How Not To Design An Efficient FHE-Friendly Block Cipher:Seljuk

status: publishe

Chaghri --- an FHE-friendly Block Cipher

The Recent progress in practical applications of secure computation protocols has also attracted attention to the symmetric-key primitives underlying them. Whereas traditional ciphers have evolved to be efficient with respect to certain performance metrics, advanced cryptographic protocols call for a different focus. The so called arithmetic complexity is viewed through the number and layout of non-linear operations in the circuit implemented by the protocol. Symmetric-key algorithms that are optimized with respect to this metric are said to be algebraic ciphers. Previous work targeting ZK and MPC protocols delivered great improvement in the performance of these applications both in lab and in practical use. Interestingly, despite its apparent benefits to privacy-aware cloud computing, algebraic ciphers targeting FHE did not attract similar attention. In this paper we present Chaghri, an FHE-friendly block cipher enabling efficient transciphering in BGV-like schemes. A complete Chaghri circuit can be implemented using only 16 multiplications, 32 Frobenius automorphisms and 32 rotations, all arranged in a depth-32 circuit. Our HElib implemention achieves a throughput of 0.26 seconds-per-bit which is 65% faster than AES in the same setting

3D bioprinting stem-cells with solubilized tendon extracellular matrix (ECM) based hydrogel

3D bioprinting aims to generate biological structures similar to natural counterparts such as tissues or organs in terms of their functions and morphology [1-2]. The major challenge with this technique is the choice of extra cellular matrix (ECM)-like biomaterial as a cell encapsulating agent. The objective of this research is to develop a composite hydrogel that would provide important biological cues to host cells. A new composite hydrogel system based on a mixture of natural ECM and agarose hydrogel is developed. ECM based hydrogel is derived from bovine native tendon by decellularization and enzymatic digestion procedures. Decellularized and solubilized tendon tissues contain important structural and bioactive extracellular matrix components such as collagen, which serves as anchorage sites for host cells

StaTI: Protecting against Fault Attacks Using Stable Threshold Implementations

Fault attacks impose a serious threat against the practical implementations of cryptographic algorithms. Statistical Ineffective Fault Attacks (SIFA), exploiting the dependency between the secret data and the fault propagation overcame many of the known countermeasures. Later, several countermeasures have been proposed to tackle this attack using error detection methods. However, the efficiency of the countermeasures, in part governed by the number of error checks, still remains a challenge. In this work, we propose a fault countermeasure, StaTI, based on threshold implementations and linear encoding techniques. The proposed countermeasure protects the implementations of cryptographic algorithms against both side-channel and fault adversaries in a non-combined attack setting. We present a new composable notion, stability, to protect a threshold implementation against a formal gate/register-faulting adversary. Stability ensures fault propagation, making a single error check of the output suffice. To illustrate the stability notion, first, we provide stable encodings of the XOR and AND gates. Then, we present techniques to encode threshold implementations of S-boxes, and provide stable encodings of some quadratic S-boxes together with their security and performance evaluation. Additionally, we propose general encoding techniques to transform a threshold implementation of any function (e.g., non-injective functions) to a stable one. We then provide an encoding technique to use in symmetric primitives which encodes state elements together significantly reducing the encoded state size. Finally, we used StaTI to implement a secure Keccak on FPGA and report on its efficiency

SoK: Parameterization of Fault Adversary Models - Connecting Theory and Practice

Since the first fault attack by Boneh et al. in 1997, various physical fault injection mechanisms have been explored to induce errors in electronic systems. Subsequent fault analysis methods of these errors have been studied, and successfully used to attack many cryptographic implementations. This poses a significant challenge to the secure implementation of cryptographic algorithms. To address this, numerous countermeasures have been proposed. Nevertheless, these countermeasures are primarily designed to protect against the particular assumptions made by the fault analysis methods. These assumptions, however, encompass only a limited range of the capabilities inherent to physical fault injection mechanisms. In this paper, we narrow our focus to fault attacks and countermeasures specific to ASICs, and introduce a novel parameterized fault adversary model capturing an adversary\u27s control over an ASIC. We systematically map (a) the physical fault injection mechanisms, (b) adversary models assumed in fault analysis, and (c) adversary models used to design countermeasures into our introduced model. This model forms the basis for our comprehensive exploration that covers a broad spectrum of fault attacks and countermeasures within symmetric key cryptography as a comprehensive survey. Furthermore, our investigation highlights a notable misalignment among the adversary models assumed in countermeasures, fault attacks, and the intrinsic capabilities of the physical fault injection mechanisms. Through this study, we emphasize the need to reevaluate existing fault adversary models, and advocate for the development of a unified model

CAPABARA: A Combined Attack on CAPA

Physical attacks pose a substantial threat to the secure implementation of cryptographic algorithms. While considerable research efforts are dedicated to protecting against passive physical attacks (e.g., side-channel analysis (SCA)), the landscape of protection against other types of physical attacks remains a challenge. Fault attacks (FA), though attracting growing attention in research, still lack the prevalence of provably secure designs when compared to SCA. The realm of combined attacks, which leverage the capabilities of both SCA and FA adversaries, introduces powerful adversarial models, rendering protection against them challenging. This challenge has consequently led to a relatively unexplored area of research, resulting in a notable gap in understanding and efficiently protecting against combined attacks. The CAPA countermeasure, published at CRYPTO 2018, addresses this challenge with a robust adversarial model that goes beyond conventional SCA and FA adversarial models. Drawing inspiration from the principles of Multiparty Computation (MPC), CAPA claims security against higher-order SCA, higher-order fault attacks, and their combination. In this work, we present a combined attack that breaks CAPA within the constraints of its assumed adversarial model. In response, we propose potential fixes to the design of CAPA that increase the complexity of the proposed attack, although not provably thwarting it. With this presented combined attack, we highlight the difficulty of effectively protecting against combined attacks

Practical Improvements to Statistical Ineffective Fault Attacks

Statistical Fault Attacks (SFA), introduced by Fuhr et al., exploit the statistical bias resulting from injected faults. Unlike prior fault analysis attacks, which require both faulty and correct ciphertexts under the same key, SFA leverages only faulty ciphertexts. In CHES 2018, more powerful attacks called Statistical Ineffective Fault Attacks (SIFA) have been proposed. In contrast to the previous fault attacks that utilize faulty ciphertexts, SIFA exploits the distribution of the intermediate values leading to fault-free ciphertexts. As a result, the SIFA attacks were shown to be effective even in the presence of widely used fault injection countermeasures based on detection and infection. In this work, we build upon the core idea of SIFA, and provide two main practical improvements over the previously proposed analysis methods. Firstly, we show how to perform SIFA from the input side, which in contrast to the original SIFA, requires injecting faults in the earlier rounds of an encryption or decryption operation. If we consider the start of the operation as the trigger for fault injection, the cumulative jitter in the first few rounds of a cipher is much lower than the last rounds. Hence, performing the attack in the first or second round requires a narrower parameter range for fault injection and hence less fault injection attempts to recover the secret key. Secondly, in comparison to the straightforward SIFA approach of guessing 32-bits at a time, we propose a chosen input approach that reduces the guessing effort to 16-bits at a time. This decreases the key search space for full key recovery of an AES-128 implementation from $2^{34}$ to $2^{19}$

Cryptanalysis of Strong Physically Unclonable Functions

Physically Unclonable Functions (PUFs) are being proposed as a low cost alternative to permanently store secret keys or provide device authentication without requiring non-volatile memory, large e-fuses or other dedicated processing steps. In the literature, PUFs are split into two main categories. The so-called strong PUFs are mainly used for authentication purposes, hence also called authentication PUFs. They promise to be lightweight by avoiding extensive digital post-processing and cryptography. The so-called weak PUFs, also called key generation PUFs, can only provide authentication when combined with a cryptographic authentication protocol. Over the years, multiple research results have demonstrated that Strong PUFs can be modeled and attacked by machine learning techniques. Hence, the general assumption is that the security of a strong PUF is solely dependent on its security against machine learning attacks. The goal of this paper is to debunk this myth, by analyzing and breaking three recently published Strong PUFs (Suresh et al., VLSI Circuits 2020; Liu et al., ISSCC 2021; and Jeloka et al., VLSI Circuits 2017). The attacks presented in this paper have practical complexities and use generic symmetric key cryptanalysis techniques

Cell sheet as a bioink for 3D bioprinting

Cell sheet technology is a growing area in tissue engineering. It enables a sheet of interconnected cells which is enriched with cell-extracellular matrix (ECM) and cell-cell interactions. Poly (N-isopropylacrylamide) (PNIPAm) coating based thermoresponsive culture dishes are used as one of the advanced cell sheet technology methods [1]. It allows the surface to demonstrate temperature responsive wettability changes in aqueous environments. Different methods can be used to fabricate PNIPAm surfaces such as initiated chemical vapor deposition (iCVD) which offers a control of the polymer thickness [2]. In this research, we showed that thermoresponsive surfaces can create cell sheet which can be used as a bioink in 3D direct cell bioprinting [3]. The aim of this work is to show that cell sheets can be used to increase mechanical strength of bioink