The human life cannot be sustained without its constant function of heart. A number of variables that put stress on the cardiovascular system, such as weight gain, smoking, and inactivity, have gradually increased the incidence of coronary heart disease in young adults. Due to the increasing rate of heart diseases, electrocardiogram (ECG) data volume is rising rapidly. So, it is necessary for the researchers to protect the copyright of these crucial data and securely transmit it from one end to another. To overcome these issues, this work proposes a system of secure transmission of ECG (ECGSecT) for copyright protection with real-time identity verification of the patient for internet of medical things (IoMT). YCbCr domain processing is applied for watermarking to enhance the performance. R-peaks are extracted before the ECG transmission and used as a watermark image. The patient's Aadhar card is divided into two sections, which are used as separate watermarks. Verification of the identity of patients is done in real-time using a secured hash algorithm (SHA). To balance the properties of proposed framework effectively, reference less fuzzy inference system (FIS) is used by taking the naturalness image quality evaluator (NIQE) and perception-based image quality evaluator (PIQE) as the input. The percentage improvement in imperceptibility is 12.94%. The proposed technique shows the higher resilience and visual similarity in comparison with existing techniques. So, the presented work can effectively be used for copyright and integrity protection along with IoMT-based real-time authentication.

Novel use of a hash-based tokenization for sharing sickle cell disease data without sharing protected health information.

Hardware-level security is crucial for establishing trust in the rapidly expanding Internet-of-Things (IoT) and edge computing systems. A promising approach employs physical unclonable functions (PUFs) which leverage intrinsic process variations to generate unique and irreproducible identifiers. However, conventional silicon-based PUFs often suffer from limited entropy and lack of reconfigurability, becoming vulnerable to machine learning attacks. Here, we present an optically reconfigurable PUF based on a 64-cell array of five-stage ring oscillators fabricated from wafer-scale monolayer MoS2. The system exhibits spectrally selective frequency shifts under red, green, and blue (RGB) illumination, establishing a dynamic optical entropy dimension that enables on-demand, reversible rekeying without hardware modification. We develop a robust key-generation pipeline combining within-chip normalization, random-projection q-ary quantization, and the Secure Hash Algorithm 256 (SHA-256) privacy amplification, followed by hash-based message authentication code (HMAC)-based key derivation. The resulting keys demonstrate near-ideal uniformity (~50%) and inter-device Hamming distance (~0.677 at q = 3, 39 ~ 0.761 at q = 4), while remaining resilient to advanced machine learning attacks (≤ 52% accuracy). We further demonstrate image encryption and authentication with noise-like ciphertexts and reliable tamper detection. This work introduces a promising class of material-intrinsic, optically addressable security primitives for trusted edge computing applications.

Cloud-based storage has become a widely adopted solution for managing and sharing digital data due to its flexibility, scalability, and cost efficiency; however, it introduces critical security challenges such as unauthorized access, data leakage, and weak authentication mechanisms. Traditional cloud systems often rely on password-based authentication and server-side encryption, which remain vulnerable if the infrastructure is compromised, potentially exposing sensitive information. To address these limitations, this work proposed a secure cloud file storage and sharing model that emphasized robust data protection and controlled accessibility. The system incorporated Multi-Factor Authentication (MFA), where users authenticated using a combination of passwords and One-Time Passwords (OTP) delivered via Simple Mail Transfer Protocol (SMTP), thereby enhancing login security. For data protection, Advanced Encryption Standard–Galois/Counter Mode (AES-GCM) was employed to encrypt files efficiently, while Rivest–Shamir–Adleman (RSA) was utilized for secure key exchange, ensuring that encryption keys remained protected. All files were encrypted before storage, eliminating the risk of plaintext exposure. Additionally, Access Control Lists (ACL) mechanisms were implemented to enable secure file sharing among authorized users only. To ensure data integrity, Secure Hash Algorithm (SHA-256) hashing was applied during file upload, allowing verification of file authenticity and detection of tampering. Files were decrypted only after validating access permissions. Furthermore, the system maintained detailed activity logs, ensuring traceability and accountability.

The paper investigates the influence of cryptographic hash function architecture on their cryptographic strength. The main focus is on a comparative analysis of the classical Merkle–Damgård architecture used in the SHA-2 family and the Sponge architecture implemented in the SHA-3 standard. It is shown how the design features of the Sponge architecture, in particular the division of the internal state into speed (rate) and capacity parts, provide an increased margin of cryptographic strength and ensure low vulnerability to the inherent Merkle–Damgård constructions, including the message extension attack. The possibility of estimating the dispersion index for attributing a hash function to a cryptographic type has been confirmed. At the same time, the question remains about the unambiguity of the correspondence between theoretical statistical indicators of the quality of hash functions. The only known indicator of the quality of hash functions is based on the variance indicator and unambiguously shows only whether a particular hash function belongs to cryptographic or non-cryptographic. At the same time, it has been confirmed that the χ² test, as a “bias detector” can prove that the hash function is hack-resistant with high probability. But the question remains about the unambiguity of the correspondence between theoretical statistical indicators of the hash functions quality.Received 2026-03-19Accepted 2026-04-13

Urban traffic management and public safety increasingly rely on real-time monitoring of traffic and environmental events. Traditional detection methods, manual surveillance, human observation, and conventional sensors suffer from limited scalability, delayed reporting, and human error, leading to inefficient interventions. To address these challenges, this research proposes an automated audio-based classification system for urban traffic and acoustic events. The system utilizes advanced Machine Learning (ML) and Deep Learning (DL) techniques to analyze urban audio signals and classify them into categories such as accidents, honking, traffic congestion, and crime-related sounds. At its core, the model employs Transformer Encoder for Representations of Audio (TERA) for feature extraction, which captures temporal and spectral patterns and converts them into high-dimensional embeddings. These embeddings are then fed into supervised classifiers, including Categorical Boosting (CatBoost), Histogram Gradient Boosting (HGB), Extra Trees Classifier (ETC), and the proposed Tree-based Generalized Additive Model (TGAM). Experimental results show that TGAM outperforms baseline ensemble models, achieving macro-average Precision, Recall, and F1-score above 90% on a balanced dataset. The system also integrates visualization tools such as confusion matrices, Receiver Operating Characteristic (ROC) curves, and waveform overlays for interpretability. Additionally, a Tkinter-based Graphical User Interface (GUI) is developed with role-based access. Administrators manage data and model training, while users perform real-time predictions. Security is ensured using TinyDB with Secure Hash Algorithm 256-bit (SHA-256) password hashing.

Community support programs may struggle with issues such as transparency, mismanagement of funds and visibility of transactions to the public. Centralized donation platforms may not offer immutable records and real-time traceability of financial contributions, which may result in a deficit of trust between donors and beneficiaries. This paper introduces a Decentralized Impact Tracking System for Community Support Programs which uses a custom-built blockchain architecture to provide transparent and tamper-resistant recording of funding activities. The system is based on three main roles, i.e., the beneficiary, the donor, and the administrator. Beneficiaries make funding requests that include details of the project, which are recorded in the form of transactions on the blockchain. Donors choose verified projects and send funds, creating blocks of new data that are linked up by a cryptographic process using a Secure Hash Algorithm 256. A simplified version of the Proof-of-Work mechanism is implemented to ensure that blocks are kept intact and can't be altered by anyone unauthorized to do so. The administrator validates and approves requests using a dashboard without making any changes to the immutable ledger. The system combines a web-based interface that has been developed with the use of the programming languages: Html, CSS, and Java Script, a backend which is provided by the open-source software: Flask and database supported authentication. The end result is a transparent audit trail in which all approved programs, transaction histories and funding progress are all available to the public. The proposed framework is an attempt to provide a structured and accountant model for decentralized donation tracking that can be deployed at the academic and prototype level.

Although quantum key distribution (QKD) provides information-theoretically secure keys, a significant gap exists between its relatively low key generation rate and the high-speed demands of classical optical communication. To address this challenge, this paper proposes a stream cipher encryption scheme based on QKD and Secure Hash Algorithm 256 (SHA-256). Core to the scheme is an innovative group-wise dual-randomized affine construction. Integrated with configurable grouping and parallel processing, this mechanism applies a linear mapping defined by dynamic initial vectors (IV) and variable full-domain strides to each data group. This approach achieves deep orthogonalization of the hash input space while preserving architectural parallelism. Simulation results demonstrate that the scheme achieves high-strength security protection while ensuring real-time performance of the communication link. Specifically, statistical analysis confirms that the ciphertext exhibits high entropy and negligible autocorrelation, alongside high key sensitivity. The scheme expands the computational search space beyond the conventional 2256 bound, effectively countering pre-computation attacks.

<p>Wireless sensor networks (WSNs) are susceptible to a variety of attacks, such as data tampering attacks, blackhole attacks, and grayhole attacks, that can affect the reliability of communication. We proposed a reputationenhanced two-way hybrid algorithm (RCHA) that uses cryptographic hash functions and reputation-based trust management to detect and de-escalate attacks accurately. The RCHA algorithm implements two hash functions RACE integrity primitives’ evaluation message digest (RIPEMD) and secure hash algorithm (SHA-3), to initiate the integrity check for the entire packet sent across the network. Every node in the WSN tracks a reputation score for each neighbor the node is connected to, and this score is dynamically updated based on the behavior of each neighbor. If a neighboring node’s reputation drops below a threshold, the node is sent a maliciousness designation. At that time, the node will broadcast an alert message to its neighboring nodes and begin to reroute its data through one of its trusted neighbors to ensure the reliability of the communication. The simulation results reported that the RCHA algorithm improved the accuracy of the attack detection rate and the number of packets delivered compared to traditional attack detection methods. The RCHA algorithm was able to maintain low computational and energy overhead for the WSN, making it an attractive option for a resource-constrained application in a WSN. Given the trends towards more collaborative networks, the reputation mechanism in the RCHA algorithm improves the overall reliability and capabilities of the WSN, regardless of adversaries.</p>

Abstract With the increasing scale of global data transmission, to meet the security data communication needs of the Internet of Things and 5G era, and to address traditional encryption algorithms being prone to cracking and having unsatisfactory communication efficiency, a new encryption algorithm - Advanced Encryption Standard/Secure Hash Algorithm 256-bit (AES/SHA-256) is proposed. The new algorithm optimizes the instantaneous key preprocessing process by introducing the Secure Hash Algorithm 256-bit (SHA-256), outputs the Proxy Re-Encryption (PRE) value, and generates the instantaneous key using PRE. Subsequently, the instantaneous key is introduced into the Advanced Encryption Standard (AES) to construct a more secure dynamic encryption framework. The results showed that the key preprocessing and key generation took 700 μs and 1,010 μs, respectively. The algorithm encryption and decryption processes took 1,000 μs and 800 μs, respectively. The highest number of request processes per second was 380, and the response time was 3,000 μs under a load of 50 users. The AES/SHA-256 performs better than other comparison algorithms. The application test results show that the algorithm has strong instantaneous dynamics and meets the requirements of information security transmission. The AES/SHA-256 encryption algorithm has positive significance for supporting the security of the digital economy ecosystem.

Securing visual information against sophisticated cyber threats remains a core challenge in modern cryptography because many existing chaos-based image encryption schemes suffer from low key sensitivity and static substitution. To overcome these intrinsic limitations, this study develops a multistage image encryption framework by synergistically fusing the Lorenz chaotic system, Secure Hash Algorithm 256 (SHA-256), and Discrete Time Quantum-inspired Walks (DTQWs). The chaotic Lorenz system yields highly sensitive diffusion sequences via bitwise modular operations, whereas the DTQW dynamically constructs plaintext-dependent Substitution Boxes (S-Boxes) and thereby reinforces confusion to minimize statistical predictability. The SHA-256 hash introduces a session-dependent quantum coin rotation parameter to ensure dynamic evolution with intrinsic plaintext sensitivity during the encryption process. Extensive simulations demonstrate outstanding security performance of the proposed scheme: near ideal entropy value of 7.9999, the Number of Pixels Change Rate (NPCR) and the Unified Average Intensity Value (UACI) rates of 99.6 % and 33.5%, correlation coefficients close to zero, and high decryption reconstruction fidelity with Peak Signal to Noise Ratio (PSNR = infty) and Normalized Correlation Coefficient (NCC = 1) for lossless recovery in our python based-evaluations. Compared with other state-of-the-art chaotic and quantum-inspired encryption techniques, the proposed framework offers superior randomness, a good diffusion-confusion balance, and robustness against statistical and differential attacks. Thus, it is a promising candidate for secure image communication and high-assurance data protection in next-generation multimedia systems.

The Secure Hash Algorithm SHA-256 and SHA-224 are widely used for software integrity, digital signatures, and blockchain across embedded and edge platforms. Prior RISC-V accelerators still struggle to achieve low cycle counts and high system throughput on long message streams. This paper proposes a hardware-efficient RISC-V accelerator with low-latency SHA instruction extensions, named SHA-RV, to reduce cycles and improve end-to-end performance. SHA-RV integrates three optimizations: a high-bandwidth BufferSet for continuous data supply, a four-stage pipelined SHA core, a system-level double-buffering pipeline, and an FSM-orchestrated BufferSet mapping. Implemented on a Xilinx ZCU102 system on a chip, SHA-RV operates at up to 300 MHz and uses 3,146 flip-flops, 5,175 lookup tables, and 15 block RAMs. On 64-byte blocks, SHA-RV completes a block in 257 cycles, improving over related RISC-V designs by between 9.7 and 134.9 times, while reducing logic resources versus the ISOCC 2024 design by 89.4 percent in flip-flops and 85.2 percent in lookup tables. At the system level, SHA-RV achieves a throughput of 599 megabits per second and an energy efficiency of 798.7 megabits per second per watt under a real-time dynamic power assumption of 0.75 watts, outperforming representative CPUs by between 61 and 454 times in energy efficiency. These results show lower latency and superior hardware efficiency relative to prior work.

Abstract. In India, land ownership disputes remain a major source of litigation, often resulting from fragmented records, lack of transparency, and outdated administrative processes. This study explores the potential of geospatially enabled blockchain technology to transform land administration into a secure, efficient, and trust based system. By combining the immutability and decentralization of blockchain with the spatial precision of geospatial data, the research proposes a digital framework that enhances the integrity of land transactions and builds stakeholder confidence. The methodology follows a modular system development approach using both software and database life cycle models. Through fact finding, stakeholder interviews, prototyping, and interface development, the system was designed to accommodate various users buyers, sellers, inspectors, and administrators. Key features include cryptographic public private key generation and secure hashing algorithms for transaction protection. A functional prototype was developed using Java and MySQL, integrating GIS capabilities and smart contracts to automate processes and ensure spatial traceability. The system’s performance was assessed based on its completeness, usability, and security. Results showed that the blockchain ledger enabled real time synchronization and minimized the risk of fraud, tampering, or duplication. Incorporating spatial data allowed for visual verification of land parcels and ownership histories, improving reliability for both citizens and government agencies. This research demonstrates how integrating geospatial intelligence with blockchain can modernize land governance, reduce bureaucratic delays, and foster a more transparent and citizen centric system. It presents a promising direction for high performance, scalable digital infrastructure in rapidly developing regions.

Routing in Wireless Sensor Networks (WSNs) is highly vulnerable due to the unreliable wireless medium and limited node resources. Routing attacks can severely degrade network performance. This paper proposes a Robust Security system using Reinforcement Learning (RSRL) and the Secure Hash Algorithm 512 (SHA-512) for secure and efficient routing in WSNs. The primary objective of the RSRL mechanism is to detect malicious nodes and enhance system security. In the RSRL mechanism, the Base Station (BS) performs aggregator verification using SHA-512 to ensure data integrity without burdening low-power sensor nodes. A Reinforcement Learning (RL) agent, executed at the BS, dynamically learns optimal policies to detect malicious sensor nodes based on node Response Time ( ), Consumed Energy ( ), and Loss Ratio ( ). The RSRL system selects reliable nodes for route selection to improve routing efficiency. The proposed RSRL model is implemented in Network Simulator 2.35. Simulation results demonstrate a 26.44% improvement in Packet Forwarding Ratio ( ) and 95% detection accuracy compared to a conventional secure routing mechanism. The results confirm that RSRL effectively mitigates routing attacks while maintaining high network performance.

Nowadays, communication can be conducted at high speed and conveniently through computer networks. In addition, devices in network systems can store data for extended periods. However, communication or storage over the network may lead to security issues or loss of data integrity. Therefore, data security mechanisms should be used to verify and maintain confidentiality and integrity. This research aims to evaluate which algorithm can verify data integrity and identify message authors in the least amount of time. The algorithms studied are Rivest–Shamir–Adleman (RSA), Hash-based Message Authentication Code–Secure Hash Algorithm 256 (HMAC-SHA256), HMAC-SHA384, and HMAC-SHA512, all of which verify data integrity and authenticate message authors. We compared the performance of all algorithms using ten different data sizes ranging from 100 to 1000 MB, with twenty datasets for each size, and evaluated their throughput and bandwidth. The results show that the HMAC-SHA256 algorithm requires the least execution time and therefore demonstrates the highest efficiency. In addition, the algorithm becomes more efficient as the data size increases, followed by HMAC-SHA512, HMAC-SHA384, and RSA, respectively. In future work, studying other algorithms that are capable of verifying data integrity and sender authenticity, such as digital signatures using RSA, Elliptic Curve Cryptography (ECC), and Galois Message Authentication Code (GMAC), or developing applications using HMAC-SHA256 for data integrity and sender authentication, will provide further insights into selecting the most appropriate algorithm for specific applications.

Cloud-based document storage offers significant flexibility but faces security challenges such as the risk of data leaks and illegal modifications. The study proposes a cryptographic framework using a combination of Advanced Encryption Standard (AES)-256 for confidential encryption and Secure Hash Algorithm (SHA)-256 for cloud storage-based document integrity verification. The system was developed with an experimental approach, implemented in application prototypes, and tested on a wide range of file sizes from as small as < 1 mb, 10 mb to 100 mb showing greater efficiency than Rivest-Shamir-Adleman (RSA) and elliptical curve cryptography (ECC). To improve security, a distributed key management scheme and password-based user authentication were added. The encryption system will be tested on Google Drive, One Drive, and mega cloud platforms and evaluated through a series of performance and security tests combined with on-premises personal computer (PC) systems. This framework provides a practical solution for secure document storage in the cloud with a balance between security, performance, and ease of use. This research reinforces the urgency of applying modern cryptography in dealing with the risk of data leakage in public cloud services, and can be adopted as a security and efficiency model and solution for individuals, as well as government and private offices that use cloud storage as a storage base for important documents such as Decrees, Securities, certificates, diplomas and other important data

To address the security of digital images, this paper proposes a novel image encryption algorithm based on a six-dimensional memristive chaotic system. First, the algorithm uses the Secure Hash Algorithm 256 (SHA-256) to generate a hash value, from which the initial dynamic key is derived. Next, it integrates Zigzag scrambling, chaotic index scrambling, and diffusion operations to form an encryption scheme with multiple rounds of scrambling and diffusion. In this framework, after each encryption operation, a part of the dynamic key is changed according to the input parameters, and the six-dimensional memristive chaotic system continues iterating to generate the pseudo-random sequence for the next operation. Finally, the proposed algorithm is evaluated using indicators including information entropy, histograms, the Number of Pixels Change Rate (NPCR) and Unified Average Changing Intensity (UACI), encryption time, and so on. The results show that the information entropy of the encrypted image reaches 7.9979; its Chi-square statistic is 186.6875; the average NPCR and UACI are 99.6111% and 33.4643%, respectively; and the encryption time is 0.342 s for the 256 × 256 Cameraman image. These indicate that image encryption is not only effective in encrypting images but also resistant to many conventional attacks.

Digital transformation of Health Information Systems (HIS) in developing countries introduces significant vulnerabilities in data security, like data tampering, lack of transparency and lack of trust among stakeholders due to the centralised nature of these HISs, which in turn hinders effective healthcare delivery. Blockchain technology, with its decentralised, immutable, and transparent nature, offers a promising solution to fortify HIS against these challenges; however, its adoption feasibility in contexts like Tanzania remains underexplored. This study aimed to assess the security vulnerabilities within the existing HIS at Temeke Referral Hospital, Dar es Salaam, Tanzania, evaluate the feasibility of integrating a permissioned Hyperledger Fabric Blockchain Network (HFBN) in the existing HIS, develop HFBN prototype and evaluate performances of its two consensus protocols (Raft and PBFT (Practical Byzantine Fault Tolerance)) in terms of Transaction Throughput (TT) and Transaction Latency (TL). A quantitative research approach was employed to collect and analyse data, with quantitative data on security challenges and feasibility being gathered via structured questionnaires with 28 healthcare professionals, IT staff, administrators and managers and analysed via Descriptive Statistics and Inferential Statistics methods, while performance results (TT and TL) were gathered through testing experiments on a developed HFBN prototype. Secure Hash Algorithm 256 (SHA 256) was used to ensure immutability of transactions, while Elliptic Curve Digital Signature Algorithm (ECDSA) was used to ensure authenticity of transactions in the developed HFBN. The findings revealed Raft consensus protocol has better performance with a higher TT of 693 transactions per second (TPS) and a lower TL of 1.8 seconds compared to PBFT, which achieved a TT of 150 TPS and a TL of 2.1 seconds, concluding that Raft is better suited than Raft in practical deployment of the developed HFBN. The findings on security vulnerabilities revealed that the existing HIS exhibited moderate security, with significant concerns regarding staff training and inconsistent audits. Also, stakeholders strongly believed in blockchain's potential to enhance security. Major barriers for adopting the blockchain technology included a lack of technical expertise, financial constraints and infrastructural readiness. Blockchain technology presents a viable solution for strengthening HIS security at Temeke Hospital. However, successful implementation is contingent upon addressing key resource constraints through phased deployment, targeted training programs, and strategic investment. This study provides a scalable framework for similar healthcare institutions in Tanzania and other resource-constrained environments.

The Internet of Things (IoT) generates massive volumes of patient and healthcare data every day. Providing the required accuracy for data classification, processing time, and analyzing the vast volumes of data from IoT devices and sensors are said to be the main challenges in IoT. Cloud computing is widely utilized as the foundation for the technologies required to secure healthcare. The healthcare industry has the most promise for blockchain technology since it can be used to integrate fragmented systems, the standard of electronic medical records should be raised, and take a more patient-centric approach to healthcare systems. The objective is to protect medical data, enable patients to use it to support their medical care, and provide reliable consent protocols for data exchange between various institutions and apps. Provide a blockchain-based architecture that verifies user identity using the Secure Hash Algorithm (SHA256) and Proof of Stake (POS) cryptography consensus technique to guarantee EHR sharing across many electronic healthcare systems.In this study, we assessed the performance of our proposed architecture using several metrics, and found that blockchain is a reliable security solution for the upcoming IoT network.

In this paper, we present our own developed programming which helps to generate a sponge-based function while avoiding any call from hashing libraries. Then, we try to implement it in a blockchain signature by getting inspired from Keccak methods such as the recently inextinguishable Secure Hash Algorithm 3 (SHA-3), but before this, we note that our main contribution here, is about introducing the Grendel permutation instead of the Keccak one as they both rely on sponge-based procedures, but the shuffling step is different. In fact, even our Legendre symbol considered here, extends the Euler criterion that is restricted to prime field, to the cases of the group of invertible elements Z/pqZ. To the best of our knowledge, this is the first time that such an approach is used in blockchain signature.