Secure Data Access Research Articles

Design and implementation of experimental data access security policy for HEPS container computing platform

China’s High-Energy Photon Source (HEPS), the first national highenergy synchrotron radiation light source, is under design and construction. In the future, at the first stage of HEPS, it is predicted that 24PB raw experimental data will be produced per month from 14 beamlines. Faced with such a huge scale of scientific data and diverse data analysis environments in light source disciplines, the HEPS scientific computing platform was designed and implemented based on container mirroring and dynamic orchestration technology to provide HEPS users with a data analysis environment. In this article, a data security access strategy is designed and evaluated for a scientific computing platform to ensure the security and efficiency of data access for users in the entire process of data analysis. First, the general situation of HEPS is introduced. Second, the challenges faced by the HEPS scientific computing system. Third, the architecture and service process of the scientific computing platform are described from the perspective of IT, some key technical implementations will be introduced in detail. Finally, the application effect of data access security policies on computing platforms will be demonstrated.

Data Security Encryption Analysis Based on Blockchain Trusted Big Data Artificial Intelligence

Abstract The rapid development of Internet of Things (IoT) technology brings convenience to people but also brings data security problems. The data security problem can be solved effectively by blockchain due to its non-tampering and decentralization features. The purpose of traceability and auditable verification is achieved by adding user identity information and access policy to the blockchain in this paper. A blockchain-based data security access mechanism for cross-organizations is proposed and an attribute-based access control model is constructed. The feasibility and efficiency of this data protection scheme are evaluated by deploying an experimental environment and comparing it to reference schemes. The scheme proposed in this paper consumes less Gas for contract deployment than in other studies, and the Gas consumption grows slowly with more nodes, i.e., the cost grows slowly. The scheme in this paper consumes 7.00 seconds and 3.05 seconds less time than the reference network approach as well as the BAC approach in executing 300 transactions, respectively. The proposed scheme in this paper has shorter attribute secret key generation time and encryption/decryption time than the reference scheme. For example, when the number of attributes is 50, the scheme in this paper reduces the time of secret key generation by 144ms, 64ms, and 348ms compared to the scheme 1, 2, and 3. This paper breaks the performance bottleneck of blockchain and provides a new scheme for the security of user’s data and encryption.

Intrusion Detection in IoT Networks Using Machine Learning Techniques

The advent of the IoT has undeniably transformed the manner in which we connect with the world innovative solutions across a multitude of sectors. However, the proliferation of IoT applications has brought to the fore a complex and multifaceted problem that warrants immediate attention: the security and energy efficiency challenges within IoT networks. As the number of IoT devices continues to surge and their applications diversify, the demand for ubiquitous and secure data access has never been greater. These applications, ranging from healthcare monitoring to industrial automation, require not only real-time data processing but also the assurance of data security and privacy. So, the research explores the machine learning techniques application for intrusion detection in IoT networks, aiming to enhance security in the rapidly evolving landscape of interconnected devices. The research emphasizes the significance of proactive measures in safeguarding IoT ecosystems and highlights the potential of machine learning to detect and mitigate intrusions effectively. In this research, a model was developed for detecting anomalies in Internet of Things networks using artificial neural networks. The research aims to develop and evaluate an effective intrusion detection model for IoT networks by leveraging machine learning techniques. The purpose is to enhance the security posture of interconnected devices, addressing the unique challenges posed by the dynamic and heterogeneous nature of IoT environments. The study tries to contribute important experiences and functional answers to reinforce the strength of IoT networks against developing digital dangers.

BEYOND LEGAL FRAMEWORKS AND SECURITY CONTROLS FOR ACCESSING CONFIDENTIAL SURVEY DATA IN THE UNITED STATES: ENGAGING DATA USERS IN DATA PROTECTION.

With growing demand for data reuse and open data within the scientific ecosystem, protecting the confidentialy of survey data and privacy of data subjects is increasingly important. Doing so requires more than legal procedures and technological controls; it requires social and behavioral intervention. In this research note, we delineate the disclosure risks of various types of survey data (e.g., longitudinal data, social network data, sensitive information, biomarkers, and geographic data), the current motivation for data reuse, and challenges to data protection. Despite rigorous efforts to protect data, there are still threats to protection of confidentiality in microdata. Unintentional data breaches, protocol violations, and data misuse are observed even in well-established restricted data access systems, indicating that the systems may all rely heavily on trust. Creating and maintaining that trust is critical to secure data access. We suggest four ways of building trust; User-Centered Design Practices; Promoting Trust for Protecting Confidential Data; General Training in Research Ethics; and Specific Training in Data Security Protocols, with an example of a new project 'Researcher Passport' by the Inter-university Consortium for Political and Social Research. Continuous user-focused improvements in restricted data access systems are necessary so that we promote a culture of trust among the research and data user community, train both in the general topic of responsible research and in the specific requirements of these systems, and offer systematic and holistic solutions.

Denosumab and Mortality in a Real-World Setting: A Comparative Study.

Denosumab (Dmab) is increasingly prescribed worldwide. Unlike bisphosphonates (BPs), its effect on mortality has yet to be well explored. This study examined the association between Dmab and all-cause mortality compared with no treatment in subjects with a fracture and BPs in subjects without a fracture. The study population was from the Sax Institute's 45 and Up Study (n = 267,357), a prospective population-based cohort with questionnaire data linked to hospital admissions (Admitted Patients Data Collection [APDC] data were linked by the Centre for Health Record Linkage), medication records (Pharmaceutical Benefits Scheme [PBS] provided by Services Australia), and stored securely (secure data access was provided through the Sax Institute's Secure Unified Research Environment [SURE]). The new-user cohort design with propensity-score (PS) matching was implemented. In the fracture cohort, Dmab and oral BP users were matched 1:2 to no treatment (Dmab: 617 women, 154 men; oral BPs: 615 women, 266 men). In the no-fracture cohort, Dmab users were matched 1:1 with oral BPs and zoledronic acid (Zol) users (Dmab:oral BPs: 479 men, 1534 women; Dmab:Zol: 280 men, 625 women). Mortality risk was measured using sex-specific pairwise multivariable Cox models. In the fracture cohort, compared with no treatment, Dmab was associated with 48% lower mortality in women (hazard ratio [HR] = 0.52, 95% confidence interval [CI] 0.36-0.72) but not in men. Oral BPs were associated with 44% lower mortality in both sexes (women HR = 0.56, 95% CI 0.42-0.77; men HR = 0.56, 95% CI 0.40-0.78). In the no-fracture cohort, compared with BPs, Dmab was associated with 1.5- to 2.5-fold higher mortality than oral BPs (women HR = 1.49, 95% CI 1.13-1.98; men HR = 2.74; 95% CI 1.82-4.11) but similar mortality to Zol. Dmab in women and oral BPs were associated with lower post-fracture mortality than no treatment. However, Dmab users had generally higher mortality than oral BP users in those without fractures. © 2023 American Society for Bone and Mineral Research (ASBMR).

Provably Secure Data Access Control Protocol for Cloud Computing

Provably Secure Data Access Control Protocol for Cloud Computing

Secure data access using blockchain technology through IoT cloud and fabric environment

AbstractIn the current landscape, staying abreast of the latest technological advancements is a formidable challenge, especially given the deluge of data inundating the internet. The realization has dawned that effectively managing the surge in emerging data necessitates the integration of multiple technologies. In pursuit of this objective, the Internet of Things (IoT), renowned for its sensor‐based data capture capabilities, is frequently coupled with blockchain technology to ensure secure data storage and access. This amalgamation, in turn, leverages the cloud environment when data volume surpasses a machine's processing capacity, thus mitigating infrastructure and maintenance costs. This study endeavors to optimize data storage within the blocks of the blockchain (BCT) by storing an index that points to the actual data. This innovative approach not only conserves storage space but also enhances operational efficiency. Furthermore, it simplifies the task of identifying malicious or faulty nodes deployed at different locations for data capture within the prescribed time frame. To exemplify this implementation, a case study is presented, focusing on securing user votes through the creation of contracts. The results showcased underscore the preference for a permissioned blockchain, such as Fabric, over a permissionless one, like Ethereum, particularly in the context of security considerations. The findings reveal that as the number of operations (in this case, votes cast) increases, Ethereum's performance deteriorates, while Fabric exhibits exceptional robustness. Additionally, the study analyzes sensor data simulated via IoT nodes before and after the application of security algorithms to underscore the significance of the proposed Secure Cloud‐Based Blockchain (SCB2) model. The analysis encompasses various facets, including the creation, validation, and computation times of transactions and blocks within a node, and positions the model favorably in comparison to existing literature.

A novel lightweight decentralized attribute-based signature scheme for social co-governance

Social co-governance is an effective way to solve public safety incidents such as COVID-19 incident. But the insiders wouldn’t share the firsthand information for fear of cyber-violence. Though most of researches paid attention to the data access control and security, less attention focused on the identity privacy. So, in this work, it constructed a lightweight decentralized attribute-based signature scheme with unconditional full anonymity (LDABS-UFA) scheme to protect user’s identity privacy security. It confuses the user’s private key with fuzzy factors, and prevents user’s privacy in the signature from being disclosed. It outsources some complex computing to cloud servers to reduce the user device performance overhead. The security analysis result shows that the scheme is UFA security, unforgeability and non-collusion. Besides, a social co-governance system based on lightweight blackbox-based traceable decentralized attribute-based signature (LWBT-DABS) scheme is proposed. By generating fingerprints for the data owner in the signature, regulators can monitor the entire system and prevent malicious user from spreading rumors. And it constructs an accountability mechanism to prevent the abuse of supervisory power. The performance analysis shows that the data signature of our scheme size is constant, and the scheme is feasibility and practicability.

Investigation of Secure Health Monitoring System Using IOT

The rapid progress of technology, particularly the Internet of Things (IoT), has introduced exciting opportunities for transforming the healthcare sector. One significant area where IoT has made a significant impact is in the creation of secure health monitoring systems. These systems utilize IoT devices and sensors to gather and transmit live health data, facilitating remote monitoring and individualized healthcare.The integration of IoT in healthcare monitoring offers numerous benefits, including improved patient outcomes, enhanced access to care, and increased efficiency in healthcare delivery.To develop you would typically follow a research methodology that involves several key steps. Clearly state the objectives of your research, such as designing and implementing a secure health monitoring system using IoT. Specify the aspects you want to focus on, such as data privacy, authentication, encryption, or device communication. Develop a high-level system architecture for your health monitoring system. Define the components, their functionalities, and how they interact with each other. Consider the security aspects, such as secure data transmission, authentication, access control, and data storage.By multiplying each of our goals by a weight provided by the user, we can scale our collection of goals into a single goal using the weighted sum approach. One of the most popular strategies is this one. Finding the appropriate weights to give each aim while using the weighted sum approach is a concern. Taken as alternative parameters for HMS1, HMS2, HMS3, HMS4, HMS5. Taken as evaluation parameters for Portability,Round-The-Clock Health Surveillance,ease of use,Reliability.HMS1 performance is good when compared to others so HMS 1 is preferred except HMS 1 performed better in secure health monitoring system using IIOD.

Data Access Control for Secure Authentication Using Dual VC Scheme Based on CP-ABE in DID

In a Decentralized Identifier (DID), the Holder does not depend on a third party but controls self-identity information and is authenticated by the Verifier. Therefore, the Verifier can request verification data for access control from the Verifiable Data Registry (VDR) and credentials to authenticate the Holder. Data access control should be used when requesting data access such that only authorized Verifiers can access it. Consequently, studies on secure and efficient data access control have been conducted, and among them a scheme using Ciphertext Policy Attribute-based Encryption (CP-ABE) is underway. However, when the CP-ABE scheme is applied to the DID, the Holder’s extended Self-Sovereign Identity (SSI), which proves that the Holder has approved access to the Holder’s data stored in the VDR, is not ensured. Furthermore, the VDR does not verify the Verifier’s data access rights, resulting in unauthorized verification and illegal access to data by the user. And issue infringement of the Holder’s privacy, where Verifiers can infer the Holder by sharing and connecting the same DID-based Verifiable Presentations (VPs) of the Holder. Also, it leads to overheads in the amount of computation and search time for encryption/decryption. Therefore, in this paper, we propose a data access control for secure authentication by solving the security vulnerabilities of CP-ABE and using a CP-ABE-based dual Verifiable Credential (VC) scheme in DID.

SECURING WIRELESS BODY AREA NETWORKS: CASE STUDIES IN SECURITY AND PRIVACY

Wireless Body Area Networks (WBANs) are a promising technology for healthcare applications, enabling continuous monitoring of vital signs and personalized services. However, the primary challenge is securing wireless communication between wearable devices and the monitoring unit. Threats include unauthorized access, data interception, and tampering. To counteract these threats, various security techniques such as encryption, authentication, and key management protocols are examined. Privacy-preserving techniques like data anonymization and secure data aggregation are presented as viable solutions. Secure data storage and access control are also discussed, with biometric-based authentication systems enhancing system security. Regulatory compliance and ethical considerations are also highlighted, with the need to adhere to healthcare data protection regulations like HIPAA. Wireless Biometric Networks (WBANs) are more vulnerable to hacking, such as identity theft and data tampering. Solutions like encryption, authentication, access control, and intrusion detection systems are proposed to address these challenges. Keywords Wireless Body Area Networks, Security Privacy, Encryption, Authentication, Access control, Intrusion detection, Case studies, Regulatory compliance, Ethical considerations, Healthcare data protection, Informed consent, Data ownership, Storage.

Toward Forward and Backward Private Dynamic Searchable Symmetric Encryption Supporting Data Deduplication and Conjunctive Queries

In Internet of Things (IoT) application scenarios such as intelligent logistics, secure data access control and sharing based on dynamic searchable symmetric encryption (DSSE) has become a research hotspot in recent years. DSSE is an encryption technology which gratifies the above requirements, while protecting the sensitive data during the operation. The existing DSSE schemes do not achieve data deduplication and conjunctive queries concurrently, and exist problems such as complex update process, inflexible query method and privacy disclosure, etc. For this purpose, the paper proposes dynamic searchable symmetric encryption for data deduplication and conjunctive queries (DSSE-DC), and constructs a concrete DSSE-DC scheme. Our scheme uses symmetric encryption with homomorphic addition and bitmap index to develop a secure and reliable search architecture, and updates through modular addition. Meanwhile, we add a deduplication mechanism to realize data deduplication which avoids the waste of cloud storage resources. Furthermore, we introduce the idea of inner product matching to achieve efficient conjunctive queries. The adaptive security of DSSE-DC scheme is proved in the random oracle model. Whilst our scheme satisfies forward and backward privacy. In comparison to the existing DSSE schemes for conjunctive queries, our scheme has advantage in update and search performances, which is applicable to IoT applications like intelligent logistics.

A health integrated platform for pharmacy clinical intervention data management and intelligent visual analytics and reporting

ObjectiveOur initiative aimed to improve the system used to capture pharmacist clinical interventions to better support staff to document, manage and identify trends in medication-related problems (MRPs). The aim of the study was to develop an electronic tool which is easily accessible by most electronic devices with secure data storage and access. MethodsA REDCap® database was designed for documentation of pharmacy clinical interventions. Information documented can be retrieved in real-time and can be integrated to Microsoft Power BI® for real-time data visualisation. The dashboards were customised to display useful information including pharmacy clinical intervention details, common MRPs, common medications involved available to users at real time. ResultsA total of 4343 interventions were documented from July 2022 to March 2023. The most common MRPs were omission of regular medications 876 (20.17%), condition untreated 722(16.62%), and contraindications apparent 451 (10.38%). The most common medications involved include iron 244 (5.62%), enoxaparin 231 (5.32%), macrogol laxatives 208 (4.79%), multivitamin 206 (4.74%), colecalciferol 179(4.12%), tramadol 156 (3.59%). ConclusionThis study demonstrated the significance of integration of health application tools of REDcap and Power BI in the data management and intelligent visual analytics and reporting.

Blockchain-Powered Healthcare Systems: Enhancing Scalability and Security with Hybrid Deep Learning.

The rapid advancements in technology have paved the way for innovative solutions in the healthcare domain, aiming to improve scalability and security while enhancing patient care. This abstract introduces a cutting-edge approach, leveraging blockchain technology and hybrid deep learning techniques to revolutionize healthcare systems. Blockchain technology provides a decentralized and transparent framework, enabling secure data storage, sharing, and access control. By integrating blockchain into healthcare systems, data integrity, privacy, and interoperability can be ensured while eliminating the reliance on centralized authorities. In conjunction with blockchain, hybrid deep learning techniques offer powerful capabilities for data analysis and decision making in healthcare. Combining the strengths of deep learning algorithms with traditional machine learning approaches, hybrid deep learning enables accurate and efficient processing of complex healthcare data, including medical records, images, and sensor data. This research proposes a permissions-based blockchain framework for scalable and secure healthcare systems, integrating hybrid deep learning models. The framework ensures that only authorized entities can access and modify sensitive health information, preserving patient privacy while facilitating seamless data sharing and collaboration among healthcare providers. Additionally, the hybrid deep learning models enable real-time analysis of large-scale healthcare data, facilitating timely diagnosis, treatment recommendations, and disease prediction. The integration of blockchain and hybrid deep learning presents numerous benefits, including enhanced scalability, improved security, interoperability, and informed decision making in healthcare systems. However, challenges such as computational complexity, regulatory compliance, and ethical considerations need to be addressed for successful implementation. By harnessing the potential of blockchain and hybrid deep learning, healthcare systems can overcome traditional limitations, promoting efficient and secure data management, personalized patient care, and advancements in medical research. The proposed framework lays the foundation for a future healthcare ecosystem that prioritizes scalability, security, and improved patient outcomes.

NDN-RBE: An Accountable Privacy Aware Access Control Framework For NDN

Abstract Named Data Networking (NDN) is an emerging network architecture. An important characteristic of NDN is its in-network cache, which enables Data packets to be available from multiple locations on the Internet. Hence the enforcement of access control mechanisms becomes even more critical in the NDN. This paper proposes a novel access control scheme referred to as Role-Based Encryption for NDN (NDN-RBE), which uses a broadcast encryption mechanism to achieve secure data access control. Our scheme uses the role inheritance property of the traditional Role-Based Access Control (RBAC) model to achieve efficient data access control over hierarchical content. This makes our scheme particularly suitable for large-scale real-world content-centric services like Netflix. Our scheme also supports additional design features such as anonymous signature-based authentication, batch signature verification and two types of privilege revocations. In addition, our formal security analysis demonstrates that our scheme is provably secure against Chosen Plaintext Attacks. Our performance and functionality comparison show that our scheme outperforms other notable existing works in terms of security, functionality, computation, communication and storage overhead. Furthermore, our experimental results show an improvement in content delivery time of the order of 15 percent compared with the other closely related works.

Blockchain-Based Secure Storage and Access Control Scheme for Supply Chain Ecological Business Data: A Case Study of the Automotive Industry.

The reliable circulation of automotive supply chain data is crucial for automotive manufacturers and related enterprises as it promotes efficient supply chain operations and enhances their competitiveness and sustainability. However, with the increasing prominence of privacy protection and information security issues, traditional data sharing solutions are no longer able to meet the requirements for highly reliable secure storage and flexible access control. In response to this demand, we propose a secure data storage and access control scheme for the supply chain ecosystem based on the enterprise-level blockchain platform Hyperledger Fabric. The design incorporates a dual-layer attribute-based auditable access control model for access control, with four smart contracts aimed at coordinating and implementing access policies. The experimental results demonstrate that the proposed approach exhibits significant advantages under large-scale data and multi-attribute conditions. It enables fine-grained, dynamic access control under ciphertext and maintains high throughput and security in simulated real-world operational scenarios.

PERANCANGAN JARINGAN VPN MENGGUNAKAN MIKROTIK DENGAN METODE L2TP/IPSEC

Currently, computer networks are essential in supporting communication in the company. There are many advantages of using computer networks, for example, communication between clients becomes easier and faster, remote servers through computer networks and client-server applications within the company. Computer network security is very important for the efficiency and effectiveness of computer network performance. Reliable infrastructure in a computer network is very influential for its performance. PT. Megacom company in the field of computer spare part distributor. The problem faced is the absence of good and secure communication technology between the head office, branch offices, and distributors. The purpose of this study is to design a Wide Area Network network between the head office and branch offices of PT. Megacom. This study uses qualitative methods with observation and interview data collection techniques. The results of the study show that in the traceroute experiment during the network test from the head office to the branch, the packet path goes well through the tunnel with fast and secure data access through a VPN network with the designed L2TP/IPSec method.

Role Based Secure Data Access Control for Cost Optimized Cloud Storage Using Data Fragmentation While Maintaining Data Confidentiality

The paper proposes a role-based secure data access control framework for cost-optimized cloud storage, addressing the challenge of maintaining data security, privacy, integrity, and availability at lower cost. The proposed framework incorporates a secure authenticity scheme to protect data during storage or transfer over the cloud. The framework leverages storage cost optimization by compressing high-resolution images and fragmenting them into multiple encrypted chunks using the owner's private key. The proposed approach offers two layers of security, ensuring that only authorized users can decrypt and reconstruct data into its original format. The implementation results depicts that the proposed scheme outperforms existing systems in various aspects, making it a reliable solution for cloud service providers to enhance data security while reducing storage costs.

Lattices-Inspired CP-ABE from LWE Scheme for Data Access and Sharing Based on Blockchain

To address the quantum attacks on number theory-based ciphertext policy attribute-based encryption (CP-ABE), and to avoid private key leakage problems by relying on a trustworthy central authority, we propose a lattice-inspired CP-ABE scheme for data access and sharing based on blockchain in this paper. Firstly, a CP-ABE-based algorithm using learning with errors (LWE) assumption is constructed, which is selective security under linear independence restriction in the random oracle model. Secondly, the blockchain nodes can act as a distributed key management server to offer control over master keys used to generate private keys for different data users that reflect their attributes through launching transactions on the blockchain system. Finally, we develop smart contracts for proving the correctness of proxy re-encryption (PRE) and provide auditability for the whole data-sharing process. Compared with the traditional CP-ABE algorithm, the post-quantum CP-ABE algorithm can significantly improve the computation speed according to the result of the functional and experimental analysis. Moreover, the proposed blockchain-based CP-ABE scheme provides not only multi-cryptography collaboration to enhance the security of data access and sharing but also reduces average transaction response time and throughput.

Blockchain based secure medical data outsourcing with data deduplication in cloud environment

With the rapid growth of cloud computing, an increasing number of individuals and businesses are opting to store their vast data on the cloud in order to cut data maintenance costs and obtain more easy access. The cloud-based Electronic Health Records (EHR) sharing scheme has provided many benefits in recent years, but the centralization of the cloud raises challenges to privacy protection and data security. Blockchain technology is viewed as a possible solution to these challenges because of its unique properties of unforgeability, anonymity, and verifiability. Therefore, a blockchain based secure data outsourcing scheme is proposed in this paper. In the proposed scheme, each activity on outsourcing EHRs is recorded as a transaction on the public blockchain, authenticity is ensured by registration, and secure data access is ensured by keyword search. Initially, the EHR is encrypted by the proposed Enhanced Map Chaotic Encryption (EMCE) algorithm to ensure confidentiality. Then, data de-duplication is performed by the proposed Tri-Level Chunk Hashing (TL-CH) technique to eliminated duplicate records and reduce the storage space. Finally, the integrity of outsourced EHRs is validated by the Third-Party Auditor (TPA). The performance and security analysis show that the proposed scheme can provide solid security against various attacks, and the storage space is reduced.