Mask Compression: High-Order Masking on Memory-Constrained Devices

Masking is a well-studied method for achieving provable security against side-channel attacks. In masking, each sensitive variable is split into $d$ randomized shares, and computations are performed with those shares. In addition to the computational overhead of masked arithmetic, masking also has a storage cost, increasing the requirements for working memory and secret key storage proportionally with $d$. In this work, we introduce mask compression. This conceptually simple technique is based on standard, non-masked symmetric cryptography. Mask compression allows an implementation to dynamically replace individual shares of large arithmetic objects (such as polynomial rings) with $\kappa$-bit cryptographic seeds (or temporary keys) when they are not in computational use. Since $\kappa$ does not need to be larger than the security parameter (e.g., $\kappa=256$ bits) and each polynomial share may be several kilobytes in size, this radically reduces the memory requirement of high-order masking. Overall provable security properties can be maintained by using appropriate gadgets to manage the compressed shares. We describe gadgets with Non-Inteference (NI) and composable Strong-Non Interference (SNI) security arguments. Mask compression can be applied in various settings, including symmetric cryptography, code-based cryptography, and lattice-based cryptography. It is especially useful for cryptographic primitives that allow quasilinear-complexity masking and hence are practically capable of very high masking orders. We illustrate this with a $d=32$ (Order-31) implementation of the recently introduced lattice-based signature scheme Raccoon on an FPGA platform with limited memory resources

A Generic Construction of an Anonymous Reputation System and Instantiations from Lattices

With an anonymous reputation system one can realize the process of rating sellers anonymously in an online shop. While raters can stay anonymous, sellers still have the guarantee that they can be only be reviewed by raters who bought their product.We present the first generic construction of a reputation system from basic building blocks, namely digital signatures, encryption schemes, non-interactive zero-knowledge proofs, and linking indistinguishable tags. We then show the security of the reputation system in a strong security model. Among others, we instantiate the generic construction with building blocks based on lattice problems, leading to the first module lattice-based reputation system

Withdrawable Signature: How to Call off a Signature

Digital signatures are a cornerstone of security and trust in cryptography, providing authenticity, integrity, and non-repudiation. Despite their benefits, traditional digital signature schemes suffer from inherent immutability, offering no provision for a signer to retract a previously issued signature. This paper introduces the concept of a withdrawable signature scheme, which allows for the retraction of a signature without revealing the signer\u27s private key or compromising the security of other signatures the signer created before. This property, defined as ``withdrawability\u27\u27, is particularly relevant in decentralized systems, such as e-voting, blockchain-based smart contracts, and escrow services, where signers may wish to revoke or alter their commitment. The core idea of our construction of a withdrawable signature scheme is to ensure that the parties with a withdrawable signature are not convinced whether the signer signed a specific message. This ability to generate a signature while preventing validity from being verified is a fundamental requirement of our scheme, epitomizing the property of withdrawability. After formally defining security notions for withdrawable signatures, we present two constructions of the scheme based on the pairing and the discrete logarithm. We provide proofs that both constructions are unforgeable under insider corruption and satisfy the criteria of withdrawability. We anticipate our new type of signature will significantly enhance flexibility and security in digital transactions and communications

WrapQ: Side-Channel Secure Key Management for Post-Quantum Cryptography

Transition to PQC brings complex challenges to builders of secure cryptographic hardware. PQC keys usually need to be stored off-module and protected via symmetric encryption and message authentication codes. Only a short, symmetric Key-Encrypting Key (KEK) can be managed on-chip with trusted non-volatile key storage. For secure use, PQC key material is handled in masked format; as randomized shares. Due to the masked encoding of the key material, algorithm-specific techniques are needed to protect the side-channel security of the PQC key import and export processes. In this work, we study key handling techniques used in real-life secure Kyber and Dilithium hardware. We describe WrapQ, a masking-friendly key-wrapping mechanism designed for lattice cryptography. On a high level, WrapQ protects the integrity and confidentiality of key material and allows keys to be stored outside the main security boundary of the module. Significantly, its wrapping and unwrapping processes minimize side-channel leakage from the KEK integrity/authentication keys as well as the masked Kyber or Dilithium key material payload. We demonstrate that masked Kyber or Dilithium private keys can be managed in a leakage-free fashion from a compact WrapQ format without updating its encoding in non-volatile (or read-only) memory. WrapQ has been implemented in a side-channel secure hardware module. Kyber and Dilithium wrapping and unwrapping functions were validated with 100K traces of ISO 17825 / TVLA-type leakage assessment

Towards a Homomorphic Machine Learning Big Data Pipeline for the Financial Services Sector

Machinelearning(ML)istodaycommonlyemployedintheFinancialServicesSector(FSS) to create various models to predict a variety of conditions ranging from financial transactions fraud to outcomes of investments and also targeted marketing campaigns. The common ML technique used for the modeling is supervised learning using regression algorithms and usually involves large amounts of data that needs to be shared and prepared before the actual learning phase. Compliance with privacy laws and confidentiality regulations requires that most, if not all, of the data must be kept in a secure environment, usually in-house, and not outsourced to cloud or multi-tenant shared environments. This paper presents the results of a research collaboration between IBM Research and Banco Bradesco SA to investigate approaches to homomorphically secure a typical ML pipeline commonly employed in the FSS industry. We investigated and de-constructed a typical ML pipeline used by Banco Bradesco and applied Homo- morphic Encryption (HE) to two of the important ML tasks, namely the variable selection phase of the model generation task and the prediction task. Variable selection, which usually precedes the training phase, is very important when working with data sets for which no prior knowledge of the covariate set exists. Our work provides a way to define an initial covariate set for the training phase while preserving the privacy and confidentiality of the input data sets. Quality metrics, using real financial data, comprising quantitative, qualitative and categorical features, demonstrated that our HE based pipeline can yield results comparable to state of the art variable selection techniques and the performance results demonstrated that HE technology has reached the inflection point where it can be useful in batch processing in a financial business setting

Quantum Attacks on Beyond-Birthday-Bound MACs

In this paper, we investigate the security of several recent MAC constructions with provable security beyond the birthday bound (called BBB MACs) in the quantum setting. On the one hand, we give periodic functions corresponding to targeted MACs (including PMACX, PMAC with parity, HPxHP, and HPxNP), and we can recover secret states using Simon algorithm, leading to forgery attacks with complexity $O(n)$. This implies our results realize an exponential speedup compared with the classical algorithm. Note that our attacks can even break some optimally secure MACs, such as mPMAC+-f, mPMAC+-p1, mPMAC+-p2, mLightMAC+-f, etc. On the other hand, we construct new hidden periodic functions based on SUM-ECBC-like MACs: SUM-ECBC, PolyMAC, GCM-SIV2, and 2K-ECBC$_{-}$Plus, where periods reveal the information of the secret key. Then, by applying Grover-meets-Simon algorithm to specially constructed functions, we can recover full keys with $O(2^{n/2}n)$ or $O(2^{m/2}n)$ quantum queries, where $n$ is the message block size and $m$ is the length of the key. Considering the previous best quantum attack, our key-recovery attacks achieve a quadratic speedup

Saber on ESP32

Saber, a CCA-secure lattice-based post-quantum key encapsulation scheme, is one of the second round candidate algorithms in the post-quantum cryptography standardization process of the US National Institute of Standards and Technology (NIST) in 2019. In this work, we provide an efficient implementation of Saber on ESP32, an embedded microcontroller designed for IoT environment with WiFi and Bluetooth support. RSA coprocessor was used to speed up the polynomial multiplications for Kyber variant in a CHES 2019 paper. We propose an improved implementation utilizing the big integer coprocessor for the polynomial multiplications in Saber, which contains significant lower software overhead and takes a better advantage of the big integer coprocessor on ESP32. By using the fast implementation of polynomial multiplications, our single-core version implementation of Saber takes 1639K, 2123K, 2193K clock cycles on ESP32 for key generation, encapsulation and decapsulation respectively. Benefiting from the dual core feature on ESP32, we speed up the implementation of Saber by rearranging the computing steps and assigning proper tasks to two cores executing in parallel. Our dual-core version implementation takes 1176K, 1625K, 1514K clock cycles for key generation, encapsulation and decapsulation respectively

Zero-Value Filtering for Accelerating Non-Profiled Side-Channel Attack on Incomplete NTT based Implementations of Lattice-based Cryptography

Lattice-based cryptographic schemes such as Crystals-Kyber and Dilithium are post-quantum algorithms selected to be standardized by NIST as they are considered to be secure against quantum computing attacks. The multiplication in polynomial rings is the most time-consuming operation in many lattice-based cryptographic schemes, which is also subject to side-channel attacks. While NTT-based polynomial multiplication is almost a norm in a wide range of implementations, a relatively new method, incomplete-NTT is preferred to accelerate lattice-based cryptography, especially on some computing platforms that feature special instructions. In this paper, we present a novel, efficient and non-profiled power/EM side-channel attack targeting polynomial multiplication based on the incomplete NTT algorithm. We apply the attack on the Crystals-Dilithium signature algorithm and demonstrate that the method accelerates attack run-time when compared to conventional correlation power attacks (CPA). While a conventional CPA tests much larger hypothesis set due to the fact that it needs to predict two coefficients of secret polynomials together, we propose a much faster zero-value filtering attack (ZV-FA), which reduces the size of the hypothesis set by targeting the coefficients individually. We also propose an effective and efficient validation and correction technique to estimate and modify the mis-predicted coefficients. Our experimental results show that we can achieve a speed-up of 128.1× over conventional CPA using a total of 13K traces