Secure and Efficient RNS Approach for Elliptic Curve Cryptography

Scalar multiplication, the main operation in elliptic curve cryptographic protocols, is vulnerable to side-channel (SCA) and fault injection (FA) attacks. An efficient countermeasure for scalar multiplication can be provided by using alternative number systems like the Residue Number System (RNS). In RNS, a number is represented as a set of smaller numbers, where each one is the result of the modular reduction with a given moduli basis. Under certain requirements, a number can be uniquely transformed from the integers to the RNS domain (and vice versa) and all arithmetic operations can be performed in RNS. This representation provides an inherent SCA and FA resistance to many attacks and can be further enhanced by RNS arithmetic manipulation or more traditional algorithmic countermeasures. In this paper, extending our previous work, we explore the potentials of RNS as an SCA and FA countermeasure and provide an description of RNS based SCA and FA resistance means. We propose a secure and efficient Montgomery Power Ladder based scalar multiplication algorithm on RNS and discuss its SCAFA resistance. The proposed algorithm is implemented on an ARM Cortex A7 processor and its SCA-FA resistance is evaluated by collecting preliminary leakage trace results that validate our initial assumptions

Parallel FPGA Implementation of RSA with Residue Number Systems - Can side-channel threats be avoided? - Extended version

In this paper, we present a new parallel architecture to avoid side-channel analyses such as: timing attack, simple/differential power analysis, fault induction attack and simple/differential electromagnetic analysis. We use a Montgomery Multiplication based on Residue Number Systems. Thanks to RNS, we develop a design able to perform an RSA signature in parallel on a set of identical and independent coprocessors. Of independent interest, we propose a new DPA countermeasure in the framework of RNS. It is only (slightly) memory consuming (1.5 KBytes). Finally, we synthesized our new architecture on FPGA and it presents promising performance results. Even if our aim is to sketch a secure architecture, the RSA signature is performed in less than 160 ms, with competitive hardware resources. To our knowledge, this is the first proposal of an architecture counteracting electromagnetic analysis apart from hardware countermeasures reducing electromagnetic radiations

Fault attacks on RSA and elliptic curve cryptosystems

This thesis answered how a fault attack targeting software used to program EEPROM can threaten hardware devices, for instance IoT devices. The successful fault attacks proposed in this thesis will certainly warn designers of hardware devices of the security risks their devices may face on the programming leve

Machine-Learning assisted Side-Channel Attacks on RNS-based Elliptic Curve Implementations using Hybrid Feature Engineering

Side-channel attacks based on machine learning have recently been introduced to recover the secret information from software and hardware implementations of mathematically secure algorithms. Convolutional Neural Networks (CNNs) have proven to outperform the template attacks due to their ability of handling misalignment in the symmetric algorithms leakage data traces. However, one of the limitations of deep learning algorithms is the requirement of huge datasets for model training. For evaluation scenarios, where limited leakage trace instances are available, simple machine learning with the selection of proper feature engineering, data splitting, and validation techniques, can be more effective. Moreover, limited analysis exists for public-key algorithms, especially on non-traditional implementations like those using Residue Number System (RNS). Template attacks are successful on RNS-based Elliptic Curve Cryptography (ECC), only if the aligned portion is used in templates. In this study, we present a systematic methodology for the evaluation of ECC cryptosystems with and without countermeasures against machine learning side-channel attacks using two attack models. RNS-based ECC datasets have been evaluated using four machine learning classifiers and comparison is provided with existing state-of-the-art template attacks. Moreover, we analyze the impact of raw features and advanced hybrid feature engineering techniques, along with the effect of splitting ratio. We discuss the metrics and procedures that can be used for accurate classification on the imbalance datasets. The experimental results demonstrate that, for ECC RNS datasets, the efficiency of simple machine learning algorithms is better than the complex deep learning techniques when such datasets are not so huge

Security Analysis of Phasor Measurement Units in Smart Grid Communication Infrastructures

Phasor Measurement Units (PMUs), or synchrophasors, are rapidly being deployed in the smart grid with the goal of measuring phasor quantities concurrently from wide area distribution substations. By utilizing GPS receivers, PMUs can take a wide area snapshot of power systems. Thus, the possibility of blackouts in the smart grid, the next generation power grid, will be reduced. As the main enabler of Wide Area Measurement Systems (WAMS), PMUs transmit measured values to Phasor Data Concentrators (PDCs) by the synchrophasor standard IEEE C37.118. IEC 61850 and IEC 62351 are the communication protocols for the substation automation system and the security standard for the communication protocol of IEC 61850, respectively. According to the aforementioned communication and security protocols, as well as the implementation constraints of different platforms, HMAC-SHA1 was suggested by the TC 57 WG group in October 2009. The hash-based Message Authentication Code (MAC) is an algorithm for verifying both message integrity and authentication by using an iterative hash function and a supplied secret key. There are a variety of security attacks on the PMU communications infrastructure. Timing Side Channel Attack (SCA) is one of these possible attacks. In this thesis, timing side channel vulnerability against execution time of the HMAC-SHA1 authentication algorithm is studied. Both linear and negative binomial regression are used to model some security features of the stored key, e.g., its length and Hamming weight. The goal is to reveal secret-related information based on leakage models. The results would mitigate the cryptanalysis process of an attacker. Adviser: Yi Qia

Combining leak--resistant arithmetic for elliptic curves defined over \F_p and RNS representation

In this paper we combine the residue number system (RNS) representation and the leak-resistant arithmetic on elliptic curves. These two techniques are relevant for implementation of elliptic curve cryptography on embedded devices.\\ % since they have leak-resistance properties. It is well known that the RNS multiplication is very efficient whereas the reduction step is costly. Hence, we optimize formulae for basic operations arising in leak-resistant arithmetic on elliptic curves (unified addition, Montgomery ladder) in order to minimize the number of modular reductions. We also improve the complexity of the RNS modular reduction step. As a result, we show how to obtain a competitive secured implementation.\\ Finally, %we recall the main advantages of the RNS representation, %especially in hardware and for embedded devices, and we show that, contrary to other approaches, ours takes optimally the advantage of a dedicated parallel architecture

Highly secure cryptographic computations against side-channel attacks

Side channel attacks (SCAs) have been considered as great threats to modern cryptosystems, including RSA and elliptic curve public key cryptosystems. This is because the main computations involved in these systems, as the Modular Exponentiation (ME) in RSA and scalar multiplication (SM) in elliptic curve system, are potentially vulnerable to SCAs. Montgomery Powering Ladder (MPL) has been shown to be a good choice for ME and SM with counter-measures against certain side-channel attacks. However, recent research shows that MPL is still vulnerable to some advanced attacks [21, 30 and 34]. In this thesis, an improved sequence masking technique is proposed to enhance the MPL\u27s resistance towards Differential Power Analysis (DPA). Based on the new technique, a modified MPL with countermeasure in both data and computation sequence is developed and presented. Two efficient hardware architectures for original MPL algorithm are also presented by using binary and radix-4 representations, respectively

Exploitation of Unintentional Information Leakage from Integrated Circuits

Unintentional electromagnetic emissions are used to recognize or verify the identity of a unique integrated circuit (IC) based on fabrication process-induced variations in a manner analogous to biometric human identification. The effectiveness of the technique is demonstrated through an extensive empirical study, with results presented indicating correct device identification success rates of greater than 99:5%, and average verification equal error rates (EERs) of less than 0:05% for 40 near-identical devices. The proposed approach is suitable for security applications involving commodity commercial ICs, with substantial cost and scalability advantages over existing approaches. A systematic leakage mapping methodology is also proposed to comprehensively assess the information leakage of arbitrary block cipher implementations, and to quantitatively bound an arbitrary implementation\u27s resistance to the general class of differential side channel analysis techniques. The framework is demonstrated using the well-known Hamming Weight and Hamming Distance leakage models, and approach\u27s effectiveness is demonstrated through the empirical assessment of two typical unprotected implementations of the Advanced Encryption Standard. The assessment results are empirically validated against correlation-based differential power and electromagnetic analysis attacks

Geração de números verdadeiramente aleatórios baseados em ruído quântico

Quantum Random Number Generators (QRNGs) promise information-theoretic security by exploring the intrinsic probabilistic properties of quantum mechanics. In practice, their security frequently relies on a number of assumptions over physical devices. In this thesis, a randomness generation framework that explores the amplitude quadrature fluctuations of a vacuum state was analyzed. It employs a homodyne measurement scheme, which can be implemented with low-cost components, and shows potential for high performance with remarkable stability. A mathematical description of all necessary stages was provided as security proof, considering the quantization noise introduced by the analog-to-digital converter. The impact of experimental limitations, such as the digitizer resolution or the presence of excess noise due to an unbalanced detection, was characterized. Moreover, we propose a framework to estimate the excess entropy introduced by an unbalanced detection, and its high impact within the Shannon entropy model was experimentally verified. Furthermore, a real-time dedicated QRNG scheme was implemented and validated. The variance characterization curve of the homodyne detector was measured, and the quantum fluctuations were determined to be preponderant for an impinging power PLO < 45.7mW. By estimating the worst-case min-entropy conditioned on the electronic noise, approximately 8.39 true random bits can be extracted from each sample, yielding a maximum generation rate of 8.23 Gbps. With a lengthcompatible Toeplitz-hashing algorithm, these can be extracted at 75 Mbps with an upper security bound of 2−105, which illustrates the quality of this implementation. Moreover, the generation scheme was validated and verified to pass all the statistical tests of the NIST, DieHarder, and TestU01’s SmallCrush batteries, as well as most of TestU01’s Crush evaluations. Finally, we propose a framework for time-interleaving the entropy source within a classical communication channel, which removes the need for a dedicated generation device. After assessing the conditions where quantum noise is dominant, support for generation rates up to 1.3 Gbps was observed. The random bitstream was subjected to the NIST randomness test suite and consistently passed all evaluations. Moreover, a clean quadrature phase shift keying constellation was recovered, which supports the multi-purpose function of the scheme.Geradores quânticos de números aleatórios (QRNGs) prometem sistemas informação-teoricamente seguros explorando as propriedades intrinsecamente probabilísticas da mecânica quântica. No entanto, experimentalmente, um conjunto de pressupostos é tipicamente imposto sobre os dispositivos experimentais. Nesta dissertação, analisou-se uma abordagem para geração de números aleatórios que explora as flutuações de amplitude em quadratura de um estado vácuo. Para tal, recorre-se a um esquema de deteção homodina que permite um elevado desempenho e estabilidade, requerendo apenas dispositivos de baixo custo. Um modelo matemático das diferentes etapas do gerador foi desenvolvido de forma a fornecer uma prova de segurança, e contabilizou-se o ruído de discretização introduzido pelo conversor analógico-digital. Adicionalmente, caracterizou-se o impacto de imperfeições experimentais como a resolução do conversor analógico-digital e a presença de ruído em excesso como consequência de uma deteção não balanceada. Uma abordagem para estimar esta contribuição no modelo de entropia de Shannon foi também proposta e experimentalmente verificada. Adicionalmente, uma implementação em tempo-real foi caracterizada. A curva de caracterização do detetor homodino foi experimentalmente verificada, e uma preponderância de ruído quântico observado para potências óticas inferiores a 45.7mW. Através de uma estimativa da min-entropy condicionada ao ruído eletrónico, aproximadamente 8.39 bits por medição podem ser extraídos, o que corresponde a uma taxa de geração máxima de 8.23 Gbps. Estes podem ser extraídos a uma taxa de 75 Mbps com um parâmetro de segurança de 2−105, ilustrativo da qualidade desta implementação, através de um algoritmo eficiente de multiplicação de matrizes de Toeplitz. Posteriormente, o esquema foi validado, passando todos os testes estatísticos das baterias NIST, DieHarder, e SmallCrush, assim como a maioria das avaliações contidas na bateria Crush. Por último, foi proposta uma abordagem para integrar esta fonte de entropia num canal de comunicação clássico, removendo desta forma a necessidade de uma implementação dedicada. Após avaliação das condições de preponderância do ruído quântico, foram observadas taxas de geração até 1.3 Gbps. Os números obtidos foram também submetidos à bateria de testes do NIST, passando consistentemente todas as avaliações. Adicionalmente, a constelação de modulação de amplitude em quadratura obtida viabiliza a operação multifuncional do sistema.Mestrado em Engenharia Físic