◽  
pp. 2990-2998 ◽  
Author(s):  
Tao ZHANG ◽  
Ming-Yu FAN
Keyword(s):  
Side Channel ◽  
Side Channel Attacks

scholarly journals ThermalAttackNet: Are CNNs Making It Easy to Perform Temperature Side-Channel Attack in Mobile Edge Devices?

2021 ◽  
Vol 13 (6) ◽  
pp. 146
Author(s):  
Somdip Dey ◽  
Amit Kumar Singh ◽  
Klaus McDonald-Maier
Keyword(s):  
Information Flow ◽  
Heat Dissipation ◽  
Side Channel ◽  
Side Channel Attack ◽  
Side Channel Attacks ◽  
Information Flow Control ◽  
On Chip ◽  
Temperature Side ◽  
Over Time ◽  
Memory Efficient

Side-channel attacks remain a challenge to information flow control and security in mobile edge devices till this date. One such important security flaw could be exploited through temperature side-channel attacks, where heat dissipation and propagation from the processing cores are observed over time in order to deduce security flaws. In this paper, we study how computer vision-based convolutional neural networks (CNNs) could be used to exploit temperature (thermal) side-channel attack on different Linux governors in mobile edge device utilizing multi-processor system-on-chip (MPSoC). We also designed a power- and memory-efficient CNN model that is capable of performing thermal side-channel attack on the MPSoC and can be used by industry practitioners and academics as a benchmark to design methodologies to secure against such an attack in MPSoC.

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.

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