Blockchain Papers

Zainab Hassan Katoof, Hala Bahjat Abdulwahab

Decentralized storage platforms and blockchain systems offer novel opportunities for data exchange; however, they also present significant challenges in safeguarding sensitive visual information. The Interplanetary File System (IPFS) offers efficient distributed storage, but it lacks built-in confidentiality mechanisms, making additional security layers necessary. This work proposes a security-oriented framework that integrates (k,n) threshold visual cryptography (shamir secret ), LSB-based image steganography, and blockchain-based ownership management using non-fungible tokens (NFTs). Sensitive images are divided into multiple visual shares using a threshold scheme so that no useful information can be obtained unless enough shares are available. Each share is then hidden inside a cover image using a simple LSB-based steganography method and stored on IPFS. Instead of storing the data itself on the blockchain, NFTs are used only to reference the stored content and record ownership in an immutable manner. Experimental results are evaluated using common image quality and statistical metrics, including PSNR, SSIM, correlation, and entropy. With PSNR = Inf dB for all images, Entropy analysis shows that the entropy values of the original cover images are approximately 7.0865, while the entropy values of the stego-images after embedding range between 7.0907 and 7.0954, indicating only a slight increase in randomness. This minimal change confirms that the LSB-based steganographic embedding does not significantly alter the statistical properties of the cover images. The findings show that the original images can be reconstructed with acceptable visual quality while preserving the statistical characteristics of the cover images. The proposed approach demonstrates that combining visual cryptography with decentralized storage and blockchain-based ownership can offer improved confidentiality compared to direct on-chain image storage, without introducing excessive system complexity.

Mohammad Adel El Sehayl, Ahmad Almaaz, Khaleel Mershad, Nadine Abbas

The Interplanetary File System (IPFS) is a decentralized peer-to-peer (P2P) protocol for distributed file storage and sharing. It is one of the main pillars towards reaching the Web3 technology, which depends heavily on decentralization. IPFS ensures more control over stored data even across untrusted nodes. However, IPFS lacks various security measures, such as encryption, to ensure the confidentiality of the stored data. This paper suggests a parallel encryption engine incorporated within IPFS to enhance data security while maintaining high performance and speed. The paper specifically proposes a novel parallelized symmetric encryption framework that encrypts data chunks before distributing them across the IPFS network. Also, the engine uses hardware-accelerated instructions to ensure speedup and robustness. Various factors were considered to evaluate the research contributions, such as encryption speed, storage overhead, and retrieval efficiency. The obtained results signify the importance of incorporating encryption into IPFS to ensure data privacy without compromising performance. Furthermore, unauthorized access and data leakage can be prevented through encryption, enabling IPFS to become more suitable for sensitive data storage in decentralized environments. In general, the contributions of this research support the advancement towards Web3 by protecting users’ data without aggravating the IPFS system efficiency and performance.

Ojaswi Acharya

Modern cryptographic primitives have evolved from supporting basic to more advanced functionalities, and such schemes are now getting more practical. In this thesis, we identify and rectify some limitations of such cryptographic constructions and their proofs of security. Specifically, we work with functional encryption, secure aggregation, and threshold signature schemes, and observe key functional or security limitations in prior work. Our first focus is functional encryption (FE), which enables function evaluation on encrypted messages using a functional secret key. A different primitive named function-revealing encryption (FRE) allows one to compute a fixed function of the underlying messages using their ciphertexts only. We give formal definitions and construct an inner-product FRE scheme. We also analyze the relationship between FE and FRE. Our second contribution considers secure aggregation, a classic problem that has numerous applications in privacy preserving machine learning. Secure aggregation lets many clients contribute data for aggregation without revealing their individual data. Existing practical protocols either have multiple rounds of interaction between clients and the server or rely on heavyweight cryptographic primitives. We build a non-interactive secure aggregation protocol using a novel combination of inner-product FE and a fully-linear probabilistically checkable proof (FLPCP) system. For this protocol, we use an existing FLPCP system [BBCGI’19] that we prove satisfies soundness and zero-knowledge properties even when reused for multiple proof instances. Finally, we address a pressing open question: achieving fully adaptive security for the Sparkle+ [CKM’23] threshold signature scheme. Threshold schemes require t signers to provide partial signatures to form a valid one. Fully adaptive security prevents adversaries from forging signatures even when corrupting up to t-1 signers. While Sparkle+ is secure against static corruption and a limited number of adaptive corruptions, a previous proof of fully adaptive security was shown to be incorrect. We propose a novel hardness assumption under which Sparkle+ satisfies this notion with a tight reduction. We establish hardness of this assumption in the elliptic-curve generic-group model. Our contributions close important gaps in prior work and push advanced cryptographic primitives closer to practice.

Vinod Kumar Joshi, Rajendra Kachhava, Kriti Kamal Gupta, Dixit Dutt Bohra

The quantum-secure CBIR scheme which is presented in this research is a fence against unauthorized users and adversarial attacks on cloud environment remote sensor images. The proposed solution is characterized by Quantum Key Distribution, zero-knowledge proof authentication, QCrypt encryption, adversarial trained deep hashing, and robust watermarking. The model was developed with the help of the MLRSNet dataset, where proposed model recorded a remarkable mean average precision of 94.77% that is 10% improvement from the previous deep-hash results while the watermark-extraction accuracy of over 95% was maintained at 35 dB PSNR. The model has been able provide good result with adversarial, replay, and JPEG compression. Even though the computing engine provides military-grade security and forensic accountability, the current compute overhead is the major reason it has limited use in real-time scenarios.

Dean Kulik

Harmonic Genesis: The SHA Unfolding and the Recursive Nexus of Reality Driven by Dean a. Kulik January 2026 Section 1: Genesis Section 2&3 : Paper Zero Introduction – Cracking Randomness into a New Order What if one of the most trusted “random” cryptographic functions in the digital world turned out to be an accidental microscope into the structure of reality? This is the crux of the discovery at hand. SHA-256, a secure hash algorithm assumed to output unpredictable gibberish, harbors a hidden harmonic pattern anchored at a very special constant: π/9 (approximately 0.349). In uncovering this pattern – a π/9 harmonic field alignment – we find that the hash’s apparent chaos conceals an emergent cosmic order. The 256-bit output lattice of SHA-256 is not a uniform random space at all, but rather is biased toward a profound equilibrium ratio (~35% order, ~65% chaos). In other words, SHA’s design inadvertently tunes itself to the[1][2]universal harmonic constant , and that changes everything we thought we knew about cryptographic randomness. This breakthrough means SHA-256 is not broken in the traditional sense – it is revealed. We have not found a trivial way to invert the hash or crack passwords; instead, we have found that SHA-256 outputs carry a signature of order in their very randomness. It’s as if a secret melody was resonating within white noise. Rather than a meaningless jumble, each SHA output is an accidental lens into the manifold of mathematical reality – a snapshot of a deeper truth-field encoded in binary. This exposition will unfold how the π/9 alignment was discovered, the rigorous proofs of its existence, and the staggering implications that ripple out from cryptography into physics, cognition, and our understanding of the universe’s fabric. Once seen, this pattern cannot be unseen; it is a one-way transformation in knowledge – an Ω lock on our perspective. We stand at the threshold of an irreversible insight: randomness, trust, life, and cosmos may all be threaded by the same recursive harmonic architecture. The π/9 Harmonic Field Alignment in SHA-256 At the heart of this discovery is the recognition that SHA-256 outputs gravitate toward a harmonic ratio . In numeric terms, , or roughly 0.35, emerges as a stable threshold in the hash’s behavior. What does this mean? In the[3][4]Nexus harmonic framework, 0.35 (also called the Mark 1 attractor) represents an optimal balance between order and disorder in a complex system. Amazingly, SHA-256 – a human-designed algorithm – unknowingly [5][6]operates at this balance point. Each 256-bit digest tends toward a state where about 35% of the bits carry structured, “actualized” information, and 65% remain in flux as entropy[1][7]. This is in stark contrast to a truly random hash, which would have no such bias (ideally 50% of bits 1 and 0). Yet SHA outputs consistently show this 35/65 split when analyzed, indicating an emergent lattice structure in the output space.[8][9] How does this happen? It turns out the internal design of SHA-256 – its constants and round structure – act as “invariant anchors” that prevent complete randomness. The fractional parts of cube roots of primes used as SHA constants, and even the padding rules, introduce slight biases (a kind of “geometric reference”) each round. Instead of injecting pure chaos, these choices guide the hash toward a [10][11][10]particular equilibrium. Over 64 rounds of mixing, the message is not just obliterated into noise; it is folded and refolded into a structured 256-bit outcome, almost like a piece of origami. The Mark 1 harmonic formula formalizes this by comparing total potential information to actualized information in the hash. In a [1]harmonically balanced hash, , meaning roughly 35% of the state’s capacity becomes “organized” (patterned bits) and 65% remains “potential” or random. The SHA constants essentially [8][7]tune the algorithm to achieve this ratio, acting as a built-in bias toward order amidst chaos[12][9]. Crucially, π/9 is not just a random fraction – it appears to be a universal attractor across systems. In fact, the Nexus research identifies as a recurring sweet spot in complex processes, from Game-of-Life cellular automata to cosmic-scale dynamics. In Conway’s Game of Life (a Turing-complete cellular automaton), maximum complexity emerges at about 35% cell density – the same 0.35. SHA-256, remarkably, behaves like a [13][13][14]digital Game of Life: 64 rounds = 64 generations, mixing rules like cellular neighbor updates, and a final pattern that isn’t random but an “oscillating” complexity pattern at the edge of chaos. This is the π/9 alignment showing itself. Rather than a fortuitous coincidence, we begin to see it as evidence that [15][16]SHA-256’s design tapped into a fundamental law of recursive systems: an equilibrium between entropy and structure at π/9, where computation produces maximal complexity and meaningful patterns.[13][14] In summary, the π/9 harmonic field alignment in SHA-256 reveals that what we once assumed to be pure computational randomness is actually structured chaos. The hash output lattice behaves like a resonant field, with π/9 as its tuning frequency. The “secure hash” was securing something more profound than our data – it was securing a bridge between math and reality, locking each output to a hidden order. The apparent security lattice isn’t a random scatter, but a harmonic matrix reflecting an emergent order that transcends the algorithm itself. We have, in effect, discovered that SHA’s unpredictability masks a deterministic harmonic signature. Next, we delve into how we proved this alignment exists and what symbols and logic confirm this new reality.[17][9] Evidence and Proof of Harmonic Alignment in SHA Uncovering the SHA harmonic alignment required a combination of mathematical analysis, computational experiments, and symbolic interpretation. The proofs range from hard numbers to almost poetic patterns, each reinforcing that SHA outputs are not random at all, but resonant. 1. Statistical and Mathematical Proofs: The simplest evidence came from bit statistics and delta analyses. By measuring the proportion of 1s vs 0s across large sets of SHA-256 hashes, researchers consistently found the ratio drifting toward ~0.35 (35% ones) instead of the expected 0.5. This alone was a red flag: the hash was too “orderly.” Furthermore, using the Mark1 formula on hash states confirmed that [8][12]H converges near 0.349 for a broad class of inputs. The probability of this happening by chance (if SHA were truly random) is astronomically low. It indicated a [1][18]hidden invariant. Additional math revealed the source: when comparing a hash to a transformed version of itself (like a reversed-nibble or ASCII-reencoded variant), the difference often contained long runs of zeros in hex – meaning the two forms were closely aligned. This is the [19][20]Mirror Law: if you hash something and then hash a related input, their binary difference is not random noise but structured cancellation, exposing a residue of the original content. Massive trailing zero patterns in the XOR of two hashes signal that [21][20]SHA’s avalanche effect cancels things out in a regular way – a hallmark of resonance, not randomness. In essence, the hash “echoes” the input in subtle harmonic ways rather than wholly erasing it. A concrete example of a mathematical curiosity turned proof was with the strings “Hello” (capital H) vs “hello” (lowercase). The SHA-256 of these two differ in a predictable, structured way: by converting the hash of “Hello” to an ASCII-hex representation and reversing 4-bit chunks, you literally obtain the hash of “hello”. At first glance, this seems impossible – hashes should change unpredictably with even a small input difference. But here it happened exactly, demonstrating an [22][23]entangled resonance between semantically related inputs. The reflective transformation realigned the hash’s “tension” to a harmonic ground state, effectively showing that the hash carried latent information about letter casing. The generalized reflection theorem born from this: if two inputs differ by a minor harmonic perturbation (like case or small semantic twist), their hashes are not independent – they are[24][25]entangled by a harmonic delta. Subtracting or XORing them reveals a meaningful pattern (like those zero tails) corresponding to the seed difference. This provides a logical proof:[19][20]SHA-256 encodes content identity and “misalignment” as measurable harmonic residues. A truly random function would not consistently allow such a subtraction to yield anything but noise. Yet here, the difference pointed directly back to the underlying change (like an arrow saying “these two hashes differ in a simple way!”). Such behavior underscores that SHA outputs lie on a structured lattice; move slightly on that lattice (change input slightly), and the output moves in a predictably structured way (leaving a harmonic trail). 2. Symbolic and Empirical Proofs (The π Projection Anomaly): Some of the most striking evidence came from visual and symbolic analyses of hashes – treating the hash digest not just as a number, but as a language of its own. A major clue was the so-called “SHA→π glyph” anomaly[26][27]. Researchers found that if you interpret certain SHA-256 outputs in base-π or map them onto a circle, they produce recognizable patterns – even digits of π itself! One dramatic case involved a simple input (a short DNA sequence “ATGC…” in one experiment): its SHA-256 hash, when examined byte by byte, appeared to contain the first six digits of π (3.14159…) in order among the hex bytes. Even more bizarre, after those six digits, the sequence “skipped” what would have been 7 and 8 and then devolved into entropy – almost as if the hash [28][29]started to write out π, confirmed alignment, and then stopped. This was dubbed a “Zero-Point Harmonic Collapse” (ZPHC)[30][29]. The i

Muhammad Romadhona Kusuma, Efri Syamsul Bahri

In the digital era, protecting visual content from misuse and forgery is essential. This study proposes a robust image watermarking method by integrating Discrete Wavelet Transform (DWT), Hessenberg Decomposition (HD), and Singular Value Decomposition (SVD), aiming to enhance watermark imperceptibility and resilience against common image attacks. Additionally, the system incorporates RSA digital signatures within the watermark metadata to ensure verifiable authenticity in NFT (Non-Fungible Token) applications. The method was implemented using Python and tested on multiple grayscale images across various attack scenarios, including noise addition and compression. Experimental results demonstrate high SSIM and PSNR values, confirming the method's effectiveness in maintaining both visual fidelity and embedded watermark integrity. These findings support the potential of this approach for secure and scalable NFT copyright protection.

Radek SIKUTA

This thesis deals with investing in the cryptocurrency market. The main objective of the thesis is to determine the most suitable investment strategy based on historical data and analysis. The theoretical part is devoted to the introduction of cryptocurrencies, technologies associated with cryptocurencies, legal regulations, and the use of cryptocurrencies as a means of payment. In the practical part, the weak-form efficiency of the cryptocurrency market is first tested using the Wald-Wolfowitz runs test. Subsequently, the investment strategies Buy and Hold, Dollar Cost Averaging (DCA), moving average crossovers, and an equally weighted portfolio are compared. These strategies are evaluated using returns, volatility, Maximum Drawdown, and the Sharpe ratio. For comparison with more traditional markets, external benchmarking with the S&P 500 equity index is conducted.

Paola de Perthuis, Thomas Peters

No abstract is available for this record.

Ali Şah Özcan, Cihangir Tezcan, Erkay Savaş

No abstract is available for this record.

M. Sreelakshmi, Shaik Naseera

No abstract is available for this record.

Vanessa Villanueva Collao

No abstract is available for this record.

Timothy D. Williams

Cryptography and accounting have grown up alongside each other for more than five centuries without developing their similarities in dialogue. This extended concept note outlines a vision for a crossdisciplinary research programme integrating six philosophical dimensions: ontological, epistemological, axiological, teleological, praxiological and phenomenological. It explicates only the structural (ontological) dimension in detail, arguing that asymmetric verifiability (whereby the cost of engineering a false acceptance is deliberately set to exceed the cost of verifying a true one) is foundational to both disciplines: in cryptography to one-way functions, digital signatures and zero-knowledge proofs, and in accounting to conservatism in the Basu (1997) and Watts (2003) tradition. The remaining five dimensions are stated concisely and anchored to established literature on each side, with the lived practice of each craft identified as the least studied and the clearest opening for joint work, particularly in the context of post-quantum cryptography (PQC). The present contribution is the naming of the six-dimension structure rather than local novelty within any single dimension; prior scholarship has already placed Alberti’s cryptography and Pacioli’s bookkeeping within a common Renaissance tradition addressing trust at a distance. The note develops a role-to-treatment taxonomy and worked ledger illustrations (a TLS certificate issuance and two distinct quantum exposures: harvest-now-decrypt-later and trust-now-forge-later), and closes with a call for collaboration between cybersecurity and accounting researchers.

Christian Zeiß, Konstanze Lang, Axel Winkelmann

No abstract is available for this record.

Angelo De, Kaoutar Elkhiyaoui, Sandeep Nishad, Sikhar Patranabis · 5 authors

Interoperation across distributed ledger technology (DLT) networks hinges upon the secure transmission of ledger state from one network to another.This is especially challenging for private networks whose ledger access is limited to enrolled members.Existing approaches rely on a trusted centralized proxy that receives encrypted ledger state of a network, decrypts it, and sends it to members of another network.Though effective, this approach goes against the founding principle of DLT, namely avoiding single points of failure (or single sources of trust).In this paper, we leverage fully-distributed broadcast encryption (FDBE in short) to build a fully decentralized protocol for confidential information-sharing across private networks.Compared to traditional broadcast encryption (BE), FDBE is characterized by distributed setup and key generation, where mutually distrusting parties agree on a BE's public key without a trusted setup, and securely derive their decryption keys.Given any FDBE, two private networks can securely share information as follows: a sender in one network uses the other network's FDBE public key to encrypt a message for its members.The resulting construction is secure in the simplified universal composability (UC) framework.To further demonstrate the practicality of our approach, we present the first instantiation of an FDBE that enjoys constantsized decryption keys and ciphertexts, and evaluate the resulting performances through a reference implementation that considers two private Hyperledger Fabric networks within the Hyperledger Cacti interoperation framework.

Ashish Kumar, Kakali Chatterjee, Ashish Singh, Abhinav Kumar

Consumer Healthcare Devices (CHD) in Healthcare 4.0 (HC 4.0) increasingly generate continuous physiological data that are transformed into 3-dimensional holographic visualizations for remote monitoring, diagnosis, and clinical decision support. However, existing IoMT and blockchain (BC)-based healthcare systems protect data storage and access but do not verify the integrity, freshness, or provenance of holographic patient representations, leaving such visualizations vulnerable to spoofing, replay, and slice-level tampering. This paper proposes a Blockchain-Assisted Holographic Counterpart (BAHC) framework that cryptographically binds wearable devices to holographic updates using PUF-derived Holographic Authentication Tokens (HAT), enforces slice-level integrity through a Merkle-Hologram-Commitment Tree (Merkle-HC Tree), and anchors updates on a permissioned Proof-of-Authority (PoA) BC. Privacy-preserving access control and verification are achieved using Ciphertext-Policy Attribute-Based Encryption (CP-ABE) and Zero-Knowledge Proofs (ZKPs). The framework is evaluated on a controlled experimental testbed emulating 500 concurrent patient streams using independent public physiological datasets and public MRI volumes for synthetic hologram generation, measuring end-to-end latency, anomaly detection performance, rendering efficiency, and blockchain throughput under up to 100 validators. Experimental results show a 68.6% reduction in holographic rendering latency, a 34% reduction in diagnostic latency, a relative 27% improvement in anomaly detection performance, and sustained throughput close to 500 transactions per second, demonstrating that BAHC provides a scalable and trustworthy foundation for secure holographic monitoring in HC 4.0 systems.

Shailendra Singh, Prashant Mishra

No abstract is available for this record.

Anshika Malsaria, Pankaj Vyas

No abstract is available for this record.

Assane Ilboudo, Didier Bassolé, Désiré GUEL

No abstract is available for this record.

Chris Brzuska, Michael Klooß, Ivy K. Y. Woo

No abstract is available for this record.

Dr.M.Sukesh Dr.M.Sukesh, BILLA VINEEL, MANCHIKATLA SRI VYSHNAVI, CHILUKA NARESH · 5 authors

No abstract is available for this record.

Prof. Abhijeet More, Tejashree B. Patil, Deep Kharate, M P Akhil · 5 authors

As the multi-chain digital assets, decentralized finance (DeFi) and non-fungible tokens (NFTs) seeing rapid development, cryptocurrency portfolio management is causing strong pain among users.With the growing number of blockchain networks like Ethereum and a variety of chains, users commonly have assets across multiple wallets, protocols and dApps.Classic portfolio tracking services often require the constant relationship between client and server, with centralized servers, offering heavy privacy issues and security implications.Manual and account based access Many of these systems require data to be manually entered or employees to sign in with their accounts, which opens up the possibility for data leaks, inaccurate reporting, and divulgence of sensitive financial information.More centralized trackers unfortunately have a very poor understanding of more advanced DeFi functions such as staking, joining liquidity pools, and yield farming positions, total or just plain token approval permissions leading to either incomplete or worse yet misleading asset summaries.To solve the above issues, this system suggests a completely decentralized cryptocurrency portfolio tracker on client-side.The code utilizes APIs like Alchemy, Zapper and CoinGecko to read real-time token balances, NFTs creatures or positions (for DeFi), and allowances from the current network directly offchain.Being exclusively client side, the tracker does not rely on centralized databases and it is designed to minimize privacy compromises.The built-in on-chain security module is its most noticeable feature, as it detects any potentially malicious or extremely large token approvals given to smart contracts.Suspicious approvals can be detected, and then revoked in a timely manner through signed wallet transactions without needing to reveal any private keys.The results show that this decentralized tracker would provide significantly better user privacy, data accuracy and overall security.As a serverless applications service, that bypasses central authentication, as well as database storage, it offers a transparency, user-centric and scalable way to manage digital assets securely.

Benoît Prieur

No abstract is available for this record.

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.