Secure Data Access Research Articles

A smart secure healthcare monitoring system with Internet of Medical Things

The new era of information technologies made smart healthcare by including edge, Internet of Things (loT), Internet of Medical Things (IoMT), cloud computing etc. This adaptation has partially replaced the old medical system, making healthcare more efficient, easy, and customized. Wireless medical sensors are used in the smart healthcare sector to capture the patient’s health data and transmit it to the remote server for treatment or diagnostic purposes. Every time a cloud-based solution is adopted to collect and preserve the sensitive and personal health information. This collected patient data is shared between the different stakeholders across the network. Due to this, healthcare systems are vulnerable to confidentiality, integrity and privacy threats. Secure data access is a big challenge in such systems. In this paper, a lightweight authentication technique with the privacy-preserving schema using fully homomorphic encryption is proposed. This approach can be used for a secure access of patient data through online mode, and also the data can be shared in an encrypted format for desired purposes of stakeholders. The proposed authentication scheme is for Internet of Medical Things that can resist all network attacks and is easy to implement. The performance analysis of the proposed work shows that overall execution time (80.03%), communication cost (15.62%) and energy consumption (79.19%) is reduced in comparison with existing work.

Hybrid Multi-User Based Cloud Data Security for Medical Decision Learning Patterns

Machine learning plays a vital role in the real-time cloud based medical computing systems. However, most of the computing servers are independent of data security and recovery scheme in multiple virtual machines due to high computing cost and time. Also these cloud based medical applications require static security parameters for cloud data security. Cloud based medical applications require multiple servers in order to store medical records or machine learning patterns for decision making. Due to high computational memory and time, these cloud systems require an efficient data security framework in order to provide strong data access control among the multiple users. In this paper, a hybrid cloud data security framework is developed to improve the data security on the large machine learning patterns in real-time cloud computing environment. This work is implemented in two phases, data replication phase and multi-user data access security phase. Initially, machine decision patterns are replicated among the multiple servers for data recovering phase. In the multi-access cloud data security framework, a hybrid multi-access key based data encryption and decryption model is implemented on the large machine learning medical patterns for data recovery and security process. Experimental results proved that the present two-phase data recovering and security framework has better computational efficiency than the conventional approaches on large medical decision patterns.

Whirlpool Hash Mutual Biometric Serpent Authentication (WPHMBSA) for secured data access in cloud environment

Cloud systems allow data sharing capabilities for providing several benefits to users and organizations. However, authentication accuracy (AA) was not improved, and time consumption was not reduced. To increase authentication accuracy, Whirlpool Hash Mutual Biometric Serpent Authentication (WPHMBSA) Technique is designed to access data on a server in a secured manner. During the registration process, users’ data are registered and stored on the server. After registering, the cloud server generates an ID and password for every registered user. For authentication, the user needs to login with an ID and password to the cloud server. During authentication, WPHMBSA Technique authenticates the biometric keys of the users. When a user is legitimate, WPHMBSA Technique confirms their authenticity to the server. Experimental evaluation of the WPHMBSA Technique and existing methods are performed by various parameters with the amount of cloud user’s information. The experimental results show that the WPHMBSA Technique obtains high accuracy and confidentiality rate within minimum time.

SISTEM INFORMASI PERHIMPUNAN MAHASISWA KATOLIK REPUBLIK INDONESIA SANTU FRANSISKUS XAVERIUS CABANG KUPANG BERBASIS MOBILE WEB

Indonesian Catholic Student Association (PMKRI) St. Fransiskus Xaverius Kupang Branch was established on October 25, 1963, which is one of the student organizations with national standards. This organization includes students who are pursuing higher education in Kupang City from 21 regencies in East Nusa Tenggara Province. A mobile web-based information system is one of the requirements for a national organization that ensures the security and speed of data access. In this case, especially the Kupang branch of PMKRI which has not utilized technology.

DSLN: Securing Internet of Things Through RF Fingerprint Recognition in Low-SNR Settings

The explosive growth of Internet of Things (IoT) has mandated the security of data access. Although authentication methods can enhance network security, their vulnerability to malicious attacks may be a barrier for the wide deployments in IoT scenarios. To address the security issue, we advocate the use of physical-layer security through radio-frequency (RF) fingerprint recognition. Observing that most RF fingerprint recognition methods show a degradation of performance under low signal-to-noise ratio (SNR) environments, we present a dynamic shrinkage learning network (DSLN) to enhance security for IoT applications, particularly in the setting of low SNR. We design a novel dynamic shrinkage threshold for improving the accuracy of recognition under low-SNR environments. Additionally, we design an identity shortcut for reducing the running time of RF fingerprint recognition. In comparison with convolutional neural network (CNN), recurrent neural network (RNN), and a hybrid CNN+RNN network (CRNN), our proposed DSLN yields accuracy improvements of up to 20%. Moreover, DSLN can reduce the running time by up to 60%, indicating its great potential to a real-time IoT system, e.g., an intelligent automotive system.

Blockchain in churn prediction based telecommunication system on climatic weather application

For better customer service and customer retention, businesses take proactive measures, including troubleshooting and solving potential challenges promptly. Blockchain technology integrates different recognition techniques of distributed pattern for monitoring database of a dedicated network and has proven a very promising technology. An automated pattern recognition decentralizes and distributes customized specific data. Machine learning, originated from artificial intelligence is primarily related to recognition of behavior patterns. Methods like knowledge discovery in database (KDD) and data mining focus on unsupervised approaches and are widely used in business and climatic weather applications. Blockchain addresses data-security concerns and builds trust by creating distributed ledger. Theft, willful fraud, software and hardware are considered by blockchain in data protection. Blockchain has greater significant feature as it makes the secure data access without enabling the central management entity. Two design features of blockchain technology help in this task. Recommended customer data pattern recognition technique using blockchain may eliminate all these problems. Two kinds of cryptographic algorithms employed in blockchain are asymmetric-key algorithms and hash functions. The current study analyzes the asymmetric cryptography approach along with key pair which supports in system security. Recurrent neural network (RNN) and support vector machine (SVM) classifier techniques consider both old customers and new customers as stable. The predictive model aids in identifying customers at churn risk in the telecommunication system. Existing proactive methods are unable to explain difficulties in customer interaction understanding and meeting their genuine needs. The proposed model organizes the customer situation and designs a customer proactive re-engagement over mobile-based telecommunication systems. Performance measures like churn prediction, classifier, confusion matrix, machine learning in the telecommunication system are used to evaluate and validate the results.

Аналітичне сховище для великих потокових даних

A concept for organizing an analytical data warehouse has been developed, which includes a method of interaction between data producers and a repository, a method of data circuit control, a method of data streaming, a method of storing initial data, a method of data processing and a method of providing secure data access. Other concepts on the market are discussed, namely: SDLF as the leading standard recommended by AWS, IronSource DL using Upsolver, SimilarWeb DL using Upsolver. A comparative analysis was conducted (mostly with SDLF, as its implementation is open, and the implementation by private companies is hidden). The advantages of the proposed concept over the existing ones are examined in detail. Recommendations on how to integrate the concept with data schema control applications are given. A service for streaming data using Apache Beam in Java has been developed. A repository architecture for analytics was designed and developed. A data schema management model was developed as well as a data schema management model and a model for secure access to data. The research that has been conducted can be improved by the experience of implementing the concept in business, as well as by collecting and systematizing knowledge about other standards that will be created.

Ensuring the ethical use of big data: lessons from secure data access

Big data holds great potential for research and for society, large volumes of varied data can be produced and made available to researchers much faster compared to ‘traditional’ data. Whilst this potential is recognized, there are ethical concerns which users of big data must consider. With the volume and variety of information in big data, comes a greater risk of disclosure. Researchers and data access services working with highly detailed and sensitive, secure data have grappled with this for many years. The sector has developed both ethical frameworks and statistical disclosure control techniques which could be utilized by those working with big data. We discuss the challenges, present some of the frameworks and techniques and conclude with recommendations for secure data access of big data.

Optimized Genetic Algorithm and Extended Diffie Hellman as an Effectual Approach for DOS-Attack Detection in Cloud

Cloud computing is a mode to increase competence and capabilities devoid of investing in any infrastructure. It seems that in cloud computing environment the major problem that ensure the secure communication and protect responsive data in open networks from unauthorised access. These days it seems the headlines are jam-packed with stories about security breaches to these services; that result in the leak of a large amount of private data of the users. As cloud computing can offer new computing benefits, but it faces soaring risks, specifically on the security side where DOS attacks can make cloud services unavailable. This paper aims to turn up an effective method of detecting DOS attacks with an optimized Genetic algorithm and extended version of Diffie-hellman algorithm. To prevent data loss or corruption caused by the insiders in the cloud, Optimized Genetic Algorithm (OGA) is utilized, which effectively recovers the data and retrieve it if the missed data without loss. It is then followed with the decryption process as if requested by the user. An optimized path assortment for information broadcast proves to be an effective method in the cloud computing atmosphere. The proposed framework ensures certification and paves way for secure data access in an unauthorized network, with improved performance. It successfully assure the high level of protection of the transmission and data transmitted. And concurrently reduce the communication complexities. To reduce time complexity and detect the attackers by mutual secret key that is brought on using extended version of Diffie-hellman to endorse available key generation.

Miyaguchi–Preneel Snefru Cryptographic Blockchain and Maximum Likelihood Consensus Deep Convolutional Q-Learning for Secure Data Access in E-Learning

E-learning is a novel perception that includes all educational activities of an individual or group working online, synchronously or asynchronously, connecting via various devices through the internet. The e-learning system has faced some concerns related to security, availability and reliability. To overcome these challenges, an important security approach is required to preserve the data of the e-learning system. A novel Miyaguchi–Preneel Snefru Cryptographic Blockchain and Maximum Likelihood Consensus Deep Convolutional Q-Learning Network (MPSCB-MLCDCQN) is introduced with three different processes namely data collection, access control and data analysis. In the proposed MPSCB-MLCDCQN, Internet of Things (IoT) devices are employed to sense and collect student activities during the e-learning process. Secondly, secure data access is performed through the Miyaguchi–Preneel Snefru hashes decentralized blockchain technology for avoiding unauthorized access. Finally, the Maximum Likelihood Consensus Deep Convolutional Q-Learning Network (MLCDCQN) is applied to analyze the student data collected from the IoT devices to make optimal action. The student data are analyzed using the Maximum Likelihood Consensus regression function by learning the features of input data and predicting the student performance behavior with higher accuracy. A comprehensive experiment of the proposed MPSCB-MLCDCQN is conducted using e-learning activities' dataset in a CloudSim simulator with certain performance metrics such as confidentiality rate, data integrity rate, processing time and prediction accuracy with respect to a number of student data. The results discussed show that the MPSCB-MLCDCQN technique provides improved performance in terms of achieving higher security and data analysis than the existing methods.

Analysis of Critical Factors in Manufacturing by Adopting a Cloud Computing Service

The advantages of a cloud computing service are cost advantages, availability, scalability, flexibility, reduced time to market, and dynamic access to computing resources. Enterprises can improve the successful adoption rate of cloud computing services if they understand the critical factors. To find critical factors, this study first reviewed the literature and established a three-layer hierarchical factor table for adopting a cloud computing service based on the Technology-Organization-Environment framework. Then, a hybrid method that combines two multi-criteria decision-making tools—called the Fuzzy Analytic Network Process method and the concept of VlseKriterijumska Optimizacija I Kompromisno Resenje acceptable advantage—was used to objectively identify critical factors for the adoption of a cloud computing service, replacing the subjective decision of the authors. The results of this study determined five critical factors, namely data access security, information transmission security, senior management support, fallback cloud management, and employee acceptance. Finally, the paper presents the findings and implications of the study.

What makes administrative data “research-ready”? A systematic review and thematic analysis of published literature

IntroductionAdministrative data are a valuable research resource, but are under-utilised in the UK due to governance, technical and other barriers (e.g., the time and effort taken to gain secure data access). In recent years, there has been considerable government investment in making administrative data “research-ready”, but there is no definition of what this term means. A common understanding of what constitutes research-ready administrative data is needed to establish clear principles and frameworks for their development and the realisation of their full research potential.ObjectiveTo define the characteristics of research-ready administrative data based on a systematic review and synthesis of existing literature.MethodsOn 29th June 2021, we systematically searched seven electronic databases for (1) peer-reviewed literature (2) related to research-ready administrative data (3) written in the English language. Following supplementary searches and snowball screening, we conducted a thematic analysis of the identified relevant literature.ResultsOverall, we screened 2,375 records and identified 38 relevant studies published between 2012 and 2021. Most related to administrative data from the UK and US and particularly to health data. The term research-ready was used inconsistently in the literature and there was some conflation with the concept of data being ready for statistical analysis. From the thematic analysis, we identified five defining characteristics of research-ready administrative data: (a) accessible, (b) broad, (c) curated, (d) documented and (e) enhanced for research purposes.ConclusionsOur proposed characteristics of research-ready administrative data could act as a starting point to help data owners and researchers develop common principles and standards. In the more immediate term, the proposed characteristics are a useful framework for cataloguing existing research-ready administrative databases and relevant resources that can support their development.

Improved Secure Identification-Based Multilevel Structure of Data Sharing in Cloud Environments

The Cloud Computing Environment (CCE) developed for using the dynamic cloud is the ability of software and services likely to grow with any business. It has transformed the methodology for storing the enterprise data, accessing the data, and Data Sharing (DS). Big data frame a constant way of uploading and sharing the cloud data in a hierarchical architecture with different kinds of separate privileges to access the data. With the requirement of vast volumes of storage area in the CCEs, capturing a secured data access framework is an important issue. This paper proposes an Improved Secure Identification-based Multilevel Structure of Data Sharing (ISIMSDS) to hold the DS of big data in CCEs. The complex file partitioning technique is proposed to verify the access privilege context for sharing data in complex CCEs. An access control Encryption Method (EM) is used to improve the encryption. The Complexity is measured to increase the authentication standard. The active attack is protected using this ISIMSDS methodology. Our proposed ISIMSDS method assists in diminishing the Complexity whenever the user’s population is increasing rapidly. The security analysis proves that the proposed ISIMSDS methodology is more secure against the chosen-PlainText (PT) attack and provides more efficient computation and storage space than the related methods. The performance of the proposed ISIMSDS methodology provides more efficiency in communication costs such as encryption, decryption, and retrieval of the data.

Authorized Shared Electronic Medical Record System with Proxy Re-Encryption and Blockchain Technology

With the popularity of the internet 5G network, the network constructions of hospitals have also rapidly developed. Operations management in the healthcare system is becoming paperless, for example, via a shared electronic medical record (EMR) system. A shared electronic medical record system plays an important role in reducing diagnosis costs and improving diagnostic accuracy. In the traditional electronic medical record system, centralized database storage is typically used. Once there is a problem with the data storage, it could cause data privacy disclosure and security risks. Blockchain is tamper-proof and data traceable. It can ensure the security and correctness of data. Proxy re-encryption technology can ensure the safe sharing and transmission of relatively sensitive data. Based on the above situation, we propose an electronic medical record system based on consortium blockchain and proxy re-encryption to solve the problem of EMR security sharing. Electronic equipment in this process is connected to the blockchain network, and the security of data access is ensured through the automatic execution of blockchain chaincodes; the attribute-based access control method ensures fine-grained access to the data and improves the system security. Compared with the existing electronic medical records based on cloud storage, the system not only realizes the sharing of electronic medical records, but it also has advantages in privacy protection, access control, data security, etc.

Multi party secure data access management in cloud using user centric block chain data encryption

Cloud is the most dominant platform being used by different organizations towards providing service access to their users and customers. Services provided are intended to store and maintain data belongs to the organizations. Access restriction and data access management are identified as key issue at the point of storage management in cloud. The data security in cloud decides the Quality of Service (QoS) performance of the entire environment. Towards this, different approaches available to handle the storage management and access restriction issues. Still, the approaches are not up to the expected range of performance to maximize the QoS performance. Also, the methods faces higher data leakage, security issues as well as higher impact of tampering, which increases the requirement of block chains towards secure data access. To improve the performance, an efficient multi party secure data access management (MSDAM) is presented in this article. The method is focused to provide data handle in different parties which perform authentication on the data update requests. Also, the method distributes the key set and scheme set for different user at different session which is framed according to user centric features. The method initializes key sets and scheme sets to be distributed to the user in a least fact randomization model. Also, the method generates block chains for the user data which is encrypted using User Centric Block chain Encryption (UCBE) scheme where the key and schemes are selected with randomization technique. Similarly, the hash code has been generated using Distancing method. The proposed method improves the performance in all the QoS parameters of the cloud.

Data Access Control Based on Blockchain in Medical Cyber Physical Systems

The current medical cyber physical systems involve a wide range of institutions and a large number of participants. Data sharing among distributed medical institutions is already a development trend. However, the security is worrying; e.g., the access to medical data lacks uniformity and standardization. What is more, data is easy to be tampered with and leaked. This has a very negative impact on the medical industry. Therefore, a strict and reliable access control mechanism for data in the medical cyber physical systems is a prerequisite for ensuring the implementation of modern medical functions. We deal with how to design effective access control in medical cyber physical systems. Combined with blockchain technology, we design the medical cyber physical systems based on blockchain data access control mechanism and unite data in the chain of union Fabric network resources access control. We qualitatively classify medical data, define the weight level of different data, design a medical data access framework based on blockchain, build an applicable model, formulate access control strategy, and specify the role assignment and access task matching of users, so as to achieve secure and effective data access control. The Hyperledger Fabric network is established as the alliance chain for managing access control rights distribution through smart contracts so as to achieve case-based medical data access control under the blockchain.

Блокчейн-технології в управлінні комунікаціями інфраструктурних проектів

The subject of research in the article is the processes and technologies of communication management of infrastructural projects. The possibilities of using blockchain technology in the field of project management are considered. The goal of work: improving the information security of infrastructure projects. The risks of stakeholder communications will be reduced by increasing the security of data access and reducing the time for their processing, which in turn will provide more flexible project management. The tasks of the work: to analyze the current state of development of blockchain technology and conduct a comparative analysis of technology and modern generally accepted management methods, give examples of implementation, determine the advantages of blockchain technology in modern conditions; analyze the benefits of using smart contracts in communication management, apply the smart contract life cycle model in an infrastructure project. Research methods: systems analysis, design approach, structural modeling, instrument Geth, programming language Solidity. The following results were obtained. The main directions of development and implementation of blockchain technology are characterized, examples of the use of blockchain technology in various industries are collected and analyzed, the main advantages and disadvantages of the technology are identified, a comparative analysis of blockchain technology and classical project management methods is carried out, the possibilities of using blockchain technology in the field of project management are described, the main the possibility of implementing reasonable contracts, the advantages and disadvantages of reasonable contracts are identified, the advantages and disadvantages of the instrument of reasonable contracts are analyzed in comparison with the traditional approach. The smart contract life cycle model presents the creation stages, installation to the blockchain contract managing, and contract completion. Provided an example of the smart contract used for the complex financial project, which reduced the risk of project failures. Conclusion. The scientific novelty of the obtained results is in the improvement of the project management life cycle model through the further development of the smart contract model. This allows to increase information security, reduce possible risks and guarantee the implementation of an infrastructure project through the use of blockchain technology in comparison with classical project management methods.

Secure and Reliable Data sharing scheme using Attribute-based Encryption with weighted attribute-based Encryption in Cloud Environment

The field of data management has been reformed by the Cloud computing technologies which offered valuable establishments and amended the storage restrictions barriers for its users. In large enterprises the cloud has been extensively used for implementation due to its benefits. There are still lot of security threats for the data in the cloud. The data owners suffer from its privacy issues which are considered as one of the major concerns. Data privacy can be secured by employing some of the existing methods such as Attribute-based Encryption (ABE). Yet, the security issues are prevailing largely over the cloud. In this research a secured data access control is proposed using the Advanced Encryption Standard (AES) combined with a weighted attribute-based Encryption (AES-WABE). To encrypt the data, the access control policies are used and weight is assigned according to its significance of each attribute. The outsourced data is stored by the cloud service provider and the attribute authority based on the weight that updates the attributes. To minimize the computational overload the data file is accessed by the receiver corresponding to its weight. The proposed procedure provides resistance for collusion, multiple user security with control of fine-grained access based on protection, reliability and efficiency. On concerning the data collaboration and confidentiality, the performance rating is done related with the Cipher-text Policy–Attribute-based Encryption (CP-ABE) and the hybrid attribute-based encryption (HABE) scheme, access control flexibility, limited decryption, full delegation, verification and partial signing.

APPLICATION OF THE SECURE HASHING ALGORITHM (SHA) METHOD AND ROLE-BASED ACCESS SECURITY AUTHENTICATION IN LARAVEL 7

Information systems that are well made will produce applications that have optimal performance for all accesses to the system. The problem that is often encountered is a system that is easy to hack and tamper with entering from the login system, causing the system to experience data security failure and is accompanied by very dangerous file and database damage. The Laravel Framework provides access security that is Progressive, Scalable and Community Framework to be developed by information system developers, but for the default system from Laravel 7 it is still not enough to provide a solution for data security and access levels for users. Then additional systems are needed in the form of: Secure Hashing Algorithm (SHA), Multi Level Access Algorithm (MLA) and Middleware Checking Access System to overcome data security problems, access and system damage. Testing on the modified login system from the Laravel 7 framework this study has been successful to map users, their access levels, block SQL injection and secure data access accordingly

Trust Level Evaluation based Asymmetric Cryptography Protocol for Flexible Access Control in Fog Computing

The foremost problems in the fog-enabled cloud computing model are security guarantees and data Access Control (AC) because of the imitation of data by invaders. To enhance the security of this system, an Extended Communication Latency-based Authentication Scheme (ECLAS) that solves the mobility and similar locality legitimate login failures via applying two-factor authentication and a keystroke dynamics computation with obfuscated Round Trip Latency (RTL) of each users. But, the data need to accessed by other user should fulfill an be expected authentication and defend against dishonest access or login. So, data AC at cloud or fog nodes is greatly essential in many applications of fog-enabled cloud systems. Therefore in this article, a Flexible AC (FAC) protocol is introduced with the ECLAS for controlling the data access in fog-enabled cloud systems according to the trust estimated by the user in the cloud and reputations created by the amount of fog nodes in a flexible way via applying the Elliptic Curve Cryptography (ECC) and Proxy Re-Encryption (PRE). In this scheme, multi-dimensional controls are proposed on cloud and fog data access according to the strategies set by the user. The user encrypts its information with asymmetric secret key and this key is split into many segments for supporting different control policies. So, the user encrypts various segments of secret key with different encryption keys which are accordingly handled by the user and an amount of fog nodes regarding various reputation characteristics in different scenarios. Then, the user or fog nodes manage the data access using data encryption by the user. Finally, the experimental results exhibit the effectiveness of the proposed FAC as compared to the state-of-the-art AC schemes.