Multi-cloud computing is becoming a prominent paradigm to improve scalability, flexibility, reliability and costeffectiveness by leveraging services from multiple cloud providers. But distributed resource management with strong security is a big challenge in multi-cloud scenarios, which are heterogeneous and dynamic. This review paper provides an all inclusive overview on various multi-cloud architectures, deployment models,resource allocation techniques, optimization methods, and security assurance mechanisms. It covers the major resource allocation strategies such as provisioning, scheduling, load balancing, resource scaling and intelligent optimization through machine learning and metaheuristicalgorithms to optimize resource utilization and Quality of Service (QoS). Additionally, the article delves into significant security methods for protecting decentralized cloud systems, including authentication, authorization, encryption, intrusion detection, trust management, and zero-trust designs. Also, through the comparison of the most recent literature, the current research trends, challenges and limitations for optimizing resources while keeping security in mind are pointed out. According to the review, combining AI-powered optimisation with sophisticated security frameworks has the potential to enhance the performance, resilience and reliability of multi-cloud environments. Last but not least, the paper outlines future research avenues for explainable AI, federated learning, blockchain-based trust management, energy-efficient resource allocation, and autonomous cloud orchestration to enable secure, scalable, and sustainable next-generation multi cloud computing environments.
The rapid growth of digital education and online recruitment has significantly increased the demand for reliable academic credential verification. Conventional certificate verification methods are often centralized, time-consuming, and susceptible to document forgery, unauthorized modification, and administrative delays. To address these challenges, this paper presents a Blockchain-Enabled Decentralized Framework for Secure Academic Certificate Issuance and Real-Time Verification. The proposed framework utilizes Ethereum blockchain technology through Solidity smart contracts to establish an immutable and transparent repository of certificate records, ensuring that issued credentials cannot be altered without detection. A SHA-256 cryptographic hashing mechanism is employed to generate unique digital fingerprints for each certificate, while Firebase Authentication and Cloud Firestore provide secure identity management and efficient off-chain metadata storage. The user interface is developed using React.js, enabling educational institutions to issue certificates and allowing employers, universities, and other stakeholders to verify credentials instantly through a simple web-based platform. During verification, the system recomputes the certificate hash and compares it with the blockchain record to detect tampering and validate authenticity in real time. Experimental evaluation on a local Ethereum network demonstrates reliable certificate issuance, rapid verification with sub-second response times, secure transaction handling, and effective resistance against certificate forgery. The proposed framework enhances transparency, trust, and operational efficiency while minimizing manual verification efforts. Furthermore, its modular architecture facilitates future migration to public blockchain networks and decentralized storage platforms, making it suitable for scalable deployment across educational institutions and digital credential ecosystems.
Cloud-based academic environments such as Learning Management Systems (LMS), Open Journal Systems (OJS), institutional repositories, and web applications face increasing cybersecurity challenges due to heterogeneous users, distributed services, and extensive exposure to public networks. Existing security approaches remain fragmented, where machine learning focuses on threat detection, Zero Trust Architecture (ZTA) emphasizes access control, and blockchain is primarily used for secure logging. The lack of integration among these components limits the ability of security systems to adapt dynamically to evolving cyber threats. This study proposes an Adaptive Cybersecurity Framework (ACF) that integrates unsupervised machine learning-based anomaly detection, a risk-based Zero Trust Policy Engine, and blockchain-based immutable audit logging within a continuous adaptive feedback loop. The framework was evaluated using 450,000 anonymized HTTP and Web Application Firewall (WAF) events collected from a multi-domain academic cloud environment consisting of LMS, OJS, repositories, and supporting web applications. The analysis revealed structured and repetitive attack behaviors dominated by automated endpoint probing and cross-domain propagation patterns, indicating ecosystem-level security threats. The proposed risk assessment mechanism demonstrated effective alignment between anomaly detection and policy-based decision making. Experimental results achieved an AUROC of 0.7296 for risk-based threat detection while maintaining an average decision latency of approximately 11 ms, indicating suitability for real-time deployment. Blockchain integration further provided verifiable, tamper-resistant audit trails for mitigation actions and policy enforcement activities. This study contributes an ecosystem-aware adaptive cybersecurity paradigm that bridges threat detection, policy enforcement, and auditability through a unified security architecture for Academic Cloud Environments.
We introduce NTRU-VRF, the first verifiable random function (VRF) constructed directly from the NTRU lattice hardness assumption, and instantiated concretely using the NIST-standardized Falcon-512 (FN-DSA) signature scheme. A VRF is a pseudorandom function that produces a publicly verifiable proof of correctness for each output. All currently deployed VRFs (IETF RFC 9381, Algorand, Ethereum) rely on elliptic-curve assumptions broken by Shor's algorithm. Prior post-quantum VRF constructions either require only a few-time security guarantee (Esgin et al., ePrint 2020/1222), rely on symmetric primitives that lack a worst-case lattice hardness reduction (Buser et al., ePrint 2021/302), or are based on Module-LWE/Module-SIS rather than NTRU. No prior work constructs a many-time, lattice-based VRF from NTRU hardness with a formal security proof. Our construction exploits a fundamental and previously unformalized property of Falcon's deterministic signing mode: for any fixed public key and input, there exists exactly one valid short-norm signature. This unique-signature property is the key structural feature that transforms a lattice signature into a VRF. We prove three theorems: Uniqueness: For any input, the NTRU-VRF output is unique. This follows directly from the unique-short-coset-vector property of the NTRU lattice. Pseudorandomness: If the Short Integer Solution (SIS) problem on NTRU lattices is hard and the hash function is modelled as a random oracle, then the VRF output is computationally indistinguishable from a uniformly random value. Provability: The Falcon signature is an efficient, publicly verifiable proof, checkable by any party holding the public key. As a concrete application, we define PQ-Sortition, a post-quantum proof-of-stake leader-election protocol that replaces ECVRF-based sortition with our NTRU-VRF construction. We provide the entropy-chain design, stake-weighted win condition, adaptive liveness mechanism, equivocation slashing, and a formal security analysis of the resulting consensus protocol. Instantiated with Falcon-512, NTRU-VRF achieves a VRF output of 32 bytes, a proof size of <= 666 bytes, evaluation time of ~0.8 ms, and verification time of ~0.1 ms on standard hardware—significantly outperforming all existing post-quantum VRF constructions and making it the first many-time, compact, lattice-based VRF suitable for high-throughput blockchain consensus.
Modern information protection methods are primarily focused on increasing computational complexity: it is assumed that a task becomes secure if finding the true message requires too many resources. However, virtually all existing models --- from classical cryptanalysis to autonomous AI agents and retrospective analysis systems (Harvest \& Analyze) --- rely on one common assumption: there exists a verification signal that allows distinguishing the true interpretation from the set of false ones. In this work, we present the \textbf{HYBRA MIRAGE} storage architecture, which is based on a different problem formulation. Instead of increasing computational complexity, we propose to eliminate the very criterion of truth upon which directed search is based. The system constructs a space of plausible interpretations and physically excludes the possibility of repeated access to the used reference space~$V$: each of its vectors is applied exactly once and then destroyed on both sides. As a result, the function $\mathsf{Assemble}(C,K,p)$ remains deterministic and total, and any valid access parameter produces a formally correct result. Even with full access to the reference space $V$ and the PIN code, an autonomous analytical agent does not obtain a mechanism to confirm that the found interpretation corresponds to the original message: each vector from $V$ was used exactly once and physically destroyed. The $\mathsf{Assemble}$ algorithm is a trade secret and is not available to the analyst. Consequently, knowledge of $V$ without knowledge of the algorithm allows generating $10^{35}+$ equivalent interpretations, but does not allow singling out the single true one among them. The proposed approach does not make brute force computationally impossible; it makes the claim that the found interpretation is precisely the one embedded by the sender unprovable. Increasing computational resources, applying more sophisticated models, or massive enumeration can produce more candidates, but do not create a procedure that allows mathematically justifying the choice of a single true interpretation. For autonomous AI agents, this leads to the disappearance of the verification signal necessary for directed search. The loss function surface degenerates into a plane with zero gradient: no iterative optimization algorithm can converge to the true parameter faster than random guessing. HYBRA MIRAGE does not compete with classical cryptographic algorithms and does not replace them. The architecture serves as an environment model for analyzing the behavior of autonomous agents under conditions of the absence of a reliable verification signal and can be used as an infrastructure layer on top of existing storage methods. The architecture does not eliminate the agent's ability to generate candidates; it eliminates the possibility of using the generation result as proof of achieving truth. The analyst finds themselves trapped in a state of epistemic equilibrium, where truth and hallucination are architecturally indistinguishable from each other.
Educational institutions require secure, transparent, and tamper-resistant systems to manage academic records, examination data, and student results while ensuring accountability and data integrity. Conventional marks management systems primarily rely on centralized databases, making them susceptible to unauthorized modifications, security breaches, limited traceability, and single points of failure. The proposed blockchain-based university student marks management framework utilizes academic information collected from institutional administrative records, including student details, faculty information, academic structures, subject allocations, examination schedules, marks, and result data. The workflow incorporates secure user authentication using SHA-256 hashing, AES-based encryption of sensitive marks data, role-based access control, blockchain transaction validation, and smart contract execution for academic operations. Ethereum blockchain, Solidity smart contracts, Flask, Web3.py, MetaMask, and Ganache are integrated to implement secure record management, immutable storage, result publication, audit trail generation, and academic analytics. Performance evaluation is conducted using blockchain transaction processing, encryption efficiency, data integrity verification, access control validation, audit traceability, and result dissemination correctness. Experimental results demonstrate reliable storage of academic records, secure handling of examination information, accurate result processing, comprehensive audit logging, and effective protection against unauthorized modifications while maintaining complete transaction transparency. The proposed architecture significantly enhances the security, reliability, transparency, and trustworthiness of university examination and academic record management systems.
Digital identity remains structurally rigid when it is bound to provider accounts, mutable handles, single social contexts, and local wallet schemes. This paper defines an accountable hash-anchor tier above wallets and credential schemes. Building on a companion model of legal identity assurance, the tier binds an inert root anchor to an event-backed Entity Actor Identity (EAID) assurance state, supports unlinkable profile anchors for distinct contexts, and lets relying parties evaluate gate-specific assurance-at-time over disclosed independent confirmation-event clusters. The formal model states the identifier and capability separation invariant, defines root and profile anchors, models disclosure and lawful resolution as constraints, and gives a two-layer erasure construction for retained commitments and off-chain personal linkage. It also models trust as a reliance event in which pseudonymous interaction becomes rational when a presentation satisfies the requested gate and recourse can reach the legally relevant imputation point. The result is a scheme-agnostic aggregation layer that complements national wallets, supports natural, juridical, and machine actor constellations, and states conditions under which pseudonymity, lawful access, data erasure, and retention can be jointly satisfied.
Web3Compass is presented as a novel search engine tailored to the decentralized Web, integrating multiple blockchain-based name services (ENS, UNS, BNB NS) and content storage networks (IPFS, Arweave, Swarm). Our work describes a real-time monitoring architecture: blockchain registries are queried continuously for new domain registrations and updates, content hashes (e.g. IPFS CIDs) are retrieved and fetched, and website data is parsed and indexed for keyword search. We emphasize the system’s novelty in unifying diverse name systems and content networks under one private search interface. A comprehensive literature review covers previous decentralized search efforts (e.g. DEWS 1, DeScan 2, Krypton 3), blockchain naming services (Namecoin 4, ENS 5, Unstoppable 6, Space ID’s .bnb 7), and content- addressed storage (IPFS 8, Arweave 9, Swarm 10). We include an architecture diagram and discuss implementation details (event log watchers, IPFS HTTP retrieval, indexing pipeline, privacy layers). Evaluation uses scalability and latency metrics, compares with existing solutions, and includes ethical/privacy analysis (e.g. query privacy via Hexens 11, censorship resistance 4). Our results show that real-time blockchain- based domain resolution is feasible and complements Web3 infrastructure, while highlighting trade-offs in data completeness and user privacy.
The management and transfer of student archives in China constitute are mission-critical administrative processes governed by strict custodial regulations. However, the traditional paper-based "sealed-transfer" model is characterized by significant inefficiencies, risk of data loss, and limited mechanisms for verifying the data integrity during cross-institutional transitions. Although blockchain technology offers potential advantages in auditability and immutability, existing solutions often fail to balance privacy protection with high-performance requirements for large-scale archival data. This study proposes a decentralized, privacy-preserving framework that integrates the FISCO BCOS consortium blockchain, the InterPlanetary File System (IPFS), and Zero-Knowledge Proofs (ZKP). The system employs a multi-group architecture, leveraging IPFS for encrypted off-chain storage and zk-SNARKs generated via Circom to enable integrity verification without exposing sensitive data. Empirical evaluation was conducted using 30 archival samples ranging from 82 KB to 3.1 MB. Results indicate that the Paillier cryptosystem introduces significant performance bottleneck, with encryption latency exceeding one hour for files large than 2.3 MB. In contrast, a hybrid RSA+AES encryption scheme combined with ZKP archives stable, size-agnostic proof generation latency of approximately 850 ms and end-to-end transfer times under 3 seconds. These findings demonstrates that the proposed framework effectively replicates the traditional “sealed-transfer” mechanism through cryptographic means, providing a scalable and regulatory-compliant solution that aligns with the Archives Law of the People’s Republic of China and the Personal Information Protection Law (PIPL). This study provides a visible technical pathway for the digital transformation of national-level educational archive systems.
X3Sync is a research proof-of-concept for federated cloud storage aggregation across multiple free-tier providers (Google Drive, Dropbox, Koofr). Files are chunked, compressed (zstd), and encrypted client-side using AES-256-GCM before distribution. The system introduces a dual-mode decryption architecture: Sovereign Mode, where ciphertext is relayed to the client for local decryption, and Edge Mode, where an ephemeral X25519 key exchange enables worker-side decryption. The backend runs on Cloudflare Workers with Neon PostgreSQL for metadata storage. This paper details the system architecture, security model, provider abstraction layer, and a commutative storage model for heterogeneous provider aggregation.
Abstract: In the era of the digital economy, establishing an efficient and compliant data asset rights confirmation system within scalable distributed infrastructures is of critical importance. However, under heterogeneous distributed ledger environments, data circulation is often trapped in a binary tension between privacy preservation and regulatory accessibility, while facing severe scalability bottlenecks. Existing studies lack a unified solution that simultaneously addresses cross-chain interoperability, post-quantum security, and low-cost verification. To this end, this paper proposes a data asset rights confirmation framework based on hybrid post-quantum zero-knowledge proofs. The framework designs a scalable recursive composition architecture combining Scalable Transparent Argument of Knowledge (STARKs) and Succinct Non-interactive Argument of Knowledge (SNARKs), leveraging off-chain compressed permutation to significantly reduce on-chain storage overhead. In parallel, a light-client-based distributed cross-chain state synchronization protocol and a regulation-friendly privacy auditing module (based on threshold encryption) are constructed to ensure transactional atomicity and conditional auditability during data circulation. Experimental evaluations conducted on two datasets, Ethereum NFT transactions and credit card fraud detection, demonstrate that, compared with cross-chain privacy-preserving solutions such as zkCross, the proposed framework reduces on-chain verification Gas costs by approximately 18.2%, compresses proof size to 0.28 kB, and achieves a peak throughput of 1,618 Transactions Per Second (TPS). Moreover, under controlled experimental conditions, the framework attains an audit success rate of 99.6% with only 14.0% performance overhead. Overall, this study alleviates the long-standing trade-offs among privacy protection, regulatory compliance, and computational scalability, and provides a verifiable technical solution for the interoperability and infrastructure development of next-generation distributed systems.
Pham Van Huong, Nguyen Ngoc Tuyen, D. H. Long, Trần Quốc Toanh · 5 authors
The paper proposes a comprehensive data security model for blockchain-based web applications. This model can be used as a general template for Web3 applications. The model consists of two parts: a blockchain core with integrated database encryption modules, replacing Fabric CA; and an application part that also integrates file encryption, database encryption, and digital signatures. The proposed model was tested on a VBCC management website using Hyperledger Fabric. File and database encryption uses AES, and digital signatures use ECDSA. To improve performance, we also replaced the GolevelDB database management system with LevelDB. Experimental results confirm the accuracy and good performance.
P. Anupama, Akhilandeshwari, Shama Priyanka, Putta Srihari · 5 authors
The increasing digitization of administrative and personal records has created a strong demand for systems that guarantee secure storage, data integrity, and reliable verification of sensitive documents. Conventional document management solutions typically depend on centralized servers, where files are vulnerable to unauthorized modification, loss, or deletion without clear traceability. This centralized model reduces trust, increases exposure to cyber threats, and often requires time-consuming manual verification to confirm document ownership and authenticity. Consequently, individuals and organizations encounter challenges such as document forgery, inconsistent records, unauthorized access, and delays in retrieval, emphasizing the necessity for a more secure and tamper-resistant solution. In traditional vault systems, documents are usually stored as basic files with minimal metadata, lacking cryptographic protection and comprehensive audit mechanisms. Due to the absence of immutability, detecting alterations in stored documents becomes difficult. Additionally, reliance on manual validation processes introduces inefficiencies and a higher likelihood of errors. These drawbacks make centralized systems unsuitable for handling critical records such as legal documents, identity credentials, certificates, and criminal records, which require strict integrity and security measures. To overcome these limitations, the proposed solution combines blockchain technology with a Django-based web platform to establish a decentralized and tamper-proof digital vault. Key document metadata, including ownership information, descriptions, timestamps, and file references, is recorded on the blockchain using smart contracts, ensuring permanent and unalterable entries. The actual files are securely stored on the server, while Web3 enables seamless communication between the application and the blockchain network. Functionalities such as document upload, search, verification, and secure access support complete transparency and data integrity. This framework significantly strengthens trust by preventing unauthorized modifications and maintaining a permanent, verifiable history of all stored documents. By integrating blockchain immutability with an intuitive web interface, the system delivers a secure, scalable, and future-oriented solution suitable for government agencies, legal bodies, and organizations managing sensitive records.
This paper presents a comprehensive analysis of the World Wide Web Consortium (W3C) decentralized identity standards and their relationship to the MF+SO sovereign identity vault architecture. We examine the W3C Decentralized Identifier (DID) Core specification (W3C, 2022), the Verifiable Credential (VC) Data Model (W3C, 2022), and related standards including DID Resolution, DID URL dereferencing, and the Verifiable Credential Proof Formats. The paper provides a taxonomic analysis of DID methods (did:key, did:ethr, did:ion, did:web, did:indy) in terms of their trust assumptions, ledger requirements, latency, cost, and privacy properties. We compare MF+SO's identity model—which uses Ed25519 public keys as self-certifying identifiers with a local hash chain for state verification—against the W3C DID Core model, identifying both alignments and divergences. Key findings include: MF+SO identifiers are functionally equivalent to DIDs but use a simplified resolution mechanism that does not require a distributed ledger or external registry; MF+SO's hash chain audit trail provides state verification properties comparable to DID Document versioning on a ledger; and MF+SO's selective disclosure mechanisms using zero-knowledge proofs (see Paper VII) directly implement the W3C Verifiable Credential selective disclosure and data minimization requirements. We analyze the interoperability implications of MF+SO's architecture, demonstrating how MF+SO DIDs can be registered on external DID methods for cross-system interoperability while maintaining the local hash chain as the authoritative state source. The paper also examines the Verifiable Credential lifecycle within MF+SO: issuance, storage, presentation, and revocation, with attention to the credential schema registry, proof format compatibility (Data Integrity Proofs, JSON Web Signatures), and the holder-binding mechanisms that prevent credential sharing. A comparative assessment evaluates MF+SO against three alternative decentra... Part of The Anticloud research corpus by Lois-Kleinner Alpasan (ORCID: 0009-0009-2233-6107). This work explores cryptography, key management in the context of sovereign AI infrastructure, post-cloud computing architectures, and transparent, blackbox-free systems.
Organizations operating multiple AI systems generate independent cryptographic ledgers that may need mutual verification, cross-referencing, or consolidated audit for enterprise-wide compliance reporting. Cross-chain notarization provides cryptographic evidence that a ledger's state is acknowledged by another independent ledger, enabling distributed audit verification without central coordination. This paper presents the design and analysis of the AIOSS cross-chain notarization protocol, which anchors the hash chain head of one ledger into another by inserting a notarization entry containing the cross-chain proof. We define three notarization modes: unilateral (ledger A notarizes ledger B's state), bilateral (mutual notarization between A and B), and supervised (third-party notarizer with independent proof). The notarization proof comprises a Merkle inclusion proof of the source ledger's state proof within a notarization ledger entry, enabling verification by any party holding both ledger files. We analyze the security of cross-chain anchoring under the common prefix assumption, proving that notarization preserves the integrity of both ledgers. Performance benchmarks demonstrate that notarization completes in under 200 milliseconds for ledgers of up to 1 million entries. We further evaluate the notarization merge operation, which produces a unified ledger from multiple notarized ledgers with cross-reference integrity. The protocol supports regulatory requirements for multi-system audit consolidation under SOC2 reporting and GDPR Article 30 record-of-processing activities. --- Part of The Anticloud research corpus by Lois-Kleinner Alpasan (ORCID: 0009-0009-2233-6107). This work explores hash chain, cryptography in the context of sovereign AI infrastructure, post-cloud computing architectures, and transparent, blackbox-free systems.
This paper examines the cryptographic foundations of audit ledgers, with particular focus on hash chains, transparency logs, and verifiable data structures as implemented in the 01s Sovereign (Kaiman) operating system's .aioss ledger format. We survey the evolution from simple hash-linked data structures to sophisticated transparency frameworks such as Certificate Transparency (CT), CONIKS, and Trillian, and demonstrate how these technologies converge in the 01s Sovereign OS to create an immutable, verifiable record of all system and AI-assisted decisions. Part of The Anticloud research corpus by Lois-Kleinner Alpasan (ORCID: 0009-0009-2233-6107). This work explores api gateway, ai routing in the context of sovereign AI infrastructure, post-cloud computing architectures, and transparent, blackbox-free systems.
This paper presents a comprehensive analysis of zero-knowledge proof (ZKP) systems and their application to privacy-preserving identity management within the MF+SO sovereign identity vault. Zero-knowledge proofs, introduced by Goldwasser, Micali, and Rackoff (1985), enable a prover to convince a verifier of the truth of a statement without revealing any information beyond the statement's validity. We examine three families of ZKP systems in the context of MF+SO's identity assertions: zk-SNARKs (Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge), zk-STARKs (Zero-Knowledge Scalable Transparent Arguments of Knowledge), and Bulletproofs. For each family, we analyze the setup assumptions (trusted setup vs. transparent), proof size, verification complexity, prover computation, and post-quantum security. The paper identifies three canonical use cases within MF+SO: (1) age verification without date of birth disclosure, where the user proves that their age exceeds a threshold without revealing their exact birth date; (2) credential possession proof, where the user proves they hold a valid credential for a resource without revealing which credential among a set they hold; and (3) membership in an allowlist without position disclosure, where the user proves their identifier appears in a list without revealing their position in the list. We present benchmark data for each use case using the Groth16 zk-SNARK (prover time: 1.2 seconds, proof size: 192 bytes, verification: 2.3 ms) and the STARK-based approach using the Winterfell library (prover time: 4.8 seconds, proof size: 48 KB, verification: 8.1 ms). The implementation complexity analysis demonstrates that zk-SNARKs require trusted setup ceremonies but provide the most compact proofs, while zk-STARKs eliminate the trusted setup requirement at the cost of larger proofs. The paper concludes with an analysis of the protocol integration requirements, including circuit compilation for the MF+SO identity predicate lang... Part of The Anticloud research corpus by Lois-Kleinner Alpasan (ORCID: 0009-0009-2233-6107). This work explores cryptography, key management in the context of sovereign AI infrastructure, post-cloud computing architectures, and transparent, blackbox-free systems.
Cloud providers need to report to their customers what carbon emissions have arisen from their use of computing resources, so that customers can include them in their own mandated emissions reporting. At present, these reports are neither verifiable nor audited. We show how a data centre operator can produce cryptographic zero-knowledge proofs to each customer that the emissions reported to that customer are accurate, without the customer being able to learn sensitive information about the data centre operator or other customers. Our approach is scalable, costing a data centre operator with one million customers an estimated $150 USD per month plus $0.01 USD for each customer who requests a verifiable emissions report. For customers, a proof is 37 KiB in size, and verifying it takes less than a second. By making emissions reports more trustworthy, we hope to give companies and policymakers the data they need to push towards decarbonisation.
Dr. B. Indira Reddy, Naga Siva Jyothi Kompalli, Dr. Rohita yamaganti, CH Sai Saketh · 6 authors
The ongoing digital evolution in the healthcare sector has increased the demand for reliable and secure systems to manage medical records. Conventional centralized storage methods are vulnerable to security threats such as data breaches, unauthorized usage, and potential data alteration, which can compromise patient confidentiality and data integrity. To overcome these challenges, this work presents a blockchain-enabled medical record management system designed to provide secure and tamper-resistant data storage. The proposed system is implemented as a decentralized web application, utilizing React.js for the user interface and Web3.js or Ethers.js to enable interaction with the blockchain network. Smart contracts written in Solidity are deployed on the Ethereum platform to handle record management and enforce strict access permissions. User authentication is facilitated through MetaMask, ensuring a secure and decentralized method of identity verification. Healthcare information, including patient records, diagnoses, prescriptions, and treatment details, is maintained on the blockchain to guarantee transparency and immutability. The system empowers patients by allowing them to control access to their data, including granting and revoking permissions for healthcare providers. Tools such as Truffle and Ganache are used during development for efficient testing and deployment. In summary, the proposed solution improves data security, privacy, and accessibility, offering a dependable and scalable approach for managing healthcare records in modern digital environments.
<title>Abstract</title> This study presents a comparative analysis of cloud-native and Distributed Ledger Technology (DLT)-based synchronization models for resilient geospatial data management in multi-cloud environments. With the rising demand for real-time geospatial data in applications such as smart cities, disaster response, and environmental monitoring, ensuring data consistency, availability, and integrity across distributed cloud infrastructures has become increasingly critical. Cloud-native models offer high throughput and scalability through managed replication and consistency protocols but may be limited by eventual consistency and reliance on provider-managed security. In contrast, DLT-based models, particularly those using blockchain, enhance data integrity and auditability through decentralized, tamper-proof synchronization, albeit at the cost of increased latency and operational complexity. To evaluate these trade-offs, we propose a composite performance framework encompassing resilience, synchronization efficiency, and operational cost. Using simulation-based analysis, we assess both models under various failure scenarios and performance conditions. Results highlight the strengths and limitations of each approach and underscore the value of a hybrid model—combining the speed of cloud-native systems with the trust guarantees of DLT—for mission-critical geospatial applications. This research offers practical recommendations for system designers and contributes to the evolving integration of blockchain, cloud, and AI technologies in secure, multi-cloud geospatial infrastructures.
The traditional ways of handling academic credentials are considered inefficient, expensive, and very vulnerable to fraud and data alteration as they rely on single-point databases. To counter these drawbacks, the authors of this paper propose a novel conception relying on blockchain technology with its central traits such as decentralization, immutable state, and cryptographic security. Under such framework, all the academic credentials are stored in a distributed ledger as non-variable and visible entries, where each credential is securely encrypted, stamped with the time of its creation, and linked in an irreversible chain, thus practically eliminating the possibility of their falsification or unauthorized change without the agreement of the entire network. The verification process is decentralized so that employers, educational institutions, and students can instantly and directly authenticate the credentials through the blockchain thereby cutting the intermediaries and considerably shortening the administrative delays and reducing overheads. Moreover, smart contracts contribute to further efficiency by automatically taking care of the issuance, management, and verification of credentials according to the pre-defined rules, thus ensuring consistency and accuracy. However, the system still offers the highest user control and privacy through the provision of tools like digital wallets and decentralized identifiers for the students to own and manage their digital credentials. These tools also give the students power to decide who can access their records and under what conditions. To ensure the integrity and confidentiality of the data, advanced security technologies such as cryptographic hashing and zero-knowledge proofs are deployed while still allowing transparency to the process of verification.
D. Suganya, R Vinaya Kumar, Arulselvy R, Ilakiya J
Digital evidence now plays a major role in criminal investigations, but managing that evidence securely is still a challenge. In many existing systems, records are stored in centralized environments where tracking every action is difficult and unauthorized changes can be hard to detect. When that happens, the reliability of evidence can be questioned during legal proceedings. In this work, we propose a digital forensic evidence management framework that uses decentralized technologies to make evidence handling more dependable. Instead of storing files in a single location, the evidence is encrypted and stored through IPFS, which helps reduce the risk of data loss and unauthorized modification. Every important action performed on the evidence is also recorded on a blockchain using the Proof of Staked Authority consensus method so that investigators can verify the complete history whenever required. To strengthen security further, the XChaCha20 algorithm is used before storage. The system also applies a VGG19based verification method to study printer-related patterns and confirm whether a document is genuine. By bringing together distributed storage, blockchain tracking, encryption, and document verification, the proposed approach offers a practical way to improve the security and trustworthiness of digital forensic evidence.