Generalised Mersenne Numbers Revisited

Generalised Mersenne Numbers (GMNs) were defined by Solinas in 1999 and feature in the NIST (FIPS 186-2) and SECG standards for use in elliptic curve cryptography. Their form is such that modular reduction is extremely efficient, thus making them an attractive choice for modular multiplication implementation. However, the issue of residue multiplication efficiency seems to have been overlooked. Asymptotically, using a cyclic rather than a linear convolution, residue multiplication modulo a Mersenne number is twice as fast as integer multiplication; this property does not hold for prime GMNs, unless they are of Mersenne's form. In this work we exploit an alternative generalisation of Mersenne numbers for which an analogue of the above property --- and hence the same efficiency ratio --- holds, even at bitlengths for which schoolbook multiplication is optimal, while also maintaining very efficient reduction. Moreover, our proposed primes are abundant at any bitlength, whereas GMNs are extremely rare. Our multiplication and reduction algorithms can also be easily parallelised, making our arithmetic particularly suitable for hardware implementation. Furthermore, the field representation we propose also naturally protects against side-channel attacks, including timing attacks, simple power analysis and differential power analysis, which is essential in many cryptographic scenarios, in constrast to GMNs.Comment: 32 pages. Accepted to Mathematics of Computatio

Null models and complexity science: disentangling signal from noise in complex interacting systems

The constantly increasing availability of fine-grained data has led to a very detailed description of many socio-economic systems (such as financial markets, interbank loans or supply chains), whose representation, however, quickly becomes too complex to allow for any meaningful intuition or insight about their functioning mechanisms. This, in turn, leads to the challenge of disentangling statistically meaningful information from noise without assuming any a priori knowledge on the particular system under study. The aim of this thesis is to develop and test on real world data unsupervised techniques to extract relevant information from large complex interacting systems. The question I try to answer is the following: is it possible to disentangle statistically relevant information from noise without assuming any prior knowledge about the system under study? In particular, I tackle this challenge from the viewpoint of hypothesis testing by developing techniques based on so-called null models, i.e., partially randomised representations of the system under study. Given that complex systems can be analysed both from the perspective of their time evolution and of their time-aggregated properties, I have tested and developed one technique for each of these two purposes. The first technique I have developed is aimed at extracting “backbones” of relevant relationships in complex interacting systems represented as static weighted networks of pairwise interactions and it is inspired by the well-known Pólya urn combinatorial process. The second technique I have developed is instead aimed at identifying statistically relevant events and temporal patterns in single or multiple time series by means of maximum entropy null models based on Ensemble Theory. Both of these methodologies try to exploit the heterogeneity of complex systems data in order to design null models that are tailored to the systems under study, and therefore capable of identifying signals that are genuinely distinctive of the systems themselves

Same Value Analysis on Edwards Curves

Recently, several research groups in cryptography have presented new elliptic curve model based on Edwards curves. These new curves were selected for their good performance and security perspectives. Cryptosystems based on elliptic curves in embedded devices can be vulnerable to Side-Channel Attacks (SCA), such as the Simple Power Analysis (SPA) or the Differential Power Analysis (DPA). In this paper, we analyze the existence of special points whose use in SCA is known as Same Value Analysis (SVA), for Edwards curves. These special points show up as internal collisions under power analysis. Our results indicate that no Edwards curve is safe from such an attacks

Closing the Gap in RFC 7748: Implementing Curve448 in Hardware

With the evidence on comprised cryptographic standards in the context of elliptic curves, the IETF TLS working group has issued a request to the IETF Crypto Forum Research Group (CFRG) to recommend new elliptic curves that do not leave a doubt regarding their rigidity or any backdoors. This initiative has recently published RFC 7748 proposing two elliptic curves, known as Curve25519 and Curve448, for use with the next generation of TLS. This choice of elliptic curves was already picked up by the IETF working group curdle for adoption in further security protocols, such as DNSSEC. Hence it can be expected that these two curves will become predominant in the Internet and will form one basis for future secure communication. Unfortunately, both curves were solely designed and optimized for pure software implementation; their implementation in hardware or their physical protection against side-channel attacks were not considered at any time. However, for Curve25519 it has been shown recently that efficient implementations in hardware along with side-channel protection are possible. In this work we aim to close this gap and demonstrate that fortunately the second curve can be efficiently implemented in hardware as well. More precisely, we demonstrate that the high-security Curve448 can be implemented on a Xilinx XC7Z7020 at moderate costs of just 963 logic and 30 DSP slices and performs a scalar multiplication in 2.5ms

FourQ on Embedded Devices with Strong Countermeasures Against Side-Channel Attacks

This work deals with the energy-efficient, high-speed and high-security implementation of elliptic curve scalar multiplication, elliptic curve Diffie-Hellman (ECDH) key exchange and elliptic curve digital signatures on embedded devices using FourQ and incorporating strong countermeasures to thwart a wide variety of side-channel attacks. First, we set new speed records for constant-time curve-based scalar multiplication, DH key exchange and digital signatures at the 128-bit security level with implementations targeting 8, 16 and 32-bit microcontrollers. For example, our software computes a static ECDH shared secret in 6.9 million cycles (or 0.86 seconds @8MHz) on a low-power 8-bit AVR microcontroller which, compared to the fastest Curve25519 and genus-2 Kummer implementations on the same platform, offers 2x and 1.4x speedups, respectively. Similarly, it computes the same operation in 496 thousand cycles on a 32-bit ARM Cortex-M4 microcontroller, achieving a factor-2.9 speedup when compared to the fastest Curve25519 implementation targeting the same platform. A similar speed performance is observed in the case of digital signatures. Second, we engineer a set of side-channel countermeasures taking advantage of FourQ\u27s rich arithmetic and propose a secure implementation that offers protection against a wide range of sophisticated side-channel attacks, including differential power analysis (DPA). Despite the use of strong countermeasures, the experimental results show that our FourQ software is still efficient enough to outperform implementations of Curve25519 that only protect against timing attacks. Finally, we perform a differential power analysis evaluation of our software running on an ARM Cortex-M4, and report that no leakage was detected with up to 10 million traces. These results demonstrate the potential of deploying FourQ on low-power applications such as protocols for the Internet of Things

Boolean Exponent Splitting

A typical countermeasure against side-channel attacks consists of masking intermediate values with a random number. In symmetric cryptographic algorithms, Boolean shares of the secret are typically used, whereas in asymmetric algorithms the secret exponent/scalar is typically masked using algebraic properties. This paper presents a new exponent splitting technique with minimal impact on performance based on Boolean shares. More precisely, it is shown how an exponent can be efficiently split into two shares, where the exponent is the XOR sum of the two shares, typically requiring only an extra register and a few register copies per bit. Our novel exponentiation and scalar multiplication algorithms can be randomized for every execution and combined with other blinding techniques. In this way, both the exponent and the intermediate values can be protected against various types of side-channel attacks. We perform a security evaluation of our algorithms using the mutual information framework and provide proofs that they are secure against first-order side-channel attacks. The side-channel resistance of the proposed algorithms is also practically verified with test vector leakage assessment performed on Xilinx\u27s Zynq zc702 evaluation board

On Sustainable Ring-based Anonymous Systems

Anonymous systems (e.g. anonymous cryptocurrencies and updatable anonymous credentials) often follow a construction template where an account can only perform a single anonymous action, which in turn potentially spawns new (and still single-use) accounts (e.g. UTXO with a balance to spend or session with a score to claim). Due to the anonymous nature of the action, no party can be sure which account has taken part in an action and, therefore, must maintain an ever-growing list of potentially unused accounts to ensure that the system keeps running correctly. Consequently, anonymous systems constructed based on this common template are seemingly not sustainable. In this work, we study the sustainability of ring-based anonymous systems, where a user performing an anonymous action is hidden within a set of decoy users, traditionally called a ``ring\u27\u27. On the positive side, we propose a general technique for ring-based anonymous systems to achieve sustainability. Along the way, we define a general model of decentralised anonymous systems (DAS) for arbitrary anonymous actions, and provide a generic construction which provably achieves sustainability. As a special case, we obtain the first construction of anonymous cryptocurrencies achieving sustainability without compromising availability. We also demonstrate the generality of our model by constructing sustainable decentralised anonymous social networks. On the negative side, we show empirically that Monero, one of the most popular anonymous cryptocurrencies, is unlikely to be sustainable without altering its current ring sampling strategy. The main subroutine is a sub-quadratic-time algorithm for detecting used accounts in a ring-based anonymous system

Survey for Performance & Security Problems of Passive Side-channel Attacks Countermeasures in ECC

The main objective of the Internet of Things is to interconnect everything around us to obtain information which was unavailable to us before, thus enabling us to make better decisions. This interconnection of things involves security issues for any Internet of Things key technology. Here we focus on elliptic curve cryptography (ECC) for embedded devices, which offers a high degree of security, compared to other encryption mechanisms. However, ECC also has security issues, such as Side-Channel Attacks (SCA), which are a growing threat in the implementation of cryptographic devices. This paper analyze the state-of-the-art of several proposals of algorithmic countermeasures to prevent passive SCA on ECC defined over prime fields. This work evaluates the trade-offs between security and the performance of side-channel attack countermeasures for scalar multiplication algorithms without pre-computation, i.e. for variable base point. Although a number of results are required to study the state-of-the-art of side-channel attack in elliptic curve cryptosystems, the interest of this work is to present explicit solutions that may be used for the future implementation of security mechanisms suitable for embedded devices applied to Internet of Things. In addition security problems for the countermeasures are also analyzed

Profiling side-channel attacks on cryptographic algorithms

Traditionally, attacks on cryptographic algorithms looked for mathematical weaknesses in the underlying structure of a cipher. Side-channel attacks, however, look to extract secret key information based on the leakage from the device on which the cipher is implemented, be it smart-card, microprocessor, dedicated hardware or personal computer. Attacks based on the power consumption, electromagnetic emanations and execution time have all been practically demonstrated on a range of devices to reveal partial secret-key information from which the full key can be reconstructed. The focus of this thesis is power analysis, more specifically a class of attacks known as profiling attacks. These attacks assume a potential attacker has access to, or can control, an identical device to that which is under attack, which allows him to profile the power consumption of operations or data flow during encryption. This assumes a stronger adversary than traditional non-profiling attacks such as differential or correlation power analysis, however the ability to model a device allows templates to be used post-profiling to extract key information from many different target devices using the power consumption of very few encryptions. This allows an adversary to overcome protocols intended to prevent secret key recovery by restricting the number of available traces. In this thesis a detailed investigation of template attacks is conducted, along with how the selection of various attack parameters practically affect the efficiency of the secret key recovery, as well as examining the underlying assumption of profiling attacks in that the power consumption of one device can be used to extract secret keys from another. Trace only attacks, where the corresponding plaintext or ciphertext data is unavailable, are then investigated against both symmetric and asymmetric algorithms with the goal of key recovery from a single trace. This allows an adversary to bypass many of the currently proposed countermeasures, particularly in the asymmetric domain. An investigation into machine-learning methods for side-channel analysis as an alternative to template or stochastic methods is also conducted, with support vector machines, logistic regression and neural networks investigated from a side-channel viewpoint. Both binary and multi-class classification attack scenarios are examined in order to explore the relative strengths of each algorithm. Finally these machine-learning based alternatives are empirically compared with template attacks, with their respective merits examined with regards to attack efficiency