Identity Management Systems Research Articles

Modelling and Implementation of a Device Based Digital Identity Management System

Identity management concerns transcends technical design issues as users disposition, awareness and attitude play a vital role in the effectiveness of such systems. A framework that supported some important digital identity management system security related features was presented in a previous study. In this current study, an attempt to empirically demonstrate the functioning of these features and to access how user’s awareness, disposition and attitude impact on the proper functioning of such systems was undertaken. To achieve these, a system was modeled and implemented using object oriented analysis and design method. The developed system empirically generates forensic evidence and an implicit mutual authentication scheme. The resulting system developed was tested for these features. The results obtained showed that the framework did provide for reliable forensic evidence generation and it also provided for the implementation of an implicit form of mutual authentication scheme. However, the outcome of a brief test conducted to gauge the reliability of this implicit mutual authentication scheme showed that the support provided was not very reliable based on these users’ factors (awareness, attitude and deposition)

A Review on Different Biometric Template Protection Methods

Biometrics is a universally used automatic identification of persons, depending on their behavioral and biological quality. Biometric authentication represents a significant role in the identity management system. Protection of biometric authentication systems demands to be discussed as there are still some points related to the integrity and public receiving of biometric systems. Feature extraction module of biometric authentication systems, during the period of enrolment, scan the biometric information to determine a set of distinctive features. This set of totally distinct features is recognized as a biometric template. This biometric template is effective in distinguishing between different users. These templates are normally stored during the time of enrolment in a database arranged by the user’s identification data. For the templates of biometrics, protection from attackers is an essential issue, since the compromised template will not be canceled and reissued like a password or token. Template security is not an obvious task because of variations present within the extracted biometric features of users. This paper surveys about different existing approaches for designing a protection scheme for biometric templates with their strengths and boundaries existing in the literature. Some prospect information in designing template protection schemes have been elaborately explained in this paper.

Cybersecurity for next generation healthcare in Qatar

Background: IoMT (Internet of Medical Things) devices (often referred to IoMT domain) have the potential to quickly diagnose and monitor patients outside the hospital by transmitting information through the cloud domain using wireless communication to remotely located medical professionals (user domain). shows the proposed IoMT framework designed to improve the privacy and security of the healthcare infrastructure. Methods: The framework consists of four modules: 1. Intrusion Detection System (IDS) using deep learning (DL) to identify bluetooth-based Denial-of-Service (DoS)-attacks on IoMT devices and is deployed on edge-computing to secure communication between IoMT and edge. 2. IDS is backed up with identity-based cryptography to encrypt the data and communication path. 3. Besides the identity-management system (to authenticate users), it is modeled with aliveness detection using face authentication techniques at the edge to guarantee the confidentiality, integrity, and availability (CIA) of the framework. 4. At the cloud level, another IDS using MUSE (Merged-Hierarchical-Deep-Learning-System-with-Layer-Reuse) is proposed to protect the system against Man-In-The-Middle attacks, while the data is transferred between IoMT-EDGE-CLOUD. Results: These four modules are developed independently by precisely analyzing dependencies. The performance of IDS in terms of precision is 99% and for the identity-management system, the time required to encrypt and decrypt 256-bit key is 66 milliseconds and 220 milliseconds respectively. The true positive rate is 90.1%, which suggests real-time detection and authentication rate. IDS (2) using MUSE (12-layer) the accuracy is >95%, and it consumes 15.7% to 27.63% less time to train than the smaller four-layer model. Conclusion: Our designed models suit edge devices and cloud-based cybersecurity systems and support the fast diagnosis and care required by critically ill patients in the community.

Biometric applications in education

Educational institutions are acquiring novel technologies to help make their processes more efficient and services more attractive for both students and faculty. Biometric technology is one such example that has been implemented in educational institutions with excellent results. In addition to identifying students, access control, and personal data management, it has critical applications to improve the academic domain's teaching/learning processes. Identity management system, class attendance, e-evaluation, security, student motivations, and learning analytics are areas in which biometric technology is most heavily employed. A literature review is performed to present an overview of biometric technology applications for educational purposes, challenges that must overcome to implement biometric technology, and potentially foreshadowing trends effectively. The future seems promising for biometric technology; the biometric technology market is expected to reach a value of USD 94 billion by 2025 at a compound annual growth rate of 36%. New characteristics are under development for commercial applications, such as vascular pattern recognition, ear shape recognition, facial thermography, odor sensing, gait recognition, heartbeat authentication, brain waves, and human body bioacoustics. The biggest challenge this technology must overcome is security and privacy issues, which must be addressed to fully develop the technology to its full potential. It is desirable that this literature review can provide researchers with a sound vision of the potential that biometric technology will have in education.

Seeded Ising Model and Distributed Biometric Template Storage and Matching.

It is known that a variant of Ising model, called Seeded Ising Model, can be used to recover the information content of a biometric template from a fraction of information therein. The method consists in reconstructing the whole template, which is called the intruder template in this paper, using only a small portion of the given template, a partial template. This reconstruction method may pose a security threat to the integrity of a biometric identity management system. In this paper, based on the Seeded Ising Model, we present a systematic analysis of the possible security breach and its probability of accepting the intruder templates as genuine. Detailed statistical experiments on the intruder match rate are also conducted under various scenarios. In particular, we study (1) how best a template is divided into several small pieces called partial templates, each of which is to be stored in a separate silo; (2) how to do the matching by comparing partial templates in the locked-up silos, and letting only the results of these intra-silo comparisons be sent to the central tallying server for final scoring without requiring the whole templates in one location at any time.

Health-ID: A Blockchain-Based Decentralized Identity Management for Remote Healthcare.

COVID-19 has made eHealth an imperative. The pandemic has been a true catalyst for remote eHealth solutions such as teleHealth. Telehealth facilitates care, diagnoses, and treatment remotely, making them more efficient, accessible, and economical. However, they have a centralized identity management system that restricts the interoperability of patient and healthcare provider identification. Thus, creating silos of users that are unable to authenticate themselves beyond their eHealth application’s domain. Furthermore, the consumers of remote eHealth applications are forced to trust their service providers completely. They cannot check whether their eHealth service providers adhere to the regulations to ensure the security and privacy of their identity information. Therefore, we present a blockchain-based decentralized identity management system that allows patients and healthcare providers to identify and authenticate themselves transparently and securely across different eHealth domains. Patients and healthcare providers are uniquely identified by their health identifiers (healthIDs). The identity attributes are attested by a healthcare regulator, indexed on the blockchain, and stored by the identity owner. We implemented smart contracts on an Ethereum consortium blockchain to facilities identification and authentication procedures. We further analyze the performance using different metrics, including transaction gas cost, transaction per second, number of blocks lost, and block propagation time. Parameters including block-time, gas-limit, and sealers are adjusted to achieve the optimal performance of our consortium blockchain.

Proposing a digital identity management framework: A mixed‐method approach

AbstractThis research aims to study the most critical elements of digital identity management to recognize the pattern and the requirements of their use and implementation. Further, an attempt is made to identify and prioritize the criteria and their relevant indicators of digital identity management in the form of a comprehensive framework. To this end a fuzzy multicriteria decision‐making approach was utilized. The framework focuses on a comprehensive perspective to consider digital identity and deals with compiling strategies and operational patterns based on the defined priorities. This applied research with a fundamental approach has a descriptive‐explanatory method as well. Through an in depth‐review of the extant literature and designing an instrument as well as semi‐structure interview the necessary data were collected. The research population consists of 10 experts. By reviewing the theoretical literature of the research, effective factors were identified and screened by the Fuzzy Delphi method leading to six main factors and 31 subfactors. Then, the collected data were analyzed through a hybrid technique known as FDANP (Fuzzy DEMATEL‐ANP) to determine the interactions between the factors and the subfactors and to weigh and prioritize them. The obtained results revealed that “strategic planning” is the most influential factor in digital identity management. Also, the subfactors namely “The use of the maturity model of digital identity management,” “commitment to the whole organization,” “integrity of digital identity management system with other systems,” “integrity of digital identity management program,” and “integrity of the two dimensions of identity management and access management” were ranked as the most influential subfactors of “strategic planning,” respectively. “Access management” was the most permeable factor in digital identity management. It means that this factor is the main problem and could be solved with the help of the influential factors. In addition, subfactors: “Access control to all resources only through the digital identity management system,” “Solution for access management of premium accounts,” “Multi‐factor authentication support,” “Access policy to all resources and information,” and “Determination of the manner of the user access to resources outside the organization” were ranked as the most permeable subfactors.

A Tokenless Cancellable Scheme for Multimodal Biometric Systems

Biometric template protection (BTP) is an open problem for biometric identity management systems. Cancellable biometrics is commonly designed to protect biometric templates with two input factors i.e., biometrics and a token used in template replacement. However, the token is often required to be kept secretly; otherwise, the protected template could be vulnerable to several security attacks and breaches of privacy. In this paper, we propose a tokenless cancellable biometrics scheme called Multimodal Extended Feature Vector (M∙EFV) Hashing that employs an improved XOR encryption/decryption notion to operate on the transformation key. We stress on multimodal biometrics where the real-valued face and fingerprint vectors are fused and embedded into a binarized cancellable template. Specifically, M∙EFV hashing consists of three stages of transformation: 1) normalization and biometric fusion; 2) randomization and binarization; and 3) cancellable template generation. To evaluate the proposed scheme, several benchmarking datasets, i.e., FVC2002, FVC2004 for fingerprint and LFW for face are used in experiments. The verification performance is validated by employing the FVC matching protocol. Various attacks are simulated and analysed in the worst-case scenario. Lastly, unlinkability and revocability properties are examined experimentally.

A Survey on Federated Identity Management Systems Limitation and Solutions

An efficient identity management system has become one of the fundamental requirements for ensuring safe, secure, and transparent use of identifiable information and attributes. Federated Identity Management (FIdM) allows users to distribute their identity information across security domains which increases the portability of their digital identities, and it is considered a promising approach to facilitate secure resource sharing among collaborating participants in heterogeneous IT environments. However, it also raises new architectural challenges and significant security and privacy issues that need to be mitigated. In this paper, we provide a comparison between FIdM architectures, presented the limitations and risks in FIdM system, and discuss the results and proposed solutions.

Blockchain-enabled decentralized identity management: The case of self-sovereign identity in public transportation

Identity management has been ripe for disruption over the past few years due to recurring incidents of data breaches that have led to personal information leaks and identity theft. The rise of blockchain technology has paved the way for the development of self-sovereign identity (SSI)—a new class of user-controlled resilient identity management systems that are enabled by distributed ledger technology. This paper examines how SSI management can be used in a public transportation sector that spans different operators in multiple countries. Specifically, the paper explores how a blockchain-based decentralized identity management system can draw on the SSI framework to provide high-level security and transparency for all involved parties in public transportation ecosystems. Accordingly, building on analyses of the existing public transportation ticketing solutions, we elicited requirements of a comparable system based on the SSI principles. Next, we developed a low-fidelity prototype to showcase how passengers can utilize standardized travel credentials that are valid across different transportation networks in Europe. The proposed system eliminates the need for multiple travel cards (i.e., one for each transportation provider) and empowers individuals to have better control over the use of their identities while they utilize interoperable ticketing systems across Europe. Overall, building on the public transportation case, we offer a proof-of-concept that shows how individuals can better manage their identity credentials via the SSI framework.

Self-sovereign identity

The concept of self-sovereign identity (SSI) describes an identity management system created to operate independently of third-party public or private actors, based on decentralised technological architectures, and designed to prioritise user security, privacy, individual autonomy and self-empowerment.

A User Identity Management System for Cybercrime Control

The rapid growth in the number of online services has lead to an increasing number of different identities managed by each user that makes people feel overloaded and suffer from password fatigue. This poses a serious problem and makes people unable to control and protect their digital identities against identity theft. As organizations grow and adds services such as ecommerce and global remote access of services, controlling who is accessing what kind of information is also becoming a difficult task. This research therefore, presents the development of a user identity management system for cybercrime control. The four stages of an identity management life cycle were developed using some mathematical tools. A two-factor authentication technique was used in developing the system, the traditional username and password was also included with biometric features for robustness. A simulation was run on the model for users ranging from 10 to 1000 using life wild dataset, and accuracy was found to be 98.01%.

Designing and testing a blockchain application for patient identity management in healthcare.

ObjectiveHealthcare systems suffer from a lack of interoperability that creates “data silos,” causing patient linkage and data sharing problems. Blockchain technology’s unique architecture provides individuals greater control over their information and may help address some of the problems related to health data. A multidisciplinary team designed and tested a blockchain application, MediLinker, as a patient-centric identity management system.MethodsThe study used simulated data of “avatars” representing different types of patients. Thirty study participants were enrolled to visit simulated clinics, and perform various activities using MediLinker. Evaluation was based on Bouras’ criteria for patient-centric identity management and on the number of errors in entry and sharing of data by participants.ResultsTwenty-nine of the 30 participants completed all study activities. MediLinker fulfilled all of Bouras’ criteria except for one which was not testable. A majority of data errors were due to user error, such as wrong formatting and misspellings. Generally, the number of errors decreased with time. Due to COVID-19, sprint 2 was completed using “virtual” clinic visits. The number of user errors were less in virtual visits than in personal visits.DiscussionThe evaluation of MediLinker provides some evidence of the potential of a patient-centric identity management system using blockchain technology. The results showed a working system where patients have greater control over their information and can also easily provide consent for use of their data.ConclusionBlockchain applications for identity management hold great promise for use in healthcare but further research is needed before real-world adoption.

A Trusted Approach for Decentralised and Privacy-Preserving Identity Management

Identity Management (IdM) systems have traditionally relied on a centralized model prone to privacy, trust, and security problems, like potential massive data breaches or identity spoofing. Identity providers accumulate excessive power that might allow them to become a big brother, analyzing and storing as much data as possible. Users should be able to trust identity providers and manage their personal information straightforwardly without compromising their privacy. The European OLYMPUS project introduces a distributed approach for IdM based on enhanced Attribute-Based Credentials (ABC) that splits the role of Identity Provider to limit their influence and chances to become a unique point of failure. However, the trust relationship between service providers, users, and identity providers is still a gap in those kinds of privacy-preserving ABC systems. Decentralized technologies are an opportunity to break away from the centralized model and propose systems that respect privacy while increasing users' trust. This paper presents an evolution of the OLYMPUS architecture, maintaining all the privacy features and incorporating distributed ledger technologies to enhance trust and security in online transactions and IdM systems. The proposed system has been implemented, tested, and validated, showing its performance and feasibility to manage user's identity in a fully privacy-preserving, distributed and reliable way.

An evaluation of identity and access management systems

One of the most critical issues of all of networks types that integrate the both of wired and wireless technologies is the performance and applicability of the electronic authentication and identification techniques. These schemes involve various technologies of different levels of security. This research presents a comparative study of six IDAM available tools, based on the three characteristics (ease of use, usefulness, and user's satisfaction), which build targets to be achieved in order to gain quality in software. The tools compared in this study are Log Mote, Oracle ID management, Tivoli Identity Manager, NetIQ-Novell, Access Sentinel, and Active Directory. In order to enable users to access the available resources in a secure way, we propose a novel architecture of IDAM. The proposed architecture basically has several advantages like, autonomy, comprehensive and systematic, standardization, and scalability.

A secure identity and access management system for decentralising user data using blockchain

A secure identity and access management system for decentralising user data using blockchain

An evaluation of identity and access management systems

One of the most critical issues of all of networks types that integrate the both of wired and wireless technologies is the performance and applicability of the electronic authentication and identification techniques. These schemes involve various technologies of different levels of security. This research presents a comparative study of six IDAM available tools, based on the three characteristics (ease of use, usefulness, and user's satisfaction), which build targets to be achieved in order to gain quality in software. The tools compared in this study are Log Mote, Oracle ID management, Tivoli Identity Manager, NetIQ-Novell, Access Sentinel, and Active Directory. In order to enable users to access the available resources in a secure way, we propose a novel architecture of IDAM. The proposed architecture basically has several advantages like, autonomy, comprehensive and systematic, standardization, and scalability.

Efficient biometric-based identity management on the Blockchain for smart industrial applications

In this work, we propose a new Blockchain-based Identity Management system for smart industry. First, we describe an efficient biometric-based anonymous credential scheme, which supports selective disclosure, suspension/thaw and revocation of credentials/entities. Our system provides non-transferability through a freshly computed hidden biometric attribute, which is generated using a secure fuzzy extractor during each authentication. This mechanism combined with offchain storage guarantees GDPR compliance, which is required for protecting user’s data. We define blinded (Brands) DLRep scheme to provide multi-show unlinkability, which is a lacking feature in Brands’ credential based systems. For larger organizations, we re-design the system by replacing the Merkle Tree with an accumulator to improve scalability. The new system enables auditing by adapting the standard Industrial IoT (IIoT) Identity Management Lifecycle to Blockchain. Finally, we show that the new proposal outperforms BASS, i.e. the most recent blockchain-based anonymous credential scheme designed for smart industry. The computational cost at the user-side (can be a weak IoT device) of our scheme is 8-times less than that of BASS. Thus, our system is more suitable for IIoT.

Decentralized Identity Systems: Architecture, Challenges, Solutions and Future Directions

Due to the exponential rise of the Internet in the last two decades, the digital presence has seen an enormous increase. Today, billions of people, devices and objects are digitally connected making the interactions much easier than before. To securely establish this connectivity in the digital era, proving digital identities has become crucial. Due to this, a growing number of organizations are building solutions that establish, verify and manage digital identities. Yet, a solution whereby digital identities and their associated data are efficiently managed is still far from being achieved. To fully understand the reason behind this lack, this paper provides a detailed state of the art related to identity management systems. It overviews traditional systems, analyses their strengths and limitations. This work highly focuses on the novel decentralized identity systems based on blockchain; a complete study describing their architecture, components, lifecycle and workflow is detailed. Additionally, solutions enabling decentralized identity are discussed, analysed and compared according to the ten principles of self-sovereign identity. Lastly, the challenges hindering the shift toward the fully decentralized identity paradigm are discussed.

Optimal feature selection-based biometric key management for identity management system: Emotion oriented facial biometric system

Identity management systems with biometric key binding make digital transactions secure and reliable. A novel methodology is proposed to develop an intelligent key management system using facial emotions. Key binding with facial emotions makes use of an intrinsic user specific trait facilitating a more natural computer to human interaction. The proposed system utilizes metaheuristic swarm intelligence based optimization techniques to extract optimal features. The work demonstrates key binding by encrypting an image with a secret key bound to optimal features extracted from facial emotions. Efficiency and correctness of proposed key management is validated by successful decryption at receiving end with any one of the enrolled emotions given as input. Deer Hunting Optimization Algorithm and Chicken Swarm Optimization are merged to select optimal features from facial emotions. The derived algorithm is called Fitness Sorted Deer Hunting Optimization Algorithm with Rooster Update. Seven facial emotions — anger, disgust, fear, happiness, sadness, surprise and neutral are used to extract optimal features from Japanese Female Facial Expressions and Yale Facial datasets to train the neural network. Proposed work achieved better performance results over state-of-art optimization algorithms such as whale optimization algorithm, grey wolf optimization, chicken swarm optimization and deer hunting optimization algorithm. Accuracy of proposed model is 2.2% better than deer hunting optimization algorithm and 12.3% better than chicken swarm optimization for a key length 80.