Secure Data Storage Research Articles

High‐Isolation Multidimensional Holography Multiplexing in Non‐Interleaved Metasurfaces

AbstractMetasurfaces have revolutionized holography by enabling high‐density channel multiplexing, positioning them as promising candidates for applications in full‐color holographic imaging, optical data storage, and encryption. However, conventional non‐interleaved metasurfaces face limitations in the number of controllable dimensions, restricting the channels available in each dimension. Here, a novel high‐dimensional multiplexing scheme is introduced that significantly enhances both the channel multiplexing capacity and isolation in non‐interleaved metasurfaces. By integrating the Rayleigh‐Sommerfeld diffraction (RSD) formula into the Gerchberg‐Saxton (GS) algorithm and incorporating gradient descent optimization, the approach achieves precise phase profile control across multiple dimensions—extending the controllable parameters to include wavelength, polarization state, and spatial distance. This method enables simultaneous multiplexing of three polarization channels, three wavelength channels, and two focal plane distances, producing a total of 18 distinct, well‐isolated holographic channels with minimal crosstalk. These results showcase the powerful channel multiplexing and isolation capabilities of this non‐interleaved metasurface design, underscoring its potential to advance optical color imaging, secure data storage, and high‐capacity information transmission, thereby contributing to the development of next‐generation intelligent optical devices.

Mapping of Industrial IoT to IEC 62443 Standards

The increasing adoption of the Industrial Internet of Things (IIoT) has led to significant improvements in operational efficiency but has also brought new challenges for cybersecurity. To address these challenges, a number of standards have been introduced over the years. One of the best-known series of standards for this purpose is ISA/IEC 62443. This paper examines the applicability of the ISA/IEC 62443 series of standards, traditionally used for securing industrial automation and control systems, to the IIoT environment. For each requirement described in the ISA/IEC 62443 standards, relevant research on that subject is reviewed and presented in a table-like manner. Based on this table, areas for future research are identified, including system hardening, asset inventory, safety instrumented system isolation, risk assessment methodologies, change management systems, data storage security, and incident response procedures. The focus on future improvement is performed for the area of system hardening, for which research and guidelines already exist but not for the specific area of IIoT environments.

Development of Heuristic Strategy With Hybrid Encryption for Energy Efficient and Secure Data Storage Scheme in Blockchain‐Based Mobile Edge Computing

ABSTRACTInternet of Things (IoT) devices is extensively employed to collect physiological health data and provide diverse services to end‐users. Nevertheless, in recent applications, cloud computing‐based IoT proves beneficial for standard data storage and ensuring high‐security information sharing. Due to limitations in battery capacity, storage, and computing power, IoT devices are often considered resource‐constrained. Consequently, data signing by IoT devices, aimed at ensuring data integrity and authentication, typically demands significant computational resources. Unsafe data storage and high latency are considered as the major issues in the IoT‐based data storage mechanism for duplicating and misusing the information while it is stored in the cloud database. Hence, blockchain technologies are needed to provide high security over the stored data. Hence, the research aimed to implement an efficient blockchain‐based data storage system in mobile edge computing, safeguarding data from unauthorized access. In this approach, it contains four layers that are cloud layer, the entity layer, the block‐chain layer, and the edge computing layer. The user's data are stored in the optimal location in the entity layer, where the data storing location is find out using the proposed Hybrid Battle Royale with Archimedes Optimization Algorithm (HBRAOA). In the edge computing layer, an optimal key‐based homomorphic encryption algorithm using Elliptic Curve Cryptography (ECC) is introduced to encrypt data with the most optimal key, ensuring secure storage. This encryption method leverages the same HBRAOA to enhance the efficiency. Next, the digital signature is demonstrated to give the authorization of the user, and it is distributed to the blockchain layer. Thus, the indexes of the shared data are stored in the blockchain layer to avoid fault tolerance and tamper‐proofing. Finally, the cloud layer receives the valuable encrypted data, and the authenticated users with known encrypted keys are able to access the data by decrypting them. The result analysis shows that the performance of the developed model, which attains 27%, 98%, 35%, and 18% enhanced than Particle Swarm Optimization (PSO)‐ECC, Black Widow Optimization (BWO)‐ECC, Battle Royale Optimization (BRO)‐ECC and Archimedes Optimization Algorithm (AOA)‐ECC. The efficiency of the proposed blockchain‐based mobile edge computing scheme with the optimization strategy is validated by conducting several similarity measures over the conventional methods.

P1009 Enhancing Inflammatory Bowel Disease care: The role of mobile applications in disease management

Abstract Background Managing Inflammatory Bowel Disease (IBD) can be challenging, requiring a careful balance of medication adherence, symptom tracking, and lifestyle adjustments. Mobile applications offer a promising avenue to support individuals with IBD in navigating these complexities. This study investigates the impact of the “My IBD Under Control” mobile application on patient education and self-management. Methods The “My IBD Under Control” app provides a comprehensive suite of features designed to improve patient outcomes. Users can record and monitor symptoms such as abdominal pain, diarrhea, and constipation, enabling early detection of potential flares and timely intervention. Timely notifications help ensure adherence to prescribed treatment plans, improving disease control and reducing the risk of complications. Access to reliable information about IBD, its causes, and management strategies empowers patients to make informed decisions about their health and take an active role in their care. The nearby restroom locator is a valuable tool, especially during flare-ups, providing peace of mind and reducing anxiety. Data on user demographics, app usage patterns, and symptom tracking were collected through the app’s built-in analytics tools. Descriptive statistics were used to analyze user demographics and app usage patterns. Data privacy was ensured through secure data storage and anonymization techniques. Results Since its launch in February 2022, the “My IBD Under Control” app has attracted a significant user base of over 5900 individuals with IBD in Turkey. The user base is predominantly male (58%) with a mean age of 38, while female users (42%) have a mean age of 33. The app’s high interaction rate of 63.4% indicates strong user engagement. Although only 7% of users have specified their IBD type, of those who did, ulcerative colitis was more prevalent (60%) than Crohn’s disease (40%). The higher engagement rate among younger users suggests that this demographic may be more receptive to digital health tools. Figure 1 illustrates the growth of the app’s user base since its launch in February 2022. The figure shows a significant increase in the total active user count and new users. Conclusion Mobile applications have the potential to revolutionize IBD care by empowering patients to take an active role in their health. The “My IBD Under Control” app offers a comprehensive suite of features to improve patient outcomes. Further research is needed to explore such apps’ long-term impact and identify strategies to optimize their use. By incorporating innovative technologies such as artificial intelligence and machine learning, future mobile health applications can enhance patient care and improve the quality of life for individuals with IBD. References Wang R, Li Z, Liu S, Zhang D. Global, regional and national burden of inflammatory bowel disease in 204 countries and territories from 1990 to 2019: a systematic analysis based on the Global Burden of Disease Study 2019. BMJ open. 2023;13(3):e065186.

Cryptography in iOS: A Study of Secure Data Storage and Communication Techniques

The study analyses the use of cryptography on iOS devices, especially exercising an understanding of enhanced data storage and protected communication. As the issue of privacy and security of applications on the handler increasingly comes to the forefront, iOS uses different cryptographic algorithms in order to ensure that the user’s private data, including passwords and other personal information, the channels of communication, etc. This research was based on the assessment of data encryption techniques of data at rest; data in transit, and the security of communication using SSL/TLS. A part of the iOS cryptography is also revealed to have certain weaknesses and all possible directions of its development as well. Through such cryptographic techniques, the research intends to discuss the security practices of iOS and also reveal the advantages/shortcomings of the current security measures. The features discovered are intended to help developers, security specialists, and users to know more about effective usage of cryptographic systems in increasing the safety of mobile devices and reduction of information risks on the basis of iOS.

Empowering drones in vehicular network through fog computing and blockchain technology.

The performance of drones, especially for time-sensitive tasks, is critical in various applications. Fog nodes strategically placed near IoT devices serve as computational resources for drones, ensuring quick service responses for deadline-driven tasks. However, the limited battery capacity of drones poses a challenge, necessitating energy-efficient Internet of Drones (IoD) systems. Despite the increasing demand for drone flying automation, there is a significant absence of a comprehensive drone network service architecture tailored for secure and efficient operations of drones. This research paper addresses this gap by proposing a safe, reliable, and real-time drone network service architecture, emphasizing collaboration with fog computing. The contribution includes a systematic architecture design and integration of blockchain technology for secure data storage. Fog computing was introduced for the Drone with Blockchain Technology (FCDBT) model, where drones collaborate to process IoT data efficiently. The proposed algorithm dynamically plans drone trajectories and optimizes computation offloading. Results from simulations demonstrate the effectiveness of the proposed architecture, showcasing reduced average response latency and improved throughput, particularly when accessing resources from fog nodes. Furthermore, the model evaluates blockchain consensus algorithms (PoW, PoS, DAG) and recommends DAG for superior performance in handling IoT data. Fog; Drones; Blockchain; PSO; IoT; Vehicular.

A survey on the application of blockchain in cryptographic protocols

With the continuous development of network technology, cryptographic protocols are facing diverse and complex security challenges. Blockchain technology, as a solution incorporating decentralization, traceability, programmability, and immutability, effectively enhances the security, trustworthiness, operational efficiency, and ensures the security and integrity of data storage in traditional cryptographic protocols. Consequently, it has gradually emerged as a focal point of research in cryptographic protocols. This manuscript delves into the ongoing research concerning the application of blockchain technology in cryptographic protocols. First, this manuscript introduces the background of blockchain research in cryptographic protocols and the corresponding basic knowledge. Secondly, we delve into the main concerns of traditional cryptographic protocols, with a particular focus on security and performance. Thirdly, according to the main classification of cryptographic protocols, the latest research results of blockchain in authentication protocols, authentication and key agreement protocols, and e-commerce protocols are presented. Finally, the research directions of blockchain technology in cryptographic protocols are summarized based on the existing research, and the future development trend is also prospected.

The Impact of Big Data on the Fashion Industry

This study explores the impact of big data on the fashion industry. Through analysis of market trend forecasting, supply chain management, personalized design and customization, optimization of marketing strategies, acceleration of market responsiveness, enhancement of market competitiveness, and improvement of consumer experience, the potential applications of big data in the fashion sector are further elucidated. The research reveals that big data can effectively boost overall operational efficiency in the fashion industry, enabling companies to achieve precise marketing, optimize inventory management, shorten time-to-market for products, reduce operational costs, and enhance market competitiveness. However, the application of big data in the fashion industry also presents challenges such as data security and privacy protection, risks of data breaches, security of data storage and transmission, and barriers to data analysis technology. Therefore, when utilizing big data technologies, businesses must strengthen data security measures, enhance data analysis capabilities, ensure the lawful use of data, and strive for sustainable development.

High-resolution, high-speed, chromotropic color printing based on fs-laser-induced gold/graphene HSFLs

Through achieving high-spatial-frequency laser-induced periodic surface structures (HSFLs) on a gold/graphene hybrid film, we introduce a high-speed, high-resolution, and wide-gamut chromotropic color printing technique. This method effectively addresses the trade-off between throughput and resolution in laser coloring. To realize Au HSFL, disordered lattice structures and high transmittance of amorphous Au (a-Au) thin film are used to overcome the rapid hot-electron diffusion and loss of plasmonic coherence typically observed on low-loss metal surfaces, respectively. Coupled with crystallization in Au and modulated surface plasmon polaritons by artificial “seed” pre-structure growing in a SiO2/Si substrate, HSFL emerged with a period of 100 nm on crystalline Au after single and rapid femtosecond laser scanning. This equips the proposed color printing with high-resolution and high-speed features simultaneously. In addition, the crystallization process is demonstrated to initiate change in the complex refractive index of Au, which causes wide-gamut colors. The chromotropic capability, which facilitates the background color to be tailored in color as well as into desirable shapes independently, enables three-level anti-counterfeiting based on the proposed color printing. Therefore, the proposed color printing is amenable for practical implementation in diverse applications, including security marking and data storage, ranging from nanoscale to large-scale fabrication.

Balancing Innovation and Privacy: Safeguarding Personal Information in the AI-Driven Digital Era

The rapid innovation of Artificial Intelligence (AI) has transformed various sectors of society by revolutionising decision making and enhancing efficiency through novel data-driven technologies. This paper explores the challenges of striking a healthy balance between future AI innovation and personal data privacy, where the massive collection and utilisation of personal data have given rise to significant privacy concerns. The study identifies the risks of massive data collection, complex and opaque algorithms, and cybersecurity threats, while simultaneously highlighting the existing legal frameworks such as General Data Protection Regulation (GDPR) and the variations among global approaches to data privacy. The paper also discusses the technical solutions such as privacy-preserving techniques including differential privacy and federated learning, as well as encryption technologies that can facilitate the secure storage and transmission of data. The research proposes strategies for building privacy-preserving AI models and encouraging cross-industry collaboration to achieve a balance between innovation and the protection of individual privacy. It also adds to the ongoing discourse on shaping a responsible future for AI.

Improving Participant Recruitment in Clinical Trials: Comparative Analysis of Innovative Digital Platforms.

Pharmaceutical product development relies on thorough and costly clinical trials. Participant recruitment and monitoring can be challenging. The incorporation of cutting-edge technologies such as blockchain and artificial intelligence has revolutionized clinical research (particularly in the recruitment stage), enhanced secure data storage and analysis, and facilitated participant monitoring while protecting their personal information. This study aims to investigate the use of novel digital platforms and their features, such as e-recruitment, e-consent, and matching, aiming to optimize and expedite clinical research. A review with a systematic approach was conducted encompassing literature from January 2000 to October 2024. The MEDLINE, ScienceDirect, Scopus, and Google Scholar databases were examined thoroughly using a customized search string. Inclusion criteria focused on digital platforms involving clinical trial recruitment phases that were in English and had international presence, scientific validation, regulatory approval, and no geographic limitations. Literature reviews and unvalidated digital platforms were excluded. The selected studies underwent meticulous screening by the research team, ensuring a thorough analysis of novel digital platforms and their use and features for clinical trials. A total of 24 digital platforms were identified that supported clinical trial recruitment phases. In general, most of them (n=22, 80%) are headquartered and operating in the United States, providing a range of functionalities including electronic consent (n=14, 60% of the platforms), participant matching, and monitoring of patients' health status. These supplementary features enhance the overall effectiveness of the platforms in facilitating the recruitment process for clinical trials. The analysis and digital platform findings refer to a specific time frame when the investigation took place, and a notable surge was observed in the adoption of these novel digital tools, particularly following the COVID-19 outbreak. This study underscores the vital role of the identified digital platforms in clinical trials, aiding in recruitment, enhancing patient engagement, accelerating procedures, and personalizing vital sign monitoring. Despite their impact, challenges in accessibility, compatibility, and transparency require careful consideration. Addressing these challenges is crucial for optimizing digital tool integration into clinical research, allowing researchers to harness the benefits while managing the associated risks effectively.

Blockchain and Machine Learning: A Multidisciplinary Synergistic Approach for Fraud Detection in Finance, Healthcare, and Cybersecurity

The integration of Blockchain and Machine Learning (ML) technologies offers a transformative approach to combating fraud across various sectors, including finance, healthcare, and cybersecurity. Blockchain's decentralized and immutable nature ensures data integrity and transparency, while Machine Learning algorithms enable the detection of intricate fraud patterns through predictive analytics and anomaly detection. This synergistic combination provides a robust mechanism for identifying fraudulent activities in real time, minimizing human error, and optimizing decision-making processes. In the financial sector, Blockchain enhances the security and transparency of transactions, while ML models analyze transaction data to identify unusual patterns that may indicate fraud. In healthcare, Blockchain ensures the secure sharing of medical records, and ML assists in detecting fraudulent claims and potential identity theft. Cybersecurity applications leverage Blockchain for secure communication and data storage, with ML identifying potential threats or vulnerabilities. By combining these two cutting-edge technologies, organizations can strengthen their fraud detection systems, improve trust, and mitigate the risks associated with financial losses, data breaches, and privacy violations. This paper explores the multidisciplinary synergy of Blockchain and ML, illustrating their potential to revolutionize fraud detection mechanisms across multiple domains, providing a comprehensive overview of current advancements, challenges, and future directions for their integration in the fight against fraud.

Security and Compliance in Cloud ERP Systems: A Deep Dive into Workday's Framework

This paper provides a comprehensive analysis of the security and compliance framework within cloud- based ERP systems, with a particular focus on Workday, a leader in the market for enterprise resource planning (ERP) solutions. As businesses increasingly transition to cloud ERP systems, ensuring robust security and regulatory compliance has become critical to safeguarding sensitive data, maintaining operational integrity, and meeting industry-specific regulations. The paper begins by introducing the essential concepts of cloud ERP security, highlighting the challenges of data breaches, data integrity, and access control. It further explores Workday's advanced security infrastructure, including its encryption protocols, secure data storage, and real-time monitoring systems, as well as its adherence to global compliance standards such as GDPR, SOC 2, and ISO 27001. The analysis also emphasizes Workday’s tailored security features for specific industries like finance, healthcare, and government, demonstrating how its platform fosters customer trust and drives adoption across diverse sectors. Looking to the future, the paper discusses emerging trends, including the integration of Artificial Intelligence (AI), Machine Learning (ML), and blockchain technology, which hold potential for enhancing data security and compliance in cloud ERP environments. This deep dive into Workday’s security and compliance framework underscores its role in mitigating risks, ensuring regulatory adherence, and positioning itself as a trusted solution in an evolving cloud landscape. Keywords: AI/ML, Cloud ERP Security, Workday Security Framework, Cloud ERP Compliance, Workday Compliance Standards, Data Security, Workday Data Encryption, Regulatory Compliance, SOC 2 Compliance, Identity and Access Management, GDPR Compliance, Risk Mitigation.

Efficient DNA Cryptography Using One-Time Pad and Run-Length Encoding for Optimized Ciphertext Storage

Cryptography ensures data privacy by transforming data into unreadable formats that only authorized individuals can decrypt. With the increase in electronically stored and transmitted data, enhanced methods for data protection are required. DNA cryptography, leveraging the genetic structure of DNA, provides a promising approach for secure communication and data storage. This paper introduces a novel DNA-based cryptographic method employing a DNA one-time pad (OTP) combined with modified run-length encoding to reduce ciphertext size. Unlike traditional cryptography, which often results in a larger ciphertext than plaintext, our proposed method demonstrates a significant reduction in ciphertext size. Experimental results reveal that for input text files of 1MB, 2MB, 3MB, 5MB, and 10MB, the ciphertext sizes were reduced by up to 20KB, 40KB, 60KB, 100KB, and 200KB, respectively. This reduction not only enhances storage efficiency but also minimizes transmission costs, marking a substantial advancement over existing DNA and classical cryptography methods. Future work will explore the application of this technique for encrypting biological data and incorporating DNA barcoding for improved data authentication and reliability.

Exploring Various Approaches for Secure Data Storage in Cloud Environments

Cloud computing has modified the way the data is stored and accessed. Even if the shared nature of cloud environments may leads to security challenges. This paper provides a comprehensive overview of various strategies used and using for securing data at rest in the cloud environment. This paper delve into the core ideas of data encryption, access control mechanism and data integrity, studying there strengths, drawbacks and accessibility to different cloud aspects. This paper also deliberate emerging trends like homomorphic encryption and block-chain based solutions, which offer innovative approaches for enhancing data privacy and security. By analyzing this approaches in depth, this paper identify the optimal strategies for protecting sensitive data stored in the cloud.

Secured Data Storage on the Cloud Using Hybrid Cryptography

With the growing reliance on cloud computing for data storage, ensuring the security and confidentiality of sensitive data has become paramount. Despite its advantages, cloud storage is susceptible to various security threats such as data breaches, unauthorized access, and insider threats. Traditional cryptographic techniques like symmetric and asymmetric cryptography offer a measure of security but have limitations when used independently. This paper proposes a hybrid cryptographic approach that combines the strengths of both symmetric and asymmetric cryptography, ensuring a robust solution for secured data storage in the cloud. The hybrid approach leverages the speed and efficiency of symmetric algorithms and the strong security features of asymmetric algorithms, making them both secure and efficient. This research explores various hybrid encryption techniques, discusses their security features, and demonstrates how they enhance data protection on cloud platforms

A method to enhance privacy preservation in cloud storage through a three-layer scheme for computational intelligence in fog computing

Recent advancements in cloud computing have heightened concerns about data control and privacy due to vulnerabilities in traditional encryption methods, which may not withstand internal attacks from cloud servers. To overcome these issues about the data privacy and control of transfer on cloud, a novel three-tier storage model incorporating fog computing method has been proposed. This framework leverages the advantages of cloud storage while enhancing data privacy. The approach uses the Hash-Solomon code algorithm to partition data into distinct segments, distributing a portion of it across local machines and fog servers, in addition to cloud storage. This distribution not only increases data privacy but also optimises storage efficiency. Computational intelligence plays a crucial role by calculating the optimal data distribution across cloud, fog, and local servers, ensuring balanced and secure data storage.•Experimental analysis of this mathematical mode has demonstrated a significant improvement in storage efficiency, with increases ranging from 30 % to 40 % as the volume of data blocks grows.•This innovative framework based on Hash Solomon code method effectively addresses privacy concerns while maintaining the benefits of cloud computing, offering a robust solution for secure and efficient data management.

Enhancing Cloud Security: Strategies and Technologies for Protecting Data in Cloud Environments

With the rapid adoption of cloud computing, ensuring the security of data has become a paramount concern for organizations of all sizes. This paper explores various strategies and technologies for protecting data in cloud environments. Encryption emerges as a fundamental technique for safeguarding data both at rest and in transit, with block ciphers and stream ciphers offering robust encryption methods. Additionally, hash functions play a critical role in verifying data integrity and ensuring secure data storage. We delve into the implementation of these techniques in cloud environments, highlighting best practices for encryption, key management, and data integrity verification. Moreover, we address common cloud vulnerabilities, such as lack of appropriate governance, isolation failure, and malicious attacks, and discuss mitigation strategies to strengthen cloud security posture. By leveraging encryption, block ciphers, stream ciphers, and hash functions, organizations can enhance data protection in the cloud and mitigate the risks associated with unauthorized access, data breaches, and tampering. This paper serves as a comprehensive guide for organizations seeking to enhance their cloud security and maintain trust in cloud-based services.

Blockchain Technology for Ensuring Data Integrity in Cloud Computing

This paper explores the integration of blockchain technology to enhance data integrity in cloud computing environments. As data breaches and unauthorized access continue to challenge traditional cloud security measures, blockchain offers a decentralized solution that ensures tamper-proof record-keeping and accountability. By leveraging cryptographic techniques and distributed ledger technology, the proposed framework enables secure data storage, sharing, and validation processes. This study highlights key use cases, potential challenges, and the overall impact of blockchain on improving trust and reliability in cloud computing, paving the way for more robust data integrity solutions in various applications across industries.

A consortium blockchain-edge enabled authentication scheme for underwater acoustic network (UAN)

The Internet of Things (IoT) allows for automated operations in diverse fields, such as agriculture monitoring, pollution monitoring, health care, and underwater monitoring. The Internet of Underwater Things (IoUT) observes the underwater environment, assists in exploration, mitigates disasters, and monitors some factors including temperature, pressure, and pollution. The IoUT relies on a network of intelligent underwater sensors that send data to surface base stations and IoT devices for storage and analysis. Nevertheless, these systems face security risks as they operate in unattended environments. Many authentication methods depend on a centralized third party, leading to higher computation costs and energy usage. To mitigate security risks, autonomous underwater devices need secure connections and authentication. This paper suggests a decentralized authentication mechanism for UAN to safeguard against unauthorized access and ensure secure data storage in the cloud. The proposed mechanism prioritizes robustness, transparency, and energy efficiency. The suggested solution incorporates an architecture based on edge and cloud layers, utilizing customized blockchain technology for secure storage and processing of data. The security of the proposed solution has been thoroughly examined through formal analysis utilizing the Real or Random (ROR) Oracle model and Scyther tool. Informal analysis further confirms the solution’s resilience against various malicious attacks. Additionally, performance and comparative analysis demonstrate that the proposed solution surpasses existing schemes.