Ruhr-Universität Bochum (RUB): Open Journal Systems
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Neurophenomenal structuralism and the role of computational context
No full textNeurophenomenal structuralism posits that conscious experiences are defined relationally and that their phenomenal structures are mirrored by neural structures. While this approach offers a promising framework for identifying neural correlates of the contents of consciousness, we argue that merely establishing structural correspondences between neural and phenomenal structures is insufficient. This paper emphasizes the critical role of computational context – the network of neural processes within which a given neural activation pattern is used – in determining content. We introduce four criteria to evaluate if neural structures are viable candidates for neural correlates of contents of consciousness within this framework. These criteria highlight that, for neural structures to mirror phenomenal structures meaningfully, they must be actively exploited by the brain’s downstream processes and influence behavior in a structure-preserving way. Our analysis demonstrates that purely anatomical and overly exhaustive causal structures fail to meet specific criteria, whereas activation structures can succeed, provided they are embedded within the appropriate computational context. Our findings challenge local structuralist theories, which overlook the content-constituting role of computational context. We conclude that incorporating computational context is essential for any structuralist account of consciousness
REED: Chiplet-based Accelerator for Fully Homomorphic Encryption
Full text linkFully Homomorphic Encryption (FHE) enables privacy-preserving computation and has many applications. However, its practical implementation faces massive computation and memory overheads. To address this bottleneck, several Application-Specific Integrated Circuit (ASIC) FHE accelerators have been proposed. All these prior works put every component needed for FHE onto one chip (monolithic), hence offering high performance. However, they encounter common challenges associated with large-scale chip design, such as inflexibility, low yield, and high manufacturing costs. In this paper, we present the first-of-its-kind multi-chiplet-based FHE accelerator ‘REED’ for overcoming the limitations of prior monolithic designs. To utilize the advantages of multi-chiplet structures while matching the performance of larger monolithic systems, we propose and implement several novel strategies in the context of FHE. These include a scalable chiplet design approach, an effective framework for workload distribution, a custom inter-chiplet communication strategy, and advanced pipelined Number Theoretic Transform and automorphism design to enhance performance.Our instruction-set and power simulations experiments with a prelayout netlist indicate that REED 2.5D microprocessor consumes 96.7mm2 chip area, 49.4Waverage power in 7nm technology. It could achieve a remarkable speedup of up to 2,991x compared to a CPU (24-core 2xIntel X5690) and offer 1.9x better performance, along with a 50% reduction in development costs when compared to state-of-the-art ASIC FHE accelerators. Furthermore, our work presents the first instance of benchmarking an encrypted deep neural network (DNN) training. Overall, the REED architecture design offers a highly effective solution for accelerating FHE, thereby significantly advancing the practicality and deployability of FHE in real-world applications
On the Characterization of Phase Noise for the Robust and Resilient PLL-TRNG Design
Full text linkA true random number generator (TRNG) is a critical component in ensuring the security of cryptographic systems. Among TRNG implementations, the phase-locked loop-based TRNG (PLL-TRNG) is a widely adopted solution for FPGA platforms due to the availability of a stochastic model. In the previous study, this stochastic model was based on analog noise signals, which potentially led to an oversimplification of the PLL physical process and resulted in an overestimation of entropy. To address this limitation, we extract key platform-specific parameters of the PLL and develop a new stochastic model tailored for multi-output PLL-TRNGs. For the first time, we reveal the effect of the PLL’s bandwidth on the correlation of sampling points and introduce a method for quantitatively controlling sampling point correlations. Finally, we validate the model through on-chip jitter measurements. Experimental results show that the proposed stochastic model accurately describes the behavior of the PLL-TRNG and provides the most conservative entropy lower bound, with a 1.8-fold improvement in jitter resolution
SoK: FHE-Friendly Symmetric Ciphers and Transciphering
Full text linkFully Homomorphic Encryption (FHE) enables computation on encrypted data without decryption, demonstrating significant potential for privacy-preserving applications. However, FHE faces several challenges, one of which is the significant plaintext-to-ciphertext expansion ratio, resulting in high communication overhead between client and server. The transciphering technique can effectively address this problem by first encrypting data with a space-efficient symmetric cipher, then converting symmetric ciphertext to FHE ciphertext without decryption.Numerous FHE-friendly symmetric ciphers and transciphering methods have been developed by researchers, each with unique advantages and limitations. These often require extensive knowledge of both symmetric cryptography and FHE to fully grasp, making comparison and selection among these schemes challenging. To address this, we conduct a comprehensive survey of over 20 FHE-friendly symmetric ciphers and transciphering methods, evaluating them based on criteria such as security level, efficiency, and compatibility. We have designed and executed experiments to benchmark the performance of the feasible combinations of symmetric ciphers and transciphering methods across various application scenarios. Our findings offer insights into achieving efficient transciphering tailored to different task contexts. Additionally, we make our example code available open-source, leveraging state-of-the-art FHE implementations
Promoting reading fluency: How should the quality of learning provision in literacy courses be assessed? : Results of an observational study
Full text linkAbstract: In diesem Beitrag werden Teilergebnisse der Studie „Erwerb von Leseflüssigkeit gering literalisierter Erwachsener (LegelitE)“ vorgestellt. Im Fokus dieses Beitrags stehen die Lernangebote in Alphabetisierungskursen zur Leseflüssigkeitsförderung sowie die Einschätzung ihres Potenzials aus lesedidaktischer Perspektive. Datengrundlage sind teilnehmende Beobachtungen und Audiographien von Sitzungen in 21 Kursen sowie die Einschätzung der Lesefähigkeiten von 57 Teilnehmenden. Die Daten wurden inhaltsanalytisch ausgewertet. Durch die Ergebnisse wird eine Spannung zwischen lesedidaktischen Anforderungen und den Angeboten in der Kurspraxis deutlich: Die Praxis des lauten, wiederholenden und begleiteten Lesens, die Textauswahl für Lautlesephasen sowie die Rückmeldungen der Kursleiter:innen zum Lesen erscheinen verbesserungsfähig. Implikationen für die Fort- und Weiterbildung von Kursleitenden werden abgeleitet.Abstract: This article presents partial results of the study "Acquisition of reading fluency by low-literate adults [Erwerb von Leseflüssigkeit gering literalisierter Erwachsener (LegelitE)]". The focus of this article is on the learning opportunities in literacy courses to promote reading fluency as well as the assessment of their potential from the perspective of reading didactics. The data is based on participant observations and audiographies of sessions in 21 courses, as well as diagnostics to assess the reading skills of 57 participants. The data was evaluated by means of qualitative content analysis. The results reveal a tension between reading didactic requirements and what is offered in course practice: the practice of reading aloud, repetitive and accompanied reading, the selection of texts for reading aloud phases, and the feedback from course instructors on reading appear to require improvement. Implications for further training of course instructors are derived
Poster: LockedApart: Faster GPU Fingerprinting Through the Compute API
Full text linkWebGL offers website direct access to the GPU, allowing beautiful graphics. The direct hardware access offered by WebGL was also shown to expose multiple security vulnerabilities. In particular, DrawnApart showed that by performing graphical micro-benchmarks on the GPU, it is possible to fingerprint the underlying hardware. Recently, the access of websites to the GPU was extended with the introduction of the WebGPU API, a new low-level API that allows websites to perform general-purpose computations on the GPU. Our research question was: Does this additional access to the GPU expose additional avenues for fingerprinting? Our initial results show that this is true. Our new attack, which we call LockedApart, uses WebGPU to directly measure contention between GPU threads. Compared to DrawnApart, LockedApart is up to 310x faster and up to 1.8x more accurate. These preliminary results show that it is important to consider the security implications of this new API. The code for LockedApart is available at https://github.com/LockedApart/LockedApar
PortPrint: Identifying Inaccessible Code with Port Contention
Full text linkIn many real-world scenarios, being able to infer specific software versions or variations of cryptographic libraries is critical to mounting targeted exploits. For this, traditional version-detection approaches often rely on direct inspection of programs. However, modern computing platforms frequently employ protection for code, e.g., using execute-only memory (XOM) or trusted execution environments (TEE) to safeguard sensitive code from disclosure and reverse engineering. This paper demonstrates how side-channel measurements via CPU port contention reveal distinctive execution signatures, even when code is inaccessible for inspection. Our proof-of-concept implementation PortPrint identifies cryptographic functions, reveals library versions, and even uncovers whether a WolfSSL build is vulnerable to CVE-2024-1544 or if Spectre mitigations are active in Xen. We verify that PortPrint works despite state-of-the-art code protection mechanisms, such as memory protection keys, hypervisor-based XOM, Intel SGX, Intel TDX, and AMD SEV. We also report a negative result for leaking code protected with these techniques using Meltdown and Foreshadow, providing valuable insights into the limitations of these attacks. Our results show that hardware-based isolation is insufficient to conceal instruction streams
Mix-Basis Geometric Approach to Boomerang Distinguishers
No full textDifferential cryptanalysis relies on assumptions like Markov ciphers and hypothesis of stochastic equivalence. The probability of a differential characteristic estimated by classical methods is the key-averaged probability under the two assumptions. However, the real probability can vary significantly between keys. Hence, tools for differential cryptanalysis in the fixed-key model are desirable. Recently, Beyne and Rijmen applied the geometric approach to differential cryptanalysis and proposed a systematic framework called quasi-differential (CRYPTO 2022).As a variant of differential cryptanalysis, boomerang attacks rely on similar assumptions, so it is important to study their probability in the fixed-key model as well. A direct extension of the quasi-differential for boomerang attacks leads to the quasi-3- differential framework (IEEE-IT 2024). However, such a straightforward approach is difficult in practical applications as there are too many quasi-3-differential trails.We tackle this problem by applying the mix-basis style geometric approach (CRYPTO 2025) to the boomerang attacks and construct the quasi-boomerang framework. By choosing a suitable pair of bases, the boomerang probability can be computed by summing correlations of quasi-boomerang characteristics. The transition matrix of the key-XOR operation is also a diagonal matrix; thus, the influence of keys can be analyzed in a similar way to the quasi-differential framework.We apply the quasi-boomerang framework to SKINNY-64 and GIFT-64. For SKINNY- 64, we check and confirm 4 boomerang distinguishers with high probability (2 with probability 1 and 2 with probability 2−4) generated from Hadipour, Bagheri, and Song’s tool (ToSC 2021/1), through the analysis of key dependencies and the probability calculation from quasi-boomerang characteristics. We also propose a divide-and-conquer approach following the sandwich framework for boomerangs with small probability or long rounds to apply the quasi-boomerang framework. After checking 2/1 boomerang distinguisher(s) of SKINNY-64/GIFT-64, we find that the previously considered invalid 19-round distinguisher of GIFT-64 is valid.In addition, as a contribution of independent interest, we revisit Boura, Derbez, and Germon’s work by extending the quasi-differential framework to the related-key scenario (ToSC 2025/1), and show an alternative way to derive the same formulas in their paper by regarding the key-XOR as a normal cipher component
MDS Diffusion Layers for Arithmetization-Oriented Symmetric Ciphers: The Rotational-Add Construction
No full textWe introduce the rotational-add diffusion layers aimed for applications in the design of arithmetization-oriented (AO) symmetric ciphers, such as fully homomorphic encryption (FHE)-friendly symmetric ciphers. This generalizes the rotational-XOR diffusion layers which have been utilized in the design of many important conventional symmetric ciphers like SHA-256, SM4, ZUC and Ascon. A rotational-add diffusion layer is defined over the finite field Fp for arbitrary prime p, enabling implementations using only rotations and modular additions/subtractions. The advantage of using such diffusion layers in AO ciphers is that, the costs of scalar multiplications can be reduced since the appearing scalars include only ±1, thus the total costs depend on sizes of the rotation offsets. In this paper, we investigate characterizations and constructions of lightest rotational-add diffusion layers over (Fmp)n that are maximum distance separable (MDS) with a focus on the case n = 4. It turns out that the minimum achievable size of the rotation offsets is 5 subject to the MDS property constraint. We specify a large class of rotational-add diffusion layers with 5 rotations and traverse all possible patterns of appearance of the scalars ±1. In four cases we can derive computationally tractable necessary and sufficient conditions for the rotational-add diffusion layers to attain the MDS property. These conditions enable explicit characterization of suitable primes p for given parameters. Leveraging these results, we construct three distinct families of rotational-add MDS diffusion layers applicable to AO ciphers. Although a rotational-add diffusion layer with 7 rotations and only additions has already been used in the design of the FHEfriendly block cipher YuX recently, to our knowledge, our work presents the first systematic theoretical characterization of rotational-add MDS diffusion layers and provides explicit constructions of them
A New Trick for Polynomial Multiplication: A verified CRT polymul utilizing a monomial factor
No full textIn this paper we present a novel transformation strategy for polynomial multiplications and apply it to NTRU Prime, specifically the parameter sets sntrup761 and ntrulpr761 working in the ring Z4591[x]/⟨x761−x−1⟩. To evaluate the practicality of our idea, we implemented the algorithm in C++ with ARM Neon intrinsics. By further exploiting the various optimization opportunities in the transformation process, we achieve state-of-the-art performance on Cortex-A72.Because of the aggressively lazy modular reduction strategy, overflows are of serious concern. Such errors in an optimized implementation are notoriously difficult to detect using traditional test vectors. To this end, the compiled binary file is formally verified using the tool CryptoLine. We use all the features in the current version of CryptoLine. This includes the Integer Set Library for range checking, plus the Logical Equivalence Checking to verify the correctness of the binary produced with the most optimized compiler setting by showing it as being equivalent to a binary from a less optimized compilation