Secure Data Storage Research Articles

JCDC: A blockchain-based framework for secure data storage and circulation in JointCloud

JointCloud computing represents a new generation cloud computing paradigm, which deeply integrates the cloud resources of multiple Cloud Service Providers (CSPs) to offer tailored cloud services to users. In contrast to traditional multi-cloud environment, JointCloud environment involve data circulation among multiple CSPs. However, in JointCloud environment, CSPs are not always fully trustworthy and they may illegally infringe upon users’ data privacy and security for their own benefit. Additionally, the heterogeneity arising from different data storage formats, structures, access control, and permission management mechanisms adopted by various CSPs makes achieving unified data management in JointCloud challenging. Therefore, to ensure secure storage and efficient circulation of data within JointCloud, it is essential to prevent violations for user privacy and data ownership, shield the heterogeneity of underlying data management mechanisms across different CSPs, and establish trusted transactions between CSPs. In this paper, we propose a framework called JointCloud Data Chain (JCDC) based on JointCloud computing and blockchain for data storage and circulation, aiming to ensure secure data storage and trustworthy transactions. JCDC utilizes blockchain to record data ownership and control data circulation, while integrating storage resources from various CSPs to construct a distributed off-chain Personal Data Storage (PDS) for expanding system storage capacity. Additionally, JCDC employs Certificateless Public Key Cryptography (CL-PKC) and Proxy Re-encryption technologies for user identity management and secure data transactions. Furthermore, smart contracts are designed to enable automated data storage and sharing. We conduct a security analysis of JCDC and develop a prototype system to validate its performance and practicality. Finally, extensive experimentation and analysis demonstrate that JCDC exhibits low time latency and cost, which makes it practical.

SAFEGUARDING CHILDREN’S DATA IN THE DIGITAL AGE: A LEGAL APPROACH TO PREVENT CYBERATTACKS AND CHILD SEXUAL ABUSE

The growth of digital technologies and online platforms has dramatically increased the risk of children becoming victims of sexual abuse. Cybercriminals often abuse children's personal information, such as their name, age, location, and online activities, to identifyand exploit them. However, this digital revolution has also led to increased risks, including the vulnerability of children's data to cybersecurity attacks. One of the most concerning consequences of such attacks is facilitating child sexual abuse. Therefore,protecting children's data is essential in preventing child sexual abuse. In this background based on this hypothesis, this paper focuses on the legal approach to protect the vulnerability of children's data from cybersecurity attacks. The paper analysis the legal frameworks and guidelines developed by the Indian government to safeguard the personal data of children. Further, it would identify the current gaps in the legal framework and emphasise the need for further improvements towards strengthening the data protection of children. Moreover, the paper explores the role of technology in protecting children's data, including data encryption, secure data storage, access controls, and monitoring systems and also analyses the challenges associated with implementing these technological solutions. Finally, the paper offers suggestions for policymakers, legal practitioners, and technology professionals to protect children's data from cyberattacks, thereby preventing child sexual abuse.

Spatio-Temporal Big Data Collaborative Storage Mechanism Based on Incremental Aggregation Subvector Commitment in On-Chain and Off-Chain Systems

As mobile internet and Internet of Things technologies rapidly advance, the amount of spatio-temporal big data have surged, and efficient and secure management solutions are urgently needed. Although cloud storage provides convenience, it also brings significant data security challenges. Blockchain technology is an ideal choice for processing large-scale spatio-temporal big data due to its unique security features, but its storage scalability is limited because the data need to be replicated throughout the network. To solve this problem, a common approach is to combine blockchain with off-chain storage to form a hybrid storage blockchain. However, these solutions cannot guarantee the authenticity, integrity, and consistency of on-chain and off-chain data storage, and preprocessing is required in the setup phase to generate public parameters proportional to the data length, which increases the computational burden and reduces transmission efficiency. Therefore, this paper proposes a collaborative storage mechanism for spatio-temporal big data based on incremental aggregation sub-vector commitments, which uses vector commitment binding technology to ensure the secure storage of on-chain and off-chain data. By generating public parameters of fixed length, the computational complexity is reduced and the communication efficiency is improved while improving the security of the system. In addition, we design an aggregation proof protocol that integrates aggregation algorithms and smart contracts to improve the efficiency of data query and verification and ensure the consistency and integrity of spatio-temporal big data storage. Finally, simulation experiments verify the correctness and security of the proposed protocol, providing a solid foundation for the blockchain-based spatio-temporal big data storage system.

Secure and efficient data storage with Rivest Shamir Adleman algorithm in cloud environment

Cloud computing rapidly is a prerequisite and releases resources with minimal management effort. The surfacing of the cloud has significantly distorted the general insight into infrastructure, software services, and development models. In contrast to single-key encryption models based on public or private keys (PKs), hybrid encryption systems combine encryption methods using symmetric or asymmetric methods. Various hybrid algorithms fail to meet users’ expectations regarding data security and cannot prevent all security risks. The secure and efficient data storage and retrieval (SEDSR) algorithm was developed for scalable key management between the content owner, cloud user, and service providers in an un-trusted cloud environment. In the implementation, the SEDSR combines the Rivest Shamir Adleman (RSA) algorithm 4096 key length with a primary symmetric key method to provide adequate and compact security with optimal retrieval systems in the cloud. Based on the experimental evaluation, the SEDSR minimizes 1.7 seconds of encryption times (ET) and 1.5 seconds of decryption time (DT) and improves by 34% throughput (TRP) compared to existing parameters.

Solana blockchain technology: a review

The introduction of a review article on the Solana blockchain is critical to setting the stage for the arguments and evidence to follow. This paragraph will provide context to the reader by discussing the current state of blockchain technology and introducing Solana as a potential solution. Blockchain technology has the potential for countless applications, ranging from financial transactions to secure data storage. However, existing blockchain systems suffer from scalability issues, were confirmation times and network congestion limit transaction volumes. This review paper on the Solana blockchain is valuable for those seeking an in-depth understanding of the design and efficacy. Given the increasing number of blockchain technologies available in the market, potential adopters face the challenge of selecting the most suitable blockchain network for their specific use case. A well-constructed review provides necessary information on the functioning of the technology, including its strengths and limitations. It also enables readers to compare various blockchain technologies and judge their suitability for their specific needs. Therefore, reviews like this one play a crucial role in helping to advance blockchain technology by driving the adoption of superior blockchain networks.

ANDROID HEALTHCARE APPLICATION

The healthcare systems is pivotal in improving the accessibility and management of healthcare services. This paper focuses on the creation of a comprehensive appointment management system to streamline various healthcare interactions. Modern healthcare challenges such as scheduling appointments, ordering medications, and accessing health information necessitate an integrated approach. The proposed system includes modules for user registration, lab test management, medication management, doctor search and appointment booking, health education articles, order tracking, and user logout functionalities. Utilizing user-friendly interfaces and robust backend infrastructure, the system ensures secure user registration, easy browsing of lab tests and medications, efficient search for specialist doctors, convenient appointment booking, access to health articles, and order tracking. Key features include personalized user profiles, real-time appointment scheduling, and secure data storage using a SQLite database. Keywords: Healthcare management, Mobile Applications, Software Engineering

Research on airport baggage anomaly retention detection technology based on machine vision, edge computing, and blockchain

AbstractAirport checked luggage entails specific requirements for speed, stability, and reliability. The issue of abnormal retention of checked luggage presents a significant challenge to aviation safety and transportation efficiency. Traditional luggage monitoring systems exhibit limitations in terms of accuracy and timeliness. To address this challenge, this paper proposes a real‐time detection and alerting of luggage anomaly retention based on the YOLOv5 object detection model, leveraging visual algorithms. By eliminating cloud servers and deploying multiple edge servers to establish a private chain, images of anomalously retained luggage are encrypted and stored on the chain. Data users can verify the authenticity of accessed images through anti‐tampering algorithms, ensuring the security of data transmission and storage. The deployment of edge computing servers can significantly reduce algorithm latency and enhance real‐time performance. This solution employs computer vision technology and an edge computing framework to address the speed and stability of checked luggage transportation. Furthermore, blockchain technology greatly enhances system security during operation. A model trained on a sample set of 4600 images achieved a luggage recognition rate of 96.9% and an anomaly detection rate of 95.8% in simulated test videos.

Challenges in acoustical modeling of data centers

Data centers are physical infrastructures that house computing machines and related hardware equipment for data storage and processing. Due to the ever-increasing trend of cloud computing and the need for secure data storage, several organizations are involved in the development of large data center facilities. This new industry sector is seeing massive growth in recent years and municipalities and counties across the nation are welcoming the construction of data centers in their areas. Acoustical modeling for a data center can be challenging due to various factors and this article discusses a few such challenges that were experienced during the acoustical assessments of data center operations.

TINJAUAN PUSTAKA: DAMPAK TEKNOLOGI INFORMASI DAN KOMUNIKASI (TIK) PADA PRAKTIK MANAJEMEN SUMBER DAYA MANUSIA DI ERA DIGITAL

This study examines the effects of Information and Communication Technology (ICT) on employee performance measurement and appraisal, focusing on how ICT can improve the accuracy and fairness of evaluations. The research methodology employed is a comprehensive literature review. Relevant articles published in Indonesian from 2019 to 2023 were retrieved from the GARUDA database. Keywords and phrases related to ICT and performance were used to search for abstracts or full-text journal articles. These were then reviewed and analyzed according to specific criteria. The results of the review of 15 journals over the past 5 years highlight 7 key points: 1) Enhanced Performance Monitoring through Real-Time Data, 2) Integration of Performance Management Systems with HR Functions, 3) Use of Artificial Intelligence for Personalized Feedback, 4) Streamlining of Evaluation Processes through Automation, 5) Adoption of Standardized Performance Metrics, 6) Employee Engagement through Interactive Feedback Mechanisms, 7) Secure Data Storage and Confidentiality.

Blockchain Technology for Integrating Electronic Records of Digital Healthcare System

Background: In most healthcare facilities, the shift from paper-based medical records to electronic health records (EHRs) has taken place. However, there are issues with credibility, management, and secure data storage with the existing EHR systems. In the healthcare industry, interoperability and user control over personal data are also major challenges. Block chain technology has become a potent tool that can provide immutability, security, and user control over records that are saved; yet, its potential usage in EHR systems is still not well understood. Objectives: This research attempts to close this knowledge gap by developing an EHR framework that is built on blockchain technology and is compatible with many national and international EHR standards, including HL7 and HIPAA. Methods: In order to investigate the state of the art in the field of EHRs, including blockchain-based EHR implementations, a systematic literature review is the study approach used. Results: The report analyzes numerous national and international EHR standards, identifies the interoperability needs based on these standards, and outlines the interoperability challenges in the current blockchain-based EHR frameworks. Without the requirement for centralized systems, the suggested framework can give the healthcare industry safer ways to exchange health information while also offering the features of immutability, security, and user control over stored records. Conclusion: This work contributes to the understanding of Blockchain technology's potential application in EHR frameworks and offers an interoperable Blockchain-based EHR framework that can meet the requirements outlined in multiple national and international EHR standards.

Exploring AWS S3: In-Depth Analysis of Bucket Management

Amazon Simple Storage Service (S3) is a cornerstone in modern data management strategies with in Amazon Web Services (AWS). It is pivotal in providing scalable, durable, and accessible object storage infrastructure. A key advantage of S3 is its scalability, enabling seamless storage capacity expansion without upfront investments or provisioning delays. This flexibility empowers organizations to accommodate dynamic data growth while maintaining operational agility, which is crucial in today's rapidly evolving digital landscape. S3's exceptional durability, boasting an impressive 99.999999999% reliability, ensures steadfast data integrity and resilience against potential failures, mitigating concerns about data loss and bolstering confidence in managing mission-critical information effectively. Accessibility is another crucial aspect, with robust access controls and APIs facilitating secure data retrieval, storage, and management from any location. This accessibility fosters collaboration and innovation by enabling seamless data interaction and utilization across geographical boundaries.S3's integration capabilities with other AWS services enhance operational efficiency and optimize data analytics workflows. It is a foundational element in data analytics, facilitating data ingestion, storage, and processing to derive actionable insights from diverse datasets. Furthermore, S3's versatility extends beyond storage, supporting applications such as content delivery, backup and archiving, disaster recovery, and machine learning model training. This versatility drives innovation across industries and underscores S3's role in driving digital transformation and fostering a culture rooted in data-driven decision-making. In conclusion, Amazon S3's unparalleled scalability, durability, and accessibility make it indispensable for organizations navigating the data-centric landscape of modern business environments, underlining the imperative of harnessing its full potential for organizational success.

Convergent encryption enabled secure data deduplication algorithm for cloud environment

SummaryThe exponential growth of data poses a critical challenge for cloud storage systems. Redundant data consumes valuable storage space and increases infrastructure costs. Data deduplication, a technique for eliminating duplicate data copies, offers a promising solution. However, existing deduplication techniques often compromise data security, especially when dealing with encrypted data. This paper proposes a novel approach that merges convergent encryption (CE) with data deduplication. CE leverages user data itself to generate unique encryption keys, enabling secure deduplication on encrypted data. We analyze existing literature on secure data deduplication and categorize various techniques using UML activity diagrams. We then present our proposed CE‐based deduplication system, outlining its functionalities through UML diagrams. This research contributes to the field of secure data storage by proposing a novel and secure deduplication approach. By demonstrating its efficiency and security benefits, this work paves the way for more efficient and secure cloud storage solutions. Finally, we demonstrate the system's effectiveness through a comparative analysis, highlighting its potential to significantly improve storage efficiency while maintaining data security.

A Review of Blockchain-Based Research on E-Health Data Sharing

With the development of medical data informatization, the data security, data privacy, and data controllability of electronic medical data with patient's personal privacy have gained social attention. Blockchain technology has decentralized characteristics, and the development of blockchain technology provides an effective solution for the secure sharing of e-medical data. Many scholars have proposed e-medical data security sharing solutions based on blockchain technology, and these solutions have attempted to solve the security problems encountered in sharing traditional e-medical data. By summarizing and analyzing the schemes in this field, this study analyzes the advantages, disadvantages, and challenges that the current mainstream schemes have, mainly in terms of blockchain data security storage, access control security sharing, and so on, in order to promote the further development of the e-medical data security sharing scheme based on blockchain technology. This study analyzes the blockchain-based e-medical data security sharing scheme proposed by scholars by analyzing the blockchain technology, cryptography technology, smart contract technology, P2P network technology and other related topics. Through systematic analysis and comparison, it explores the challenges of the current research and provides references for the future proposals of blockchain technology-based schemes.

Decentralized edge computing approach for secure and efficient preservation of short-term electronic forensic evidence through consensus

With the burgeoning prevalence of edge computing, there has been a significant surge in the utilization of content caching across the digital landscape, significantly streamlining and expediting short-term electronic forensic operations. This study pioneers an innovative caching model tailored specifically for short-lived electronic forensic evidence within edge computing environments. The novel framework integrates blockchain technology to ensure the secure storage of evidentiary data, bolstered by an advanced consensus mechanism rooted in the MerkleTree architecture. This design safeguards the consistency and immutability of stored information. By decentralizing the process, this approach empowers real-time, on-the-edge electronic forensic investigations, effectively mitigating any risk of tampering from all parties involved, such as forensic examiners, cloud service providers, and end-users. Empirical findings robustly substantiate the efficacy of this proposed model in safeguarding and maintaining the fidelity of electronic evidence records, thus guaranteeing both the integrity and promptness of forensic materials. This groundbreaking solution sets a new standard for trustworthy and expedient handling of digital forensics at the edge of networks.

Development Of Web-Based Teleradiology Application To Enhance The Quality Of Radiology Services

The development of digital radiology technology improves the quality of medical services, but challenges in image distribution and interpretation encourage the use of teleradiology. The development of web-based teleradiology applications is a cost-effective solution with the ability to integrate patient data and DICOM image display to improve the efficiency of radiology interpretation. This has the potential to improve the quality of radiology services by accelerating the diagnostic process and reducing the physical accessibility limitations of radiologists.This study aims to develop a web-based application as a solution to radiographic image delivery and PACS weaknesses, and test its effectiveness in improving the quality of radiology services. The research method used is the research and development (R&D) method, which aims to produce and test new products. The results of this study show that the development of a web-based teleradiology application provides an appropriate solution to the constraints of the reader's presence at the image capture site, while maintaining image quality according to DICOM standards. The application allows easy use of various devices, data exchange between medical professionals, and secure data storage. In Addition, it reduces the waiting time in the delivery and reading of radiographic images by radiologists. Compared to older methods, such as delivery via email or Whatsapp, this web application shows improved quality and accuracy of radiographic image reading.

Intrusion detection and secure data storage in the cloud were recommend by a multiscale deep bidirectional gated recurrent neural network

Data communication security is developing very day with the creation of cloud computing. The imperative for robust data communication security has become increasingly evident with the pervasive adoption of cloud computing. However, challenges persist due to the inherent complexities and limited security measures in cloud environments, particularly in transmitting and storing sensitive information. Previous studies have underscored the intricate nature of intrusion detection systems (IDS) in cloud-based settings. In this research, a Multi scale Deep Bidirectional Gated Recurrent Neural Network and Optimal Encryption Scheme espoused Intrusion Detection and Secure Data Storage in the Cloud (MDBGRNN-ID-SCESOA) is proposed. Leveraging the KDD CUP 99 dataset and DS2OS Dataset, initial data preprocessing involves Domain Transform Filtering (DTF) for tokenization, dimension reduction, and semantic analysis. Subsequently, MDBGRNN is employed to discern intrusion from non-intrusion data. Furthermore, a two-way encryption mechanism, integrating Elliptical Curve Cryptography (ECC) with the Sine Cosine Egret Swarm Optimization Algorithm (ECC-SCESOA), enhances data security while minimizing computational overhead. To safeguard encrypted data at rest in the cloud, a steganography process is devised, effectively concealing sensitive content. Performance evaluation metrics, including accuracy, specificity, sensitivity, encryption/decryption time, execution time, memory usage, and Matthews correlation coefficient (MCC), demonstrate the efficacy of MDBGRNN-ID-SCESOA. Comparative analysis with existing techniques reveals notable enhancements in computational efficiency and data security. This comprehensive approach addresses critical security concerns in cloud computing, offering a promising avenue for safeguarding sensitive data in cloud environments.

IoMT-Based Smart Healthcare Detection System Driven by Quantum Blockchain and Quantum Neural Network.

Electrocardiogram (ECG) is the main criterion for arrhythmia detection. As a means of identification, ECG leakage seems to be a common occurrence due to the development of the Internet of Medical Things. The advent of the quantum era makes it difficult for classical blockchain technology to provide security for ECG data storage. Therefore, from the perspective of safety and practicality, this article proposes a quantum arrhythmia detection system called QADS, which achieves secure storage and sharing of ECG data based on quantum blockchain technology. Furthermore, a quantum neural network is used in QADS to recognize abnormal ECG data, which contributes to further cardiovascular disease diagnosis. Each quantum block stores the hash of the current and previous block to construct a quantum block network. The new quantum blockchain algorithm introduces a controlled quantum walk hash function and a quantum authentication protocol to guarantee legitimacy and security while creating new blocks. In addition, this article constructs a hybrid quantum convolutional neural network called HQCNN to extract the temporal features of ECG to detect abnormal heartbeats. The simulation experimental results show that HQCNN achieves an average training and testing accuracy of 94.7% and 93.6%. And the detection stability is much higher than classical CNN with the same structure. HQCNN also has certain robustness under the perturbation of quantum noise. Besides, this article demonstrates through mathematical analysis that the proposed quantum blockchain algorithm has strong security and can effectively resist various quantum attacks, such as external attacks, Entanglement-Measure attack and Interception-Measurement-Repeat attack.

Decentralize transaction records of digital payment gateway using Ethereum Blockchain and Interplanetary File System

This research proposes a system to store transaction records from a payment gateway based on digital payments by utilizing blockchain technology and Interplanetary File System (IPFS) as distributed storage. In digital payments, the possibility of online fraud or theft of customer data is a problem that needs to be solved. Although the solution is to use a Payment Gateway with security standards to prevent these problems, the system is still centralized and vulnerable to the possibility of system failure or data changes by irresponsible people. Blockchain furnishes a secure and unalterable record for documenting payment transactions. Conversely, IPFS presents a decentralized and immune-to-censorship approach for storing and accessing data. The usage of these technologies guarantees the secure storage of payment transaction data and related documents (such as invoices and receipts) while effectively thwarting data manipulation or censorship attempts. Therefore, this research aims to build a blockchain technology system to increase security and maintain the integrity of the data generated from the Payment Gateway. This research using distributed data storage using IPFS to save transaction from the payment gateway data. Based on the evaluation and security analysis results, implementing a blockchain technology system to store transaction records from digital-based payment gateways can improve data security and integrity. In the gas fee increase analysis, the gas fee will increase according to the total number of bytes generated when the transaction is made, where each byte will cost 12 gwei to pay the gas fee.

Retraction notice: Cloud-based secure data storage and access control for internet of medical things using federated learning

Retraction notice: Cloud-based secure data storage and access control for internet of medical things using federated learning

Investigating data storage security and retrieval for Fitbit wearable devices

PurposeThe use of wearable devices to monitor aspects of personal health is increasing. The Fitbit is an example of a popular device used for this purpose.It is unknown whether users’ privacy (i.e. sensitive data collected from wearable devices) would be leaked via unauthorized access. So, this investigation will answer the following questions; are the data transmissions protected against unauthorised access or modification? what data are transmitted between the device and the server? how much data can be collected by unauthorized access?MethodThis paper describes an investigation into data access in the Fitbit Blaze and, specifically, whether this is possible without connecting to the Fitbit server. A Man-In-The-Middle (MITM) attack was used in this investigation.ResultIn this experiment, the firmware image, transferred when the device connects to the Fitbit server, is first captured and analysed to obtain data. This was done to attempt to identify the encryption method and obtain the unique device MAC address. Secondly, some fitness data, namely, the authentication key, the cryptographic key and the Nonce, were extracted from the Fitbit application. We attempted to connect the Fitbit Blaze device and the Fitbit application directly without connecting via the Fitbit server. We also attempted direct access to the Fitbit Blaze using a charger cable. In addition, Fitbit Java files were extracted from the Fitbit application.ConclusionFinally, the outcomes of this investigation are compared with investigations into other Fitbit devices in the previous research.