Mohammad Javad Jannati, Abolfazl Iraninasab, Mehrshad Eskandarpour
As blockchain adoption accelerates, smart contracts have become attractive targets for attackers, often resulting in significant financial losses. While many studies focus on well-known vulnerabilities like reentrancy or integer overflows, weaknesses in pseudo-random number generation (PRNG) remain a persistent and critical challenge despite their role in decentralized applications such as lotteries, games, and token distribution. In Ethereum, randomness is often derived from predictable environmental variables like block timestamps or sender addresses, making these systems vulnerable to manipulation. This paper presents a rigorous investigation into PRNG vulnerabilities in Ethereum smart contracts and introduces two practical attack strategies. The first method relies on brute-force contract deployment to obtain a desired output, incurring high gas costs. The second approach leverages the CREATE2 opcode to precompute candidate contract addresses off-chain, reducing gas usage by over 90%. However, since final outcome prediction depends on block.timestamp at execution time, attack success is contingent on network timing stability and validator behavior. Through formal analysis and empirical evaluation on a controlled local test network, we demonstrate success rates of 100% for Method 1 and 98% for Method 2 under fixed-timestamp conditions. Under simulated live-network congestion, Method 2 success drops to 87% due to block.timestamp sensitivity. Our findings highlight the urgent need for secure randomness solutions, such as verifiable random functions (VRFs) and decentralized randomness beacons. Without adopting such mechanisms, blockchain applications across Ethereum and other EVM-compatible platforms remain exposed to critical security risks.
Rajasekaran P., Duraipandian M., Johny Renoald Albert, R. Jamuna · 5 authors
The Internet of Medical Things (IoMT) in the IoT with Cloud Healthcare (CHI) creates a high volume of real‐time medical data, but traditional compression methods suffer high computation costs, privacy leaks and quantum attacks, while advanced cryptographic algorithms such as homomorphic encryption are costly and have poor scalability for the real‐time system application. In this work, we propose a quantum‐enhanced zero‐knowledge healthcare compression network (QZ‐HCN) that associates zero‐knowledge proofs (ZKPs) with quantum‐inspired deep learning (QIDL) by introducing an innovative adaptive quantum‐supported ZKP verification mechanism (AQ‐ZKV) and a quantum fusion autoconventional neural network (QF‐AutoCNN) technique to achieve efficient, privacy‐preserving compression. For healthcare IoT datasets, QZ‐HCN can reach 98.16% in accuracy, 97.09% in F‐measure, 96.32% in precision and 97.45% in recall, with a throughput of 449.57 bits/s; processing time is reduced to 0.85 s, and memory cost is minimised to be only 192 kbits, which outperforms CNN‐Encryption (90.23% accuracy), proxy re‐encryption and homomorphic encryption by at most 13 percentage points in accuracy and 75 percentage points in memory efficiency. The secure and scalable management for CHI data is achieved by QZ‐HCN, which solves the problems of privacy threats and space costs of real‐time medical applications.
Biometric authentication provides high convenience with the drawback of privacy leakage, replay attacks, and centralized control over biometric templates. This paper introduces an Ethereum-based decentralized biometric authentication framework that uses Elliptic Curve Digital Signature Algorithm (ECDSA), InterPlanetary File System (IPFS) storage, and an on-chain challenge–response protocol. In the proposed model, encrypted biometric templates are stored of-chain in IPFS, whereas their content identifiers (CIDs) are registered in Ethereum smart contracts. Every authentication attempt necessitates a new on-chain nonce and an ECDSA signature of the concatenation of the CID and the nonce, authenticated through Ethereum’s built-in method, ecrecover. The design supports explicit replay protection, revocation, and public auditability. Deployment of the prototype on Ganache and MetaMask reveals that the scheme provides secure, transparent, and tamper-proof authentication with minimal gas consumption on FVC2004 datasets and reasonable storage usage on Ethereum.
Open access
Cryptography and Data Security
Advanced Steganography and Watermarking Techniques
The fast digitalization of contemporary society has changed the data into a valuable resource, and it has been the key to the innovation in the financial sector, healthcare, politics, and industries, and it has also increased risks both in terms of misusing it, stealing it, and using it. Information security through maintaining confidentiality, integrity and availability of information has thus become a pre-requisite to trust in digital infrastructures. The present paper gives a detailed discussion of how cryptography, cybersecurity, and data privacy come into convergence and have a central role to play in protecting the digital ecosystems. Basic cryptographic primitives such as symmetric and asymmetric encryption, hash functions as well as digital signatures are discussed as the foundation of secure communication. With these, more complex privacy-sensitive technology like homomorphic encryption, zero-knowledge proofs, and differential privacy is discussed as technology that could offer the opportunity to perform safe computation and share data without jeopardizing the privacy of individuals.The paper also explores the disruptive potential of quantum computing, specifically how it can render the popular public-key systems insecure by figuring out ways to break them, e.g. the Shor algorithm, and assesses the new paradigm of post-quantum cryptography as a reaction to this existential risk. The examples are discussed within various fields such as secure communication schemes, data-at-rest security, cloud computing, and the Internet of things (IoT), e.g., in which cryptographic efficiency and versatility are most crucial. It is a synthesis of these factors that the paper highlights that cryptography is not only a technical protection but it is a cornerstone enabling resiliency, trust, and privacy-by-design in the digital era. This paper then ends with a discussion on the challenges that still need to be tackled, including scalability, usability and compliance with regulations, and how future research will be needed to define the future of secure and privacy-preserving technologies in the increasingly interconnected world.
The article presents an analysis of the robustness of an authentication scheme based on zero watermarking. The study examines a two-factor authentication scheme that uses "knowledge of something" (a password) and "possession of something" (a digital RGB image) as its factors. The zero watermarking algorithm chosen is based on DWT and K-means transformations, with additional use of the Swish function. The analysis is conducted by considering the theoretical complexity of the algorithm assuming the adversary knows its parameters, such as the password, the hash of the password, the image, the reference watermark, the transformation result, and other parameters. Previous studies have shown a high theoretical robustness of the scheme, which relies on the complexity of the password and the dimensionality of the image. For large image sizes (512×512 pixels and above), a relatively high level of cryptographic resistance is achieved. However, this robustness is not formally proven, and the actual strength may be significantly lower due to the specifics of the images and transformations, which can introduce additional vulnerabilities. The algorithm is subject to a relatively high rate of collision, associated with digital image transformations and matrix multiplications, which weakens its resistance. Authentication schemes and zero watermarking algorithms require further research, formal proof of cryptographic properties, and methods for integration into access control systems, as they can provide a high level of authentication robustness in systems with high noise levels. Additionally, the convenience and low cost of such schemes give them an advantage over other authentication methods. The study provides recommendations for improving the potential characteristics of the algorithm.
Open access
Advanced Steganography and Watermarking Techniques
The growth of cloud computing in the healthcare field has led to significant developments, but ensuring the confidentiality and protection of medical records such as electronic health records (EHRs) remains a major concern for healthcare service applications. In cloud computing, the basic authentication provided by most service providers is insufficient to ensure secure access to critical or sensitive resources. Moreover, most of the existing healthcare management systems are ineffective in handling a number of patient data, which leads to single points of failure. To address these issues, elliptic curve cryptography (ECC) with Curve25519 is utilized to enhance security in cloud storage, particularly within healthcare management systems. The ECC with Curve25519 is optimized for efficient and fast scalar multiplication, which reduces computational overhead and enhances performance. The curve parameters are selected to prevent vulnerabilities and ensure security against known attacks. Moreover, it is efficient in maintaining the integrity of patient records, which reduces storage and bandwidth requirements. The ECC with Curve25519 achieves lower Key-Gen, prove, verify, proving key size, and verification key size of 13.7 s, 48 s, 0.608 s, 13.27 Mb, and 123.70 Kb, respectively, in comparison with proxy re-encryption algorithm with zero-knowledge proof (ZKP).
The paper explores the possibility of expanding the use of end-to-end encryption protocols based on the Double Ratchet algorithm in applications with low trust in the server, particularly in turn-based games and strategic interactions. The relevance of the research is due to the growing need for secure communication in cyberattacks, especially during military operations. The field of end-to-end encryption requires the study of additional applications beyond the usual ones, such as encrypted communication in text messengers. The developed implementation of the protocol can be safely used in any applications that aim to implement end-to-end encryption and satisfy the criterion of session ephemerality (in cases where secrets are stored outside a secure environment). The implemented server supports ephemeral sessions, which guarantee minimal risks of information compromise, and uses digital signatures (EdDSA) for user authentication. Logical routing of requests ensures efficient message transmission in secure scenarios. The choice of the classic game of checkers as an example allowed the authors to effectively demonstrate the advantages of end-to-end encryption and the capabilities of the implemented protocol. All cryptographic operations, including key generation, encryption and decryption of messages, are successfully performed on client devices. It is important to improve error handling mechanisms and optimize the operation of WebAssembly. An interesting area of further research is the creation of zero-knowledge proof mechanisms to prevent Man-In-The-Middle attacks during the creation of a shared secret, optimizing integration with cryptographic hardware security modules (HSM), and exploring the scalability of the solution. The proposed approach can be used to solve real-world information security problems where trust in the data transmission channel is critically important. Thus, the work has created a comprehensive solution that includes a cryptographic protocol, a backend, and a web client, which demonstrates the viability of end-to-end encryption in browser environments and multiplayer games. The work can be used as a basis for further research and development in the field of security of communication systems and privacy in multiplayer games.
10.5281/zenodo.17605813 chaos structure complexity sequences / test files / public domain Chaos Complexity Domain Sequencing"Maximum Entropy Equilibrium"sha384sum OUTFN_BASE-OUTFN_VER-OUTFN_VERMIN-20221230191340.OUTFN_EXT.1069cbf8cebedf73040848960d915d728f8ebce64de339e57c03984b9b125065571ee73cba2fbe8324d57770631f22d3c27download Value Char Occurrences Fraction 0 4000000106 0.500000 1 3999999894 0.500000Total: 8000000000 1.000000Entropy = 1.000000 bits per bit.Optimum compression would reduce the sizeof this 8000000000 bit file by 0 percent.Chi square distribution for 8000000000 samples is 0.00, and randomlywould exceed this value 99.81 percent of the times.Arithmetic mean value of data bits is 0.5000 (0.5 = random).Monte Carlo value for Pi is 3.141394237 (error 0.01 percent).Serial correlation coefficient is 0.000013 (totally uncorrelated = 0.0).sha384sum OUTFN_BASE-OUTFN_VER-OUTFN_VERMIN-20230103155948.OUTFN_EXT.107d6275873f72a0edc7585db17bba50cdfb4a5097f3f50ac7b69eaa85ae8ec95975fb187579a5b05ff0c69ca71378fe71d download Value Char Occurrences Fraction 0 4000000107 0.500000 1 3999999893 0.500000Total: 8000000000 1.000000Entropy = 1.000000 bits per bit.Optimum compression would reduce the sizeof this 8000000000 bit file by 0 percent.Chi square distribution for 8000000000 samples is 0.00, and randomlywould exceed this value 99.81 percent of the times.Arithmetic mean value of data bits is 0.5000 (0.5 = random).Monte Carlo value for Pi is 3.141257485 (error 0.01 percent).Serial correlation coefficient is 0.000004 (totally uncorrelated = 0.0). DATA MORGANA COMMUNICATIONS AUTHOR/ EDWIN J. VENINGEDITOR EDWIN J. VENINGCORRESPONDENCE ADMIN@DATAMORGANA.NETWEBSITE SPAWN HTTPS://WWW.DATAMORGANA.NETRELEASED DD 20230525 [ YYYYMMDD ]EDIT REV.DD 20231208 over 20230726REF <symbolic base> See addendum:- binary ambiguity is expectedIntroduction in Dutch : page 2 20230726 crt0 Addendum: The test vectors presented here stem from the design of a custom generator, originally intended to outperform competitors in various categories of "randomness" generation. The goal was to achieve chaotic streams that exceeded the capabilities of other contenders, without relying on traditional methods for balancing distribution qualities. The resulting system incorporates parametric high-gain, maximum entropy equilibrium functions and methods, with output files available for download from this page. These files are derived from this work and should be used with caution. Historical Context: In 2019, a proposal was made to enhance the cryptographic subsystem of operating systems through a novel approach. This concept involved hardening the system with a new cryptographic processing "idea" of operation(s), integrated within a fresh confidence model. This idea was presented as the open-source project: /dev/entropy, a Unix non-blocking character device designed for non-disclosed ZKP (Zero-Knowledge Proof) seasonal or projected transactions/operations. The goal was to bootstrap system entropy pools using unique host identification, confidence constraints, and host signature processing in its own ZKP design (a system verifier capsule). /dev/entropy was intended to serve as the system entropy pool, which would be well-documented and securely stored. The author and programmer asserted that chaining cryptographic functions could weaken their security, leading to a proposal for entropy pools that would re-seed cryptographic functions in the host stack using non-linear, complexity-driven methods. These operations were intentionally designed to be opaque to prevent exposure, aiming to mitigate known mechanical noise attack vectors and thwart binary dissection. The processing would involve a novel use of "RAM" or "held latent memory." The project concluded in 2019 but remains a significant influence on the development of unique event processing and symbolic information transformations. As for the test vectors, no claims are made regarding their randomness or indexing properties. Envisioned Applications for the Methods and Functions: High-speed calibration of scientific instruments High-gain precision, offering persistent increases in resolution for guidance systems, telemetry, and high-availability scheduling (real-time systems) Persistence of identification tokens, tokenizing information by range, sequence hinting (*), as suggested in the ZKP paper ZKP 'circuitry' / 'gadgets' with enhanced properties, allowing for directional confidence balancing and omni-directional jumps, encoding with unique event processing such as spacetime locality encoding Real-time processing improvements, introducing new priority-type scheduling and domain sequencing (correlated context, with no known limits or recursion results) Application of "lossy" parity and "hashing" in new contexts, utilizing range hinting or the development of a symbolic encoded sequence that persists in noisy systems. The ratio is under testing. Expected hardware development: Domain sequencing through event processors with hardened/optical circuitry and one-way functions These methods aim to serve as a critical infrastructure carrier post-quantum Cryptography (PQC), offering potential solutions for complex network topologies and signal semantics for future interstellar applications. This approach leverages spatial and referential qualities without sudden collapse, adding the Temporal Domain Cryptography from 2015 as part of the ongoing evolution. DISCLAIMER: The contents of these vectors may contain the densest information to date, with an inherent carbon footprint that requires careful handling. Due to the dense nature of this data, it may cause local mechanical friction and, in extreme cases, could lead to combustion. As with any significant discovery, proceed with caution. Note: This is not the recommended practice in the narrowing binary domain of information. For reference: CACert Random Number Results — "No Entropy Here" home https://www.datamorgana.net
The convergence of quantum physics and machine learning presents unprecedented opportunities for developing ultra-secure authentication systems. This comprehensive paper investigates the integration of quantum random number generators (QRNGs) with advanced machine learning architectures, including quantum neural networks (QNNs), long short-term memory (LSTM) networks, and hybrid quantumclassical models, to establish authentication mechanisms with information-theoretic security guarantees. We provide rigorous theoretical foundations spanning quantum entropy theory, min-entropy estimation, and randomness certification, complemented by detailed analyses of contemporary QRNG hardware implementations including photonic integrated circuits achieving generation rates exceeding 20 Gbps. The paper explores deep learning architectures for biometric authentication, demonstrating how QNN-enhanced systems achieve superior performance through quantum superposition and entanglement. Furthermore, we examine the application of quantum entropy sources in zero-knowledge proof protocols, particularly zk-SNARKs and zk-STARKs, addressing post-quantum security concerns. Through comprehensive mathematical formulations, algorithmic implementations, and security analyses, we establish that hybrid quantum-classical authentication systems combining QRNG-derived cryptographic keys with ML-based behavioral authentication provide provably secure, practical solutions for next-generation cybersecurity applications. Experimental results from current quantum hardware platforms validate theoretical predictions and demonstrate real-world applicability.
Open access
Chaos-based Image/Signal Encryption
Physical Unclonable Functions (PUFs) and Hardware Security
Abstract — The Fractal Eavesdrop Detection (FED) protocol defines a cryptographic mutual-authentication... The Fractal Eavesdrop Detection (FED) protocol defines a cryptographic mutual-authentication and integrity validation mechanism between two fractal nodes sharing a recursive lineage. Unlike conventional systems that rely on fixed keys or static hashes, FED uses algorithmic mutability, session-based seed derivation, multi-point challenge validation, and time-bound CRC binding to detect both impersonation and passive eavesdropping. The protocol is designed for lightweight, low-power devices such as ESP32-class microcontrollers and operates without blockchain consensus or zero-knowledge proofs, while still enabling secure proof-of-origin and tamper-awareness. FED serves as the security and validation layer within the EQUORA Institute’s Fractal Economy architecture and complements the BlockFractal cryptographic tokenization layer and the EquoraVault hardware-based proof-of-impact system. This document is released as part of the EQUORA Institute White Paper Series and is a preprint version (v0.8), subject to revision. All versions remain archived for DOI-based citation integrity.
Open access
2 source records
Chaos-based Image/Signal Encryption
Physical Unclonable Functions (PUFs) and Hardware Security
Zero-Knowledge Proofs (ZKP) and Homomorphic Encryption (HE) are crucial for data privacy in applications like cloud, blockchain, and analytics. However, the real-world adoption often faces performance challenges, particularly in the execution of the Number Theoretic Transform (NTT) required for polynomial multiplication involving sizes beyond \(2^{20}\) and large integer widths (e.g., 256 bits). FPGAs offer a promising platform for acceleration, but efficiently implementing large-size NTTs remains difficult due to the limited on-chip resources. The widely adopted four-step NTT method, used to relieve the need for large on-chip memory, introduces performance bottlenecks. Initially, the traditional dataflow NTT architecture may not fully exploit available compute capability, which hinders achieving peak performance. Furthermore, during the matrix transpose phase, the non-sequential access to external High-Bandwidth Memory (HBM) causes inefficiency. To address these challenges, we introduce HiFA, an FPGA-based automatic accelerator framework designed for high-performance and flexible large-size NTT computations. HiFA utilizes a stacked NTT architecture for high parallelism, maximizing HBM throughput. It supports various decomposed polynomial sizes via a novel reordering module. Additionally, a specialized cyclic shuffle module is integrated to optimize data movement during the matrix transpose step, alleviating random memory access delay. HiFA also provides an automatic Design Space Exploration (DSE) framework that identifies optimal four-step decomposition parameters and generates corresponding hardware configurations. Our experiments show that the FPGA implementation of HiFA achieves an average speedup of 2.97× and up to 7.25× improvement in latency over prior state-of-the-art FPGA solutions. Compared to prior GPU-based methods, HiFA achieves an average energy efficiency gain of 2.24×.
A. G. Ramakrishnan, Shubham Agarwal, Sharmila Kumari Selvanayagam, Kunwar P. Singh
As image generation models grow increasingly powerful and accessible, concerns around authenticity, ownership, and misuse of synthetic media have become critical. The ability to generate lifelike images indistinguishable from real ones introduces risks such as misinformation, deepfakes, and intellectual property violations. Traditional watermarking methods either degrade image quality, are easily removed, or require access to confidential model internals – making them unsuitable for secure and scalable deployment. We are the first to introduce ZK-WAGON, a novel system for watermarking image generation models using the Zero-Knowledge Succinct Non-Interactive Argument of Knowledge (ZK-SNARKs). Our approach enables verifiable proof of origin without exposing model weights, generation prompts, or any sensitive internal information. We propose Selective Layer ZK-Circuit Creation (SL-ZKCC), a method to selectively convert key layers of an image generation model into a circuit, reducing proof generation time significantly. Generated ZK-SNARK proofs are imperceptibly embedded into a generated image via Least Significant Bit (LSB) steganography. We demonstrate this system on both GAN and Diffusion models, providing a secure, model-agnostic pipeline for trustworthy AI image generation.
Open access
2 source records
Physical Unclonable Functions (PUFs) and Hardware Security
Adversarial Robustness in Machine Learning
Generative Adversarial Networks and Image Synthesis
The dawn of the disruptive quantum computing scenario marks a serious threat to the existence of traditional cryptosystems. With laws such as Shor’s, capable of factoring large integers in polynomial time, and Grover’s, 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.
Health-care is undergoing a considerable digital shift in the present state, which is driven by the rise of new technologies and the changes taking place globally. The movement is rebalancing the provision and availability of health care, at the same time that it highlights the importance of protecting confidential information about patients. Coupled with the cryptographic primitives, blockchain technology provides a formidable answer, as it promises to improve data integrity using decentralized processes. In this paper, a hybrid blockchain-based EHR management and security solution to Electronic Health Records (EHRs) is described. Having considered the drawbacks of the blockchain in its ability to work with large files the system is connected with Ethereum blockchain through Ganache and program construction tools is equipped with the InterPlanetary File System (IPFS). In the hybrid model, one does store each row hash (unique identifier) of the patients records on the blockchain, but one does not store the actual data on the blockchain, instead on IPFS. A Decentralized Application (DApp) built on the programing language of Ethereum, Solidity, and the web3.js interface also allows secure data access via cryptocurrency wallets like MetaMask. The use of smart contracts is deployed to process transactions to achieve transparency and verifiability. To enhance security the Elliptic Curve Digital Signature Algorithm (ECDSA) is adapted to provide unauthorised access. Results of simulation reveal that a suggested method is reliable in providing patient data security, maintain immutability, and secure exchange of data. The approach promotes transparency within the digital health-care systems and strengthens the stakeholder belief by allowing a decentralised structure of these systems.
This paper unveils the LemniCoin ecosystem, advancing from a Binance Smart Chain (BSC) foundation to a quantum-resistant paradigm through the Lemniscate-AGM Isogeny (LAI) cryptosystem.Building on security audits conducted on March 27, 2025, and April 13, 2025, we introduce LemniCoin-QR (April 2025), a quantumhardened token; a secure wallet (May 2025); and LemniChain (December 2025), a Proof-of-Stake (PoS) blockchain.The Lemniscate-AGM Isogeny Problem (LAIP) underpins LAI, offering unparalleled resistance to quantum threats, surpassing Bitcoin (BTC) and Ethereum (ETH).We provide detailed proofs, audit insights, and implementation strategies, demonstrating superior security, transaction efficiency, and environmental sustainability-positioning LemniCoin as a premier investment in the post-quantum era.
In a time of rising cyber threats and widespread digital communication, protecting sensitive information is crucial. This paper offers a detailed survey and analysis of current methods in secure communication, focusing on the relationship between cryptographic systems and steganographic techniques. We base our work on foundational mathematics, especially commutative algebra, and use modern technologies like Generative Adversarial Networks (GANs), zero-knowledge proofs, and quantum-resistant algorithms. We present a layered approach to information security. We discuss how combining classical and modern cryptography with improved steganographic embedding and signal processing techniques highlights the need for hybrid and adaptable models to protect communication. This study aims to be a reference point for future research and development in secure digital systems. Key Words: Cryptography : from classical to post-quantum, Steganography and Data hiding Techniques, GAN-Based Steganography in wireless sensor network , Methodology Overview.
bstract In order to give users instant access to market data, portfolio management features, and analytical tools, this research paper introduces CryptoTracker, a feature-rich real-time cryptocurrency tracking application. The system makes use of contemporary web technologies to provide a responsive interface that is constantly updated to reflect the state of the market. In addition to outlining the system's functionality, architecture, and implementation specifics, we also go into the difficulties in creating trustworthy cryptocurrency tracking tools in a volatile market. Keywords: Cryptocurrency, Real-time tracking, Portfolio management, Web technologies, Financial analysis, Data visualization
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 methods—such as elliptic curves, abelian varieties, and projective algebraic structures—in 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 theorem–proof 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 theorem–proof style sections addressing: TKE reconstruction consistency RTH entropy evolution under recursion QIDL transformation intractability (as a conceptual model) Defined core operators: Projection (𝒯) Modulation (f) Reconstruction () Polyhedral rotation (_{I,D}) Sealing (𝒮) 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 TetraUnified’s 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 — Experimental Framework for Hyperdimensional Cryptography, Recursive Hashing, and Distributed State Models.Zenodo. https://doi.org/10.5281/zenodo.17759222
The rapid advancement of quantum computing presents a fundamental challenge to modern cryptographic security, particularly in the domain of hash functions that ensure data integrity, authentication, and blockchain security. Traditional crypto graphic hash functions such as SHA-256, SHA-3, and BLAKE2 rely on computational hardness assumptions that become obsolete in the presence of large-scale quantum computers. Shor’s algorithm can efficiently break RSA and ECC-based cryptosys tems, while Grover’s algorithm reduces the security of traditional hash functions by square root complexity, significantly weakening their preimage and collision resistance. This quantum threat necessitates the development of post-quantum secure hashing techniques that remain resilient against both classical and quantum adversaries. This paper proposes Quantum Hashing, a novel cryptographic framework that integrates quantum entanglement, lattice-based cryptography, and hybrid quantum classical hashing to construct post-quantum secure hash functions. We introduce a formal model for Quantum Collision Resistance (QCR) and provide entropy-based ran domness enhancement to ensure unpredictable hash outputs. Unlike classical hashing approaches, our framework leverages the hardness of lattice problems (e.g., Shortest Vector Problem, Learning with Errors) to withstand quantum attacks while incorpo rating Quantum Key Distribution (QKD) mechanisms to enhance entropy and key management. Furthermore, we evaluate the security of Quantum Hashing under various attack models, comparing its resistance against Grover’s search and collision attacks. We benchmark its performance against NIST Post-Quantum Cryptography (PQC) final ists, including CRYSTALS-DILITHIUM, SPHINCS+, and Falcon, demonstrating that our approach offers superior resilience while maintaining computational feasibility. Additionally, we present an implementation of Quantum Hashing using Qiskit, show casing its practical applicability in quantum circuits and quantum-secure blockchain architectures. Our findings highlight that Quantum Hashing provides a scalable, entropy-efficient, and post-quantum resilient cryptographic primitive suitable for next-generation cryptographic applications. This work paves the way for secure post-quantum digital signatures, blockchain consensus mechanisms, and zero-knowledge proof systems that require tamper-resistant hashing in a quantum computing era.
Justin A. Drake, Dmitry Khovratovich, Mikhail Kudinov, Benedikt Wagner
With the threat posed by quantum computers on the horizon, systems like Ethereum must transition to cryptographic primitives resistant to quantum attacks. One of the most critical of these primitives is the non-interactive multi-signature scheme used in Ethereum's proof-of-stake consensus, currently implemented with BLS signatures. This primitive enables validators to independently sign blocks, with their signatures then publicly aggregated into a compact aggregate signature. In this work, we introduce a family of hash-based signature schemes as post-quantum alternatives to BLS. We consider the folklore method of aggregating signatures via (hash-based) succinct arguments, and our work is focused on instantiating the underlying signature scheme. The proposed schemes are variants of the XMSS signature scheme, analyzed within a novel and unified framework. While being generic, this framework is designed to minimize security loss, facilitating efficient parameter selection. A key feature of our work is the avoidance of random oracles in the security proof. Instead, we define explicit standard model requirements for the underlying hash functions. This eliminates the paradox of simultaneously treating hash functions as random oracles and as explicit circuits for aggregation. Furthermore, this provides cryptanalysts with clearly defined targets for evaluating the security of hash functions. Finally, we provide recommendations for practical instantiations of hash functions and concrete parameter settings, supported by known and novel heuristic bounds on the standard model properties.
Muhammad Jawad, Mahmood A. Al-Shareeda, Omar Yawez Mustafa Mustafa, Mohammed Amin Almaiah · 5 authors
Analysis of repeated attack signatures is important because of the rapid evolution of the Social Internet of Vehicles (SIoV). However, threats such as replay attacks, session hijacking, and key reuse make secure communication between vehicles, roadside units (RSUs), and the fog node difficult. Traditional models for authentication are limited by computational overhead and lack quick key revocation. In response to these challenges, we propose a hybrid cryptographic authentication scheme that combines a Zero-Knowledge Proof (ZKP) with AES-GCM encryption. Our protocol implements a dynamic key revocation mechanism to avoid rogue and session key migration, minimizing re-authentication delay. Security analysis in the Real-Oracle Random (ROR) model shows that it is not vulnerable to impersonation or replay attacks. Evaluations demonstrate decreases of 58% in authentication latency while achieving 45% and 72% improvements in communication and computation efficiency, respectively. Our approach is also scalable and secure, providing SIoV with higher reliability for automotive applications in the vehicular networks of the future.
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
Data security during transmission over public networks has become a key concern in an era of rapid digitization. Image data is especially vulnerable since it can be stored or transferred using public cloud services, making it open to illegal access, breaches, and eavesdropping. This work suggests a novel way to integrate blockchain technology with a Chaotic Tent map encryption scheme in order to overcome these issues. The outcome is a Blockchain driven Chaotic Tent Map Encryption Scheme (BCTMES) for secure picture transactions. The idea behind this strategy is to ensure an extra degree of security by fusing the distributed and immutable properties of blockchain technology with the intricate encryption offered by chaotic maps. To ensure that the image is transformed into a cipher form that is resistant to several types of attacks, the proposed BCTMES first encrypts it using the Chaotic Tent map encryption technique. The accompanying signed document is safely kept on the blockchain, and this encrypted image is subsequently uploaded to the cloud. The integrity and authenticity of the image are confirmed upon retrieval by utilizing blockchain's consensus mechanism, adding another layer of security against manipulation. Comprehensive performance evaluations show that BCTMES provides notable enhancements in important security parameters, such as entropy, correlation coefficient, key sensitivity, peak signal-to-noise ratio (PSNR), unified average changing intensity (UACI), and number of pixels change rate (NPCR). In addition to providing good defense against brute-force attacks, the high key size of [Formula: see text] further strengthens the system's resilience. To sum up, the BCTMES effectively addresses a number of prevalent risks to picture security and offers a complete solution that may be implemented in cloud-based settings where data integrity and privacy are crucial. This work suggests a promising path for further investigation and practical uses in secure image transmission.
Open access
Chaos-based Image/Signal Encryption
Advanced Steganography and Watermarking Techniques