International Association for Cryptologic Research

International Association
for Cryptologic Research


Shivam Bhasin

Affiliation: PACE Labs, TL@NTU


Attacking and Defending Masked Polynomial Comparison for Lattice-Based Cryptography
In this work we are concerned with the hardening of post-quantum key encapsulation mechanisms (KEM) against side-channel attacks, with a focus on the comparison operation required for the Fujisaki-Okamoto (FO) transform. We identify critical vulnerabilities in two proposals for masked comparison and successfully attack the masked comparison algorithms from TCHES 2018 and TCHES 2020 using first-orde side-channel attacks and show that their advertised security properties do not hold. Additionally, we break the higher-order secured masked comparison from TCHES 2020 using a collision attack which does not require side-channel information. To enable implementers to spot such flaws in the implementation or underlying algorithms, we propose a framework that is designed to test the re-encryption step of the FO transform for information leakage. Our framework relies on a specifically parametrized t-test and would have identified the previously mentioned flaws in the masked comparison. Our framework can be used to test both the comparison itself and the full decapsulation implementation.
Persistent Fault Attack in Practice 📺
Persistence fault analysis (PFA) is a novel fault analysis technique proposed in CHES 2018 and demonstrated with rowhammer-based fault injections. However, whether such analysis can be applied to traditional fault attack scenario, together with its difficulty in practice, has not been carefully investigated. For the first time, a persistent fault attack is conducted on an unprotected AES implemented on ATmega163L microcontroller in this paper. Several critical challenges are solved with our new improvements, including (1) how to decide whether the fault is injected in SBox; (2) how to use the maximum likelihood estimation to pursue the minimum number of ciphertexts; (3) how to utilize the unknown fault in SBox to extract the key. Our experiments show that: to break AES with physical laser injections despite all these challenges, the minimum and average number of required ciphertexts are 926 and 1641, respectively. It is about 38% and 28% reductions of the ciphertexts required in comparison to 1493 and 2273 in previous work where both fault value and location have to be known. Furthermore, our analysis is extended to the PRESENT cipher. By applying the persistent fault analysis to the penultimate round, the full PRESENT key of 80 bits can be recovered. Eventually, an experimental validation is performed to confirm the accuracy of our attack with more insights. This paper solves the challenges in most aspects of practice and also demonstrates the feasibility and universality of PFA on SPN block ciphers.
Generic Side-channel attacks on CCA-secure lattice-based PKE and KEMs 📺
In this work, we demonstrate generic and practical EM side-channel assisted chosen ciphertext attacks over multiple LWE/LWR-based Public Key Encryption (PKE) and Key Encapsulation Mechanisms (KEM) secure in the chosen ciphertext model (IND-CCA security). We show that the EM side-channel information can be efficiently utilized to instantiate a plaintext checking oracle, which provides binary information about the output of decryption, typically concealed within IND-CCA secure PKE/KEMs, thereby enabling our attacks. Firstly, we identified EM-based side-channel vulnerabilities in the error correcting codes (ECC) enabling us to distinguish based on the value/validity of decrypted codewords. We also identified similar vulnerabilities in the Fujisaki-Okamoto transform which leaks information about decrypted messages applicable to schemes that do not use ECC. We subsequently exploit these vulnerabilities to demonstrate practical attacks applicable to six CCA-secure lattice-based PKE/KEMs competing in the second round of the NIST standardization process. We perform experimental validation of our attacks on implementations taken from the open-source pqm4 library, running on the ARM Cortex-M4 microcontroller. Our attacks lead to complete key-recovery in a matter of minutes on all the targeted schemes, thus showing the effectiveness of our attack.
DAPA: Differential Analysis aided Power Attack on (Non-) Linear Feedback Shift Registers
Differential power analysis (DPA) is a form of side-channel analysis (SCA) that performs statistical analysis on the power traces of cryptographic computations. DPA is applicable to many cryptographic primitives, including block ciphers, stream ciphers and even hash-based message authentication code (HMAC). At COSADE 2017, Dobraunig et al. presented a DPA on the fresh re-keying scheme Keymill to extract the bit relations of neighbouring bits in its shift registers, reducing the internal state guessing space from 128 to 4 bits. In this work, we generalise their methodology and combine with differential analysis, we called it differential analysis aided power attack (DAPA), to uncover more bit relations and take into account the linear or non-linear functions that feedback to the shift registers (i.e. LFSRs or NLFSRs). Next, we apply our DAPA on LR-Keymill, the improved version of Keymill designed to resist the aforementioned DPA, and breaks its 67.9-bit security claim with a 4-bit internal state guessing. We experimentally verified our analysis. In addition, we improve the previous DPA on Keymill by halving the amount of data resources needed for the attack. We also applied our DAPA to Trivium, a hardware-oriented stream cipher from the eSTREAM portfolio and reduces the key guessing space from 80 to 14 bits.
The Curse of Class Imbalance and Conflicting Metrics with Machine Learning for Side-channel Evaluations 📺
We concentrate on machine learning techniques used for profiled sidechannel analysis in the presence of imbalanced data. Such scenarios are realistic and often occurring, for instance in the Hamming weight or Hamming distance leakage models. In order to deal with the imbalanced data, we use various balancing techniques and we show that most of them help in mounting successful attacks when the data is highly imbalanced. Especially, the results with the SMOTE technique are encouraging, since we observe some scenarios where it reduces the number of necessary measurements more than 8 times. Next, we provide extensive results on comparison of machine learning and side-channel metrics, where we show that machine learning metrics (and especially accuracy as the most often used one) can be extremely deceptive. This finding opens a need to revisit the previous works and their results in order to properly assess the performance of machine learning in side-channel analysis.
Make Some Noise. Unleashing the Power of Convolutional Neural Networks for Profiled Side-channel Analysis 📺
Profiled side-channel analysis based on deep learning, and more precisely Convolutional Neural Networks, is a paradigm showing significant potential. The results, although scarce for now, suggest that such techniques are even able to break cryptographic implementations protected with countermeasures. In this paper, we start by proposing a new Convolutional Neural Network instance able to reach high performance for a number of considered datasets. We compare our neural network with the one designed for a particular dataset with masking countermeasure and we show that both are good designs but also that neither can be considered as a superior to the other one.Next, we address how the addition of artificial noise to the input signal can be actually beneficial to the performance of the neural network. Such noise addition is equivalent to the regularization term in the objective function. By using this technique, we are able to reduce the number of measurements needed to reveal the secret key by orders of magnitude for both neural networks. Our new convolutional neural network instance with added noise is able to break the implementation protected with the random delay countermeasure by using only 3 traces in the attack phase. To further strengthen our experimental results, we investigate the performance with a varying number of training samples, noise levels, and epochs. Our findings show that adding noise is beneficial throughout all training set sizes and epochs.
SITM: See-In-The-Middle Side-Channel Assisted Middle Round Differential Cryptanalysis on SPN Block Ciphers 📺
Side-channel analysis constitutes a powerful attack vector against cryptographic implementations. Techniques such as power and electromagnetic side-channel analysis have been extensively studied to provide an efficient way to recover the secret key used in cryptographic algorithms. To protect against such attacks, countermeasure designers have developed protection methods, such as masking and hiding, to make the attacks harder. However, due to significant overheads, these protections are sometimes deployed only at the beginning and the end of encryption, which are the main targets for side-channel attacks.In this paper, we present a methodology for side-channel assisted differential cryptanalysis attack to target middle rounds of block cipher implementations. Such method presents a powerful attack vector against designs that normally only protect the beginning and end rounds of ciphers. We generalize the attack to SPN based ciphers and calculate the effort the attacker needs to recover the secret key. We provide experimental results on 8-bit and 32-bit microcontrollers. We provide case studies on state-of-the-art symmetric block ciphers, such as AES, SKINNY, and PRESENT. Furthermore, we show how to attack shuffling-protected implementations.
Persistent Fault Analysis on Block Ciphers
Persistence is an intrinsic nature for many errors yet has not been caught enough attractions for years. In this paper, the feature of persistence is applied to fault attacks, and the persistent fault attack is proposed. Different from traditional fault attacks, adversaries can prepare the fault injection stage before the encryption stage, which relaxes the constraint of the tight-coupled time synchronization. The persistent fault analysis (PFA) is elaborated on different implementations of AES-128, specially fault hardened implementations based on Dual Modular Redundancy (DMR). Our experimental results show that PFA is quite simple and efficient in breaking these typical implementations. To show the feasibility and practicability of our attack, a case study is illustrated on the shared library Libgcrypt with rowhammer technique. Approximately 8200 ciphertexts are enough to extract the master key of AES-128 when PFA is applied to Libgcrypt1.6.3 with redundant encryption based DMR. This work puts forward a new direction of fault attacks and can be extended to attack other implementations under more interesting scenarios.
Practical Evaluation of FSE 2016 Customized Encoding Countermeasure
Shivam Bhasin Dirmanto Jap Thomas Peyrin
To protect against side-channel attacks, many countermeasures have been proposed. A novel customized encoding countermeasure was published in FSE 2016. Customized encoding exploits knowledge of the profiled leakage of the device to construct an optimal encoding and minimize the overall side-channel leakage. This technique was originally applied on a basic table look-up. In this paper, we implement a full block cipher with customized encoding countermeasure and investigate its security under simulated and practical setting for a general purpose microcontroller. Under simulated setting, we can verify that customized encoding shows strong security properties under proper assumption of leakage estimation and noise variance. However, in practical setting, our general observation is that the side-channel leakage will mostly be present even if the encoding scheme is applied, highlighting some limitation of the approach. The results are supported by experiments on 8-bit AVR and 32-bit ARM microcontroller.