Aug 24, 2025·Proceedings of the 31st ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2, 2026
Thomas Gassmann, Stefanos Chaliasos, Thodoris Sotiropoulos, Zhendong Su
Zero-knowledge proofs (ZKPs) are the cornerstone of programmable cryptography. They enable (1) privacy-preserving and verifiable computation across blockchains, and (2) an expanding range of off-chain applications such as credential schemes. Zero-knowledge virtual machines (zkVMs) lower the barrier by turning ZKPs into a drop-in backend for standard compilation pipelines. This lets developers write proof-generating programs in conventional languages (e.g., Rust or C++) instead of hand-crafting arithmetic circuits. However, these VMs inherit compiler infrastructures tuned for traditional architectures rather than for proof systems. In particular, standard compiler optimizations assume features that are absent in zkVMs, including cache locality, branch prediction, or instruction-level parallelism. Therefore, their impact on proof generation is questionable. We present the first systematic study of the impact of compiler optimizations on zkVMs. We evaluate 64 LLVM passes, six standard optimization levels, and an unoptimized baseline across 58 benchmarks on two RISC-V-based zkVMs (RISC Zero and SP1). While standard LLVM optimization levels do improve zkVM performance (over 40\%), their impact is far smaller than on traditional CPUs, since their decisions rely on hardware features rather than proof constraints. Guided by a fine-grained pass-level analysis, we~\emph{slightly} refine a small set of LLVM passes to be zkVM-aware, improving zkVM execution time by up to 45\% (average +4.6\% on RISC Zero, +1\% on SP1) and achieving consistent proving-time gains. Our work highlights the potential of compiler-level optimizations for zkVM performance and opens new direction for zkVM-specific passes, backends, and superoptimizers.
The dawn of the disruptive quantum computing scenario marks a serious threat to the existence of traditional cryptosystems. With laws such as Shorâs, capable of factoring large integers in polynomial time, and Groverâs, able to speed up brute-force key searches, these attacks make conventional public-key infrastructures increasingly vulnerable, whereas even symmetric ciphers lose good measure of their strength. In this article, we focus on an elaborative description of a patented method for quantum-secure key generation, wherein Qabbalah (QBLH) complexity is utilized in the geometric-symbolic realm, in conjunction with magic number squares, phi/pi coordinate weighting, and tetrahedral trinary state encoding. The proposed system of TriGate QBLH Quantum-Safe Encryption converts seed inputs to multidimensional keys that resist linear algebraic attacks owing to non-linear permutations, irrational constant weighting, and topological complexity. Normally, pseudo-random number generators spatialize entropy in Euclidean geometry, as opposed to the present technique that places entropy in a completely non-Euclidean domain, where classical as well as quantum adversaries find it hard to traverse. We describe the method in detail, present its benefits over lattice- and hash-based post-quantum schemes, and walk through an example of its implementation. Consideration is also given to its potential integration with PQC standards, blockchain authentication, and decentralized finance applications. The system fuses symbolic mathematics, such as the 231 Gates of QBLH, with trinary logic mapped onto tetrahedral states to not only create encryption keys but also verifiable geometric signatures. This represents a paradigm shift toward geometric cryptography, which may be a viable method to realize scalable and trustworthy digital infrastructure in a quantum-threatened environment.
Zero-Knowledge Proofs (ZKPs) have emerged as a powerful tool for secure and privacy-preserving computation. ZKPs enable one party to convince another of a statement's validity without revealing anything else. This capability has profound implications in many domains, including machine learning, blockchain, image authentication, and electronic voting. Despite their potential, ZKPs have seen limited deployment because of their exceptionally high computational overhead, which manifests primarily during proof generation. To mitigate these overheads, a (growing) body of researchers has proposed hardware accelerators and GPU implementations of both kernels and complete protocols. Prior art spans a wide variety of ZKP schemes that vary significantly in computational overhead, proof size, verifier cost, protocol setup, and trust. The latest and widely used ZKP protocols are intentionally designed to balance these trade-offs. One particular challenge in modern ZKP systems is supporting complex, high-degree gates using the SumCheck protocol. We address this challenge with a novel programmable accelerator to efficiently handle arbitrary custom gates via SumCheck. Our accelerator achieves upwards of $1000\times$ geomean speedup over CPU-based SumChecks across a range of gate types. We include this unit in zkPHIRE, a programmable, full-system accelerator that accelerates the HyperPlonk protocol. zkPHIRE achieves $1486\times$ geomean speedup over CPU and $11.87\times$ geomean speedup over the state-of-the-art at iso-area. Together, these results demonstrate compelling performance while scaling to large problem sizes (upwards of $2^{30}$ constraints) and maintaining small proof sizes ($4-5$ KB).
Hash functions are fundamental components in both cryptographic and non-cryptographic systems, supporting secure authentication, data integrity, fingerprinting, and indexing. While the Ascon family, selected by the National Institute of Standards and Technology (NIST) in 2023 for lightweight cryptography, has been extensively evaluated in its authenticated encryption mode, its hashing and extendable-output variants, namely Ascon-Hash256, Ascon-XOF128, and Ascon-CXOF128, have not received the same level of empirical attention. This paper presents a structured benchmarking study of these hash variants using both the SMHasher framework and custom Python-based simulation environments. SMHasher is used to evaluate statistical and structural robustness under constrained, patterned, and low-entropy input conditions, while Python-based experiments assess application-specific performance in Bloom filter-based replay detection at the network edge, Merkle tree aggregation for blockchain transaction integrity, lightweight device fingerprinting for IoT identity management, and tamper-evident logging for distributed ledgers. We compare the performance of Ascon hashes with widely used cryptographic functions such as SHA3 and BLAKE2s, as well as high-speed non-cryptographic hashes including MurmurHash3 and xxHash. We assess avalanche behavior, diffusion consistency, output bias, and keyset sensitivity while also examining Ascon-XOF's variable-length output capabilities relative to SHAKE for applications such as domain-separated hashing and lightweight key derivation. Experimental results indicate that Ascon hash functions offer strong diffusion, low statistical bias, and competitive performance across both cryptographic and application-specific domains. These properties make them well suited for deployment in resource-constrained systems, including Internet of Things (IoT) devices, blockchain indexing frameworks, and probabilistic authentication architectures. This study provides the first comprehensive empirical evaluation of Ascon hashing modes and offers new insights into their potential as lightweight, structurally resilient alternatives to established hash functions.
Cloud storage has undergone drastic improvements in recent years as it facilitates the storage of huge volumes of data. However, storing data in the cloud remains a complex task as it has to deal with security concerns. Blockchain is implemented to successfully avoid the security crises involved in the cloud storage network. Several approaches have been developed to secure data transmission within the cloud, but they have resulted in minimal throughput, failed in detecting threats, and consumed more time to transmit data. To address these complexities, a Hybrid Smart Contract-enabled Lightweight Authentication framework (HSC-LwA) is proposed to secure the transmission of data in a heterogeneous blockchain. The proposed HSC-LwA model works with hybrid concepts that include a consensus algorithm, Proof of Stake (PoS), and Proof of Work (PoW). This hybrid method incorporates a reward-based strategy to verify the transaction to add a block to the network. The primary task of this model is to safeguard the information within the cloud network and the data in a heterogeneous blockchain. The evaluation of the proposed HSC-LwA method obtained the values for Gas Transaction, Genuine user rate, Responsiveness, and Transaction Time is 286.87KB, 0.88, 6.73s, and 5.48s based on transaction analysis, whereas the model showed the improvement by obtaining the values for the above metrics as 330.12KB, 0.86, 6.32s, 5.55s with user analysis.
Web3 technologies are fundamentally secured by classical cryptographic algorithms like the Elliptic Curve Digital Signature Algorithm (ECDSA), Advanced Encryption Standard (AES), and Secure Hash Algorithms (SHA). The advent of fault-tolerant quantum computers, however, poses a significant threat to these systems. Shorâs algorithm can break the asymmetric schemes that underpin user wallets and asset ownership, while Groverâs algorithm quadratically weakens the security of symmetric ciphers and hash functions. This paper presents an integrated simulation framework, built using Python and Qiskit, to demonstrate these quantum threats in a unified context. We implement simulated attacks against simplified, small-scale instances of RSA, ECDSA, AES, and SHA to model the structural feasibility of these quantum attacks. For Shorâs algorithm, we utilize a classical simulation of the quantum oracles for modular exponentiation and elliptic curve point addition, focusing on the viability of the overall quantum-classical workflow. For Groverâs algorithm, we use standard Qiskit circuit library implementations with simplified oracles. Our findings confirm the theoretical vulnerabilitiesâsuccessfully factoring RSA-15, solving the ECDLP on a toy curve, and finding keys/preimages in 8-bit search spaces. More importantly, this work highlights the practical simulation challenges and immense resource requirements for breaking production-scale keys, reinforcing the critical need for the Web3 ecosystem to transition towards post-quantum cryptography.
Blockchain bridges have become essential infrastructure for enabling interoperability across different blockchain networks, with more than $24B monthly bridge transaction volume. However, their growing adoption has been accompanied by a disproportionate rise in security breaches, making them the single largest source of financial loss in Web3. For cross-chain ecosystems to be robust and sustainable, it is essential to understand and address these vulnerabilities. In this study, we present a comprehensive systematization of blockchain bridge design and security. We define three bridge security priors, formalize the architectural structure of 13 prominent bridges, and identify 23 attack vectors grounded in real-world blockchain exploits. Using this foundation, we evaluate 43 representative attack scenarios and introduce a layered threat model that captures security failures across source chain, off-chain, and destination chain components. Our analysis at the static code and transaction network levels reveals recurring design flaws, particularly in access control, validator trust assumptions, and verification logic, and identifies key patterns in adversarial behavior based on transaction-level traces. To support future development, we propose a decision framework for bridge architecture design, along with defense mechanisms such as layered validation and circuit breakers. This work provides a data-driven foundation for evaluating bridge security and lays the groundwork for standardizing resilient cross-chain infrastructure.
The Internet of Things (IoT) has become an integral part of daily life, making the protection of user privacy increasingly important. In gateway-based IoT systems, user data is transmitted through gateways to platforms, pushing the data to various applications, widely used in smart cities, industrial IoT, smart farms, healthcare IoT, and other fields. Threshold Public Key Encryption (TPKE) provides a method to distribute private keys for decryption, enabling joint decryption by multiple parties, thus ensuring data security during gateway transmission, platform storage, and application access. However, existing TPKE schemes face several limitations, including vulnerability to quantum attacks, failure to meet Simulation-Security (SS) requirements, lack of verifiability, and inefficiency, which results in gateway-based IoT systems still being not secure and efficient enough. To address these challenges, we propose a Verifiable Simulation-Secure Threshold PKE scheme based on standard Module-LWE (VSSTPM). Our scheme resists quantum attacks, achieves SS, and incorporates Non-Interactive Zero-Knowledge (NIZK) proofs. Implementation and performance evaluations demonstrate that VSSTPM offers 112-bit quantum security and outperforms existing TPKE schemes in terms of efficiency. Compared to the ECC-based TPKE scheme, our scheme reduces the time cost for decryption participants by 72.66%, and the decryption verification of their scheme is 11 times slower than ours. Compared with the latest lattice-based TPKE scheme, our scheme reduces the time overhead by 90% and 48.9% in system user encryption and decryption verification, respectively, and their scheme is 13 times slower than ours in terms of decryption participants.
Abstract The increasing levels of data collection and processing, and the consequential risks to both individual users and society, have led to rising demands for privacy. This chapter first discuses different notions of privacy, including anonymity, and how cryptography relates to them. It then reviews a range of cryptographic privacy-enhancing technologies that can be used to support a variety of privacy objectives. The first is Tor, which is used to support anonymity on the internet. Next, it is shown how zero-knowledge proofs enable truths to be communicated without revealing unnecessary information. The goal of secure multiparty computation (MPC) is to enable sensitive data from multiple sources to be input to a computation while maintaining the privacy of the component data items. Finally, a range of further technologies are introduced, including blind signature schemes, group signature schemes, homomorphic encryption, private set intersection and private information retrieval.
This paper introduces a comprehensive architectural framework for quantum-resistant health data management. The proposed Immutable Health Ledger (IHL) represents a fundamental paradigm shift an advanced Zero-Trust architecture engineered to withstand both current cyber threats and the emerging challenges posed by quantum computing, which are expected to render existing encryption standards obsolete. The IHL ensures provable data sovereignty through three foundational principles: a Biometric Trust Anchor in which patient identity serves as the cryptographic root of trust; a Post-Quantum Cryptographic Foundation built upon NIST-standardized algorithms with a hybrid deployment strategy; and a Distributed Integrity Layer that makes any form of data manipulation computationally and economically impractical. This document presents the complete mathematical formulations, formal security proofs, performance analyses, and an implementation roadmap that together define the operational and theoretical integrity of the proposed system.
Zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARK) schemes have been a promising technique in verified computation. Zk-SNARK schemes were designed to be mathematically secure against cryptographic attacks and it remains unclear whether they are vulnerable to fault injection attacks. In this work, we provide a positive answer by presenting ZK-Hammer, which leaks secrets from zk-SNARK schemes via Rowhammer. We incur faults in the exponentiate variables in the Quadratic Arithmetic Program (QAP) problem. Then we analyze the faulty proof using the bilinear pairing technique and manage to recover the secret. We employ a Rowhammer fault evaluation in libsnark and identify 3 CVEs.
Benfordâs Law and Fraud Detection
Cryptographic Implementations and Security
Advanced Steganography and Watermarking Techniques
The security proof of a protocol, though formally rigorous within a given model, is entirely contingent on the model's assumptions. If the adversary's capabilities are underspecified, the cryptographic primitives are idealized, or the security properties are incompletely formalized, the proof may not hold in practice.The first contribution advances prior work on refining symbolic models for crypto- graphic primitives to better capture their behaviors. Specifically, we propose more precise equational theories for the ElGamal cryptosystem, DSA signatures, and Zero-Knowledge Proofs. Standard symbolic modeling of these primitives disregards their algebraic prop- erties, which may lead to missed attacks in larger protocols. Additionally, we introduce a formal model of exponentiation and re-encryption Mix-Networks. By combining these models with our equational theories, we can automatically find attacks based on the incorrect use of the Mix-Networks missed by previous symbolic models.The second contribution involves analyzing the WireGuard protocol. We examine the protocol's claimed security properties under an adversary capable of compromising any possible key combinations. To systematize this analysis, we introduce the concepts of minimal defensive model and minimal offensive adversary model. The defensive models ensures that violating a security property requires possessing specific atomic capabilities. Minimal offensive models define the smallest sets of adversarial capabilities that break security. Theses derivations helped to identify an implementation optimization that introduces new attack vectors.The third contribution presents a hybrid protocol combining WireGuard and Post- Quantum WireGuard, aligning with recommendations for a secure transition to post- quantum cryptography. Although a symbolic analysis of PQ-WireGuard existed, we uncover discrepancies between the model and the protocol's specifications, including pre- viously missed Unknown Key-Share attacks. We propose fixes and ensure the hybrid protocol's security relies on both the corrected post-quantum and classical WireGuard protocols. We formally defined a hybrid protocol's security as when there exists both minimal defensive models dependent on post-quantum keys and defensive models depen- dent on classical keys. Our work underscores the importance of iterative analysis during design, as achieving hybrid security required repeated refinement between modeling and verification.
This paper presents a comprehensive examination of advanced cryptographic primitives and their instantiations, focusing on signature schemes, zero-knowledge proofs, and threshold encryption schemes. The foundational properties required for a secure and complete digital signature scheme are first outlined, with an emphasis on existential unforgeability. Zero-knowledge proofs are then examined in detail, including definitions of completeness, zero-knowledge, soundness, and simulation extractability, along with a discussion of universal versus non-universal proof systems. The core contribution lies in the design and analysis of a threshold encryption scheme based on Shamirâs secret sharing and a CLT encryption framework. The construction of a (t, P)-threshold encryption scheme is defined, introducing the concept of partial decryption simulability. The framework ensures that any (t + 1)-sized subset of parties can decrypt the ciphertext while maintaining security against adversarial attempts. Additionally, the implementation of universal zero-knowledge proof systems is discussed, highlighting the trade-offs between universal and specific SRS-based proofs. The instantiation of pseudorandom functions and their weak robustness properties is also examined, ensuring secure key management and resistance to adversarial key collisions. Through detailed analysis and construction, this work provides a solid foundation for building secure cryptographic systems with efficient threshold encryption and zero-knowledge proofs, contributing to the advancement of cryptographic protocols and their applications in secure communications and data protection.
Stephan Rabanser, Ali Shahin Shamsabadi, Olive Franzese, Xiao Wang · 6 authors
Cautious predictions -- where a machine learning model abstains when uncertain -- are crucial for limiting harmful errors in safety-critical applications. In this work, we identify a novel threat: a dishonest institution can exploit these mechanisms to discriminate or unjustly deny services under the guise of uncertainty. We demonstrate the practicality of this threat by introducing an uncertainty-inducing attack called Mirage, which deliberately reduces confidence in targeted input regions, thereby covertly disadvantaging specific individuals. At the same time, Mirage maintains high predictive performance across all data points. To counter this threat, we propose Confidential Guardian, a framework that analyzes calibration metrics on a reference dataset to detect artificially suppressed confidence. Additionally, it employs zero-knowledge proofs of verified inference to ensure that reported confidence scores genuinely originate from the deployed model. This prevents the provider from fabricating arbitrary model confidence values while protecting the model's proprietary details. Our results confirm that Confidential Guardian effectively prevents the misuse of cautious predictions, providing verifiable assurances that abstention reflects genuine model uncertainty rather than malicious intent.
Blockchain technology, with its inherent security, transparency, and immutability, presents a novel approach to addressing critical challenges in public health. This paper explores the potential of blockchain to revolutionize data management, enhance disease surveillance, and empower communities in public health initiatives. We examine how blockchain can secure sensitive health data, facilitate interoperability among disparate systems, and enable decentralized data sharing for research and interventions. Furthermore, we discuss the applications of blockchain in supply chain management for pharmaceuticals, vaccine distribution, and the creation of secure digital identities for individuals. By leveraging blockchain's distributed ledger technology, we can foster trust, improve data integrity, and promote community engagement in public health, ultimately leading to more effective and equitable health outcomes.
The proposed research presents a theoretical investigation into the integration of zero-knowledge proofs (ZKP) within autonomous defense architectures, establishing rigorous mathematical foundations for privacy-preserving security verification in next-generation cybersecurity systems. This study addresses fundamental theoretical challenges in autonomous security verification by developing novel mathematical constructs that enable privacy-preserving proof generation and verification while maintaining formal security guarantees. The research methodology encompasses the development of formal mathematical models for non-interactive zero-knowledge proof systems optimized for autonomous verification environments. These models extend existing theoretical frameworks by introducing novel constructs for proof composition and verification in distributed systems, with particular emphasis on formal security properties including completeness, soundness, and zero-knowledge characteristics.
Verifiable credentials (VCs) serve as the digital counterparts to physical credentials, with their security assured through cryptographic methods. The interest on VCs has been renewed by the publication of the European Regulation eIDAS 2.0 that instructs the member states to provide their citizens with a digital wallet (EUDI Wallet) that stores such credentials and that the citizens can use all across the European Union. A great effort has been placed in the definition of common standards that are described in the EUDI Architecture and Reference Framework (ARF), that will be used for the design of the EUDI Wallet. One of the crucial aspects is the identification of the formats and types of VCs supported to be stored in it. The goal of this thesis is twofold: first, to provide a systematic description and analysis of the two VC formats that have been the primary candidates for support by the EUDI Wallet, and second, to propose cryptographic protocols and primitives that facilitate the addition of new features to these credential formats or improve the existing ones. The two VC formats that have been the primary candidates in the development of the EUDI ARF covers (1) the VCs based on hiding commitments that are signed by the issuer using a general purpose digital signature algorithm, and (2) the anonymous credentials generated using the framework of Camenisch and Lysyanskaya, that make use of special digital signature schemes supporting NIZKP that allow one to prove knowledge of a signature created by the issuer. We describe and characterize these formats with a special focus on the cryptographic aspects underlying their design. Then, we introduce a novel cryptographic primitive that can be used to increase the security of the storage of anonymous credentials. We call this primitive multi-holder anonymous credential, and it allows a holder to split an anonymous credential in shares and store them on multiple devices. To present the credential, the holder will need the contribution of a given threshold of the devices. This ensures that as long as an adversary does not compromise enough devices, reaching the threshold, it cannot steal the credential and use it to impersonate the holder. We instantiate a multi-holder anonymous credential that is compatible with the BBS anonymous credential scheme, and we prove its security. Finally, we present a cryptographic commitment scheme whose security is proven in the standard model under assumptions on cryptographic group actions, which are quantum resistant. This commitment scheme, unlike the more efficient commitment based on hashing and salting, supports algorithms and non-interactive zero knowledge proofs to prove predicates about the committed messages, which is an important feature for privacy-preserving applications. To be more specific, when our scheme is used to create VCs, it enables holders to create predicate proofs about the attributes included in their VC, increasing their ability to minimize the disclosure of data.
Abstract: Algebraic geometry offers a powerful and elegant mathematical framework for the design and analysis of modern cryptographic protocols. This research paper investigates the application of algebraic geometry methodsâsuch as elliptic curves, abelian varieties, and projective algebraic structuresâin enhancing the security, efficiency, and scalability of cryptographic systems. By bridging advanced algebraic structures with cryptographic primitives, the study demonstrates how algebraic geometry enables the construction of secure public key protocols, zero-knowledge proofs, and post-quantum resilient schemes. Through theoretical modeling, performance benchmarking, and comparative analysis with classical cryptographic approaches, the paper illustrates the advantages of algebraic geometry in terms of computational hardness assumptions, structural integrity, and potential for innovation in secure communications. The findings contribute to the evolving landscape of cryptography by positioning algebraic geometry as a foundational tool in next-generation cryptographic protocol design. Keywords: algebraic geometry, cryptographic protocols, elliptic curves, public key cryptography, post-quantum cryptography, projective varieties, zero-knowledge proofs, secure communication, mathematical cryptography, abelian varieties
TetraUnified v2.0 presents a fully revised, academically aligned research framework integrating three experimental components: Tetrahedral Key Exchange (TKE):Exploratory key exchange mechanism based on recursive geometric projections. Recursive Tesseract Hashing (RTH):Hyperdimensional hashing model using 16-axis Clifford projections and recursive entropy mixing. Quantum Isoca-Dodecahedral Lattice Encryption (QIDL):Conceptual encoding model for representing plaintext within dynamic polyhedral phase lattices. This version restructures the system into a coherent research-grade framework, emphasizing mathematical clarity, reproducibility, consistent notation, and proper cryptographic disclaimers.No security guarantees are claimed and no component should be used in production systems.All structures are intended strictly for experimental simulation, prototyping, and conceptual evaluation. Purpose of This Release Version 2.0 was developed to achieve three objectives: Remove speculative, metaphorical, or narrative content from earlier drafts and establish a formal academic tone. Strengthen mathematical structure and notation, including explicit operator definitions and theoremâproof formulations. Position the system as a technical R&D testbed, rather than a security product or operational cryptographic protocol. This release supersedes all previous versions.Earlier manuscripts are preserved only as historical development notes. Key Improvements in v2.0 1. Formal Mathematical Structures Includes new theoremâproof style sections addressing: TKE reconstruction consistency RTH entropy evolution under recursion QIDL transformation intractability (as a conceptual model) Defined core operators: Projection (đŻ) Modulation (f) Reconstruction (đ) Polyhedral rotation (đ_{I,D}) Sealing (đź) Geometric embeddings now use clearly stated synthetic Clifford bases. 2. Cryptographic Positioning TKE, RTH, and QIDL are explicitly described as experimental, unverified, not secure, and not production-ready. No hardness assumptions are claimed. All constructs are positioned as alternative simulation models inspired by geometric/topological methods. 3. Distributed Systems & Navigation Concepts Introduces a conceptual framework for: phase-based synchronization inertial alignment without external timing sources distributed state coordination under high latency resilience to environmental drift or partial network partitions 4. Comparison with Existing Quantum Programming Includes a revised comparison table contrasting: NISQ-era quantum programming TetraUnifiedâs hyperdimensional simulation models Highlights key architectural differences without implying superiority. 5. Expanded Application Sections Updated application discussions for TKE, RTH, and QIDL covering: distributed identity experiments mesh communication models ledger integrity prototyping inertial navigation research off-world / high-latency environments multi-agent swarm coordination recursive lineage tracking for AI pods All applications are strictly conceptual research pathways, not operational deployments. Version Philosophy TetraUnified v2.0 establishes the framework as: an academic-style experimental cryptography model a research environment for hyperdimensional and geometric transformations an R&D prototype for studying non-linear distributed coordination a computational sandbox for exploring alternative post-quantum architectures No practical security, correctness, or adversarial resistance should be inferred.Formal verification and cryptanalysis remain open areas for future work. Included Artifacts This release includes: the revised LaTeX manuscript (PDF) updated mathematical definitions for TKE, RTH, QIDL reference diagrams and basis definitions example code structures (if present in repository) reproducibility metadata and version history Notes on Previous Versions Earlier versions contained exploratory and speculative material.Version 2.0 replaces these with a rigorous mathematical and systems-engineering structure. Per Zenodo policies, earlier versions remain visible but represent developmental prototypes only.The DOI series now resolves to v2.0 as the authoritative technical edition. Intended Use TetraUnified v2.0 is intended for: researchers exploring geometric or topological cryptography models distributed systems experimentation verifiable computation and XR/digital-twin state modeling conceptual post-quantum architecture studies academic and peer review simulation, prototyping, and reproducibility analysis This work is not intended for operational cryptography, production deployment, or security-critical environments. Citation MacDonald, M. (2025).TetraUnified v2.0 â Experimental Framework for Hyperdimensional Cryptography, Recursive Hashing, and Distributed State Models.Zenodo. https://doi.org/10.5281/zenodo.17759222
To provide the encrypted data with public tamperproof and traceability, in this paper, we first explore and discuss that the alone signature attached to the encrypted data is in a low coupling state with the ciphertext which gives rise to signature substitution attack destructing assurance of the encrypted data. Then we propose a new cryptographic primitive called Secret-Embedded Ciphertext Signature of Knowledge (SECTSoK). And then give the general construction of SE-CTSoK in Schnorr identification scheme form over groups. The proposed SE-CTSoK is not only a signature for the ciphertext to make the ciphertext tamper-proof, but also a zero-knowledge argument of the ciphertext random secret to give the proof that the ciphertext secret is embedded in SE-CTSoK for sure without revealing it. Furthermore, we introduce the standardized definition of the Irreconfigurability model for the ciphertext signature to cover any type of the signature substitution attack, and then we give the formalized proof to our proposed SE-CTSoK in Irreconfigurability model which demonstrates that the ciphertext with the corresponding SE-CTSoK can only be correctly traced and confirmed to the ciphertext generator.
This paper introduces the Cartesian Merkle Tree, a deterministic data structure that combines the properties of a Binary Search Tree, a Heap, and a Merkle tree. The Cartesian Merkle Tree supports insertions, updates, and removals of elements in $O(\log n)$ time, requires $n$ space, and enables membership and non-membership proofs via Merkle-based authentication paths. This structure is particularly suitable for zero-knowledge applications, blockchain systems, and other protocols that require efficient and verifiable data structures.
Zero-Knowledge Proofs (ZKPs) are a rapidly growing technique for privacy-preserving and verifiable computation.ZKPs enable one party (a prover: P) to prove to another (a verifier: V) that a statement is true or correct without revealing any additional information.This powerful capability has led to ZKPs being applied and proposed for application in blockchain technologies, verifiable machine learning, and electronic voting.However, ZKPs have yet to see widespread, ubiquitous adoption due to the exceptionally high computational complexity of the proving process.Naturally, there has been recent work to accelerate ZKP primitives and protocols using GPUs and ASICs.However, the protocols considered so far face one of two challenges: they require a trusted setup for each new application or generate large proofs with high verification costs, limiting their applicability in scenarios with numerous verifiers or strict verification time constraints.HyperPlonk is a state-of-theart ZKP protocol that supports both one-time, universal setup and small proof sizes/verification costs expected by publicly verifiable, consensus-based systems (e.g., blockchain).While HyperPlonk's setup and verifier properties are highly desirable, the proving phase is costly.A HyperPlonk prover must compute on large bitwidths (e.g., 255-381b) and polynomials (e.g., of degree 2 24 ), employs computationally (e.g., MSM) and bandwidth (e.g., SumCheck) intensive kernels, and the complete protocol comprises many steps, each constituting distinct kernels.We present an accelerator, zkSpeed, to
Artificial Intelligence (AI) is profoundly transforming cryptography by significantly enhancing cryptanalysis techniques and informing innovative cryptographic design approaches. This survey reviews recent advancements in applying deep learning methods to side-channel and differential fault analyses, demonstrating substantial improvements over traditional methods in attack efficiency, accuracy, and resilience. Additionally, it highlights breakthroughs such as neural differential cryptanalysis, which expand classical cryptanalytic boundaries. In cryptographic design, Generative Adversarial Networks (GANs) have successfully automated the creation of high-quality cryptographic primitives, particularly S-boxes. Furthermore, AI shows promise in post-quantum cryptography (PQC) by uncovering potential vulnerabilities and optimizing cryptographic parameters. Despite these advancements, challenges persist regarding data dependency, model generalization, and interpretability. Future research directions emphasize enhancing AI model explainability, creating standardized benchmarks, and integrating AI with emerging technologies such as quantum computing and zero-knowledge proofs.
Open access
Cryptographic Implementations and Security
Chaos-based Image/Signal Encryption
Physical Unclonable Functions (PUFs) and Hardware Security