Developing an IoT Identity Management System Using Blockchain

Nowadays, people around the world completely depend and mostly use the Internet to maintain communication, contact with family, friends and with people around the world, access and exchange information, and enjoy multimedia communication. As the use of internet increase then users those who use internet and Access the information using internet in the organization or outside organization also increase. User Data security is very tedious and important part of IT system and its user lifecycle control system. Because of this the reason user data security is always consider while designing security systems for an organization. Modern approaches are to maintain the track of users and records of user access, Identity management systems and Access Management Systems are used. Identity management system help to provide a super-set of user provisioning systems that provide easy management of user credentials and their identity information to users and others those who need that information. Similarly Access Management Systems provide strong authentication and authorization solution using SSO, WebSEAL, and policy-based approach to identify who can access the resource at what level. The new research and approaches provide such a new functions base on organization policies that help to re-engine the access of user base on security procedures to the resources which are available. This paper provides an overview of the Identity Management Systems Access Management System and Federated Identity Manager that how they are use to manage the user security and also the challenges or risks in implementing a Secure system.

Blockchain (BC) has recently paved the way for developing Decentralized Identity Management (IdM) systems for different information systems. Researchers widely use it to develop decentralized IdM systems for the Health Internet of Things (HIoT). HIoT is considered a vulnerable system that produces and processes sensitive data. BC-based IdM systems have the potential to be more secure and privacy-aware than centralized IdM systems. However, many studies have shown potential security risks to using BC. A Systematic Literature Review (SLR) conducted by the authors on BC-based IdM systems in HIoT systems showed a lack of comprehensive security and risk management frameworks for BC-based IdM systems in HIoT. Conducting a further SLR focusing on risk management and supplemented by Grey Literature (GL), in this paper, a security taxonomy, security framework, and cybersecurity risk management framework for the HIoT BC-IdM systems are identified and proposed. The cybersecurity risk management framework will significantly assist developers, researchers, and organizations in developing a secure BC-based IdM to ensure HIoT users’ data privacy and security.

Identity management (IdM) systems employ Identity Providers (IdPs), as guardians of users' critical information. However, Distributed Denial-of-Service (DDoS) attacks can make IdPs operations unavailable, compromising legitimate users. In the literature, the main countermeasures against DDoS attacks are based on either the application of external resources to extend the system lifetime (replication) or on the DDoS attacks detection. The first approach increases the solutions cost, and in general the second one is prone to high rates of false negatives and/or false positives. This work presents SAMOS, a first scheme to mitigate DDoS attacks in IdM systems through a novel approach: organizations of IdP clustering using optimization techniques. SAMOS is started based on the monitoring of processing and memory resources, differently from the solutions in the literature that are started based on the attack detection by the network traffic analysis. SAMOS minimizes the DDoS attacks effects using operational IdPs in the system, differently from the works that employ external computer resources. Results considering data from real IdM systems indicate the scheme viability.

The rapid expansion of Internet of Things (IoT) devices has highlighted the shortcomings of traditional centralized identity management systems, which often suffer from single points of failure, high latency, and limited scalability. These challenges are particularly significant in IoT environments with limited resources, where secure and efficient identity management is crucial for real-time data processing and decision-making. This paper introduces a consortium blockchain-based IoT identity management system enhanced by fog computing. By utilizing blockchain’s decentralized and tamper-resistant features, the system secures identity management, while fog computing minimizes latency by processing data closer to its source. Our system is designed to scale effectively, even in densely populated IoT deployments, while maintaining low energy consumption and high throughput. Simulation results show notable reductions in latency and improvements in throughput, with the system achieving an average latency of 175.15 ms for registration operations with a 0.35 MB payload. The system’s robustness is further demonstrated by its resilience to common IoT security threats, such as man-in-the-middle attacks and node compromise. Key contributions include the innovative integration of blockchain and fog computing, enhanced scalability and efficiency, improved security through decentralized identity management, and adaptability to emerging technologies like quantum-resistant cryptography.

PurposeThe aim of this paper is to evaluate the use of blockchain for identity management (IdM) in the context of the Internet of things (IoT) while focusing on privacy-preserving approaches and its applications to healthcare scenarios.Design/methodology/approachThe paper describes the most relevant IdM systems focusing on privacy preserving with or without blockchain and evaluates them against ten selected features grouped into three categories: privacy, usability and IoT. Then, it is important to analyze whether blockchain should be used in all scenarios, according to the importance of each feature for different use cases.FindingsBased on analysis of existing systems, Sovrin is the IdM system that covers more features and is based on blockchain. For each of the evaluated use cases, Sovrin and UniquID were the chosen systems.Research limitations/implicationsThis paper opens new lines of research for IdM systems in IoT, including challenges related to device identity definition, privacy preserving and new security mechanisms.Originality/valueThis paper contributes to the ongoing research in IdM systems for IoT. The adequacy of blockchain is not only analyzed considering the technology; instead the authors analyze its application to real environments considering the required features for each use case.

Digital identity is the key element of digital transformation in representing any real-world entity in the digital form. To ensure a successful digital future the requirement for an effective digital identity is paramount, especially as demand increases for digital services. Several Identity Management (IDM) systems are developed to cope with identity effectively, nonetheless, existing IDM systems have some limitations corresponding to identity and its management such as sovereignty, storage and access control, security, privacy and safeguarding, all of which require further improvement. Self-Sovereign Identity (SSI) is an emerging IDM system which incorporates several required features to ensure that identity is sovereign, secure, reliable and generic. It is an evolving IDM system, thus it is essential to analyse its various features to determine its effectiveness in coping with the dynamic requirements of identity and its current challenges. This paper proposes numerous governing principles of SSI to analyse any SSI ecosystem and its effectiveness. Later, based on the proposed governing principles of SSI, it performs a comparative analysis of the two most popular SSI ecosystems uPort and Sovrin to present their effectiveness and limitations.

As digital platforms expand globally, ensuring data sovereignty across regions has emerged as a critical concern, particularly in identity management systems. Existing identity architectures often centralize data storage and control, creating compliance risks in multi-jurisdictional deployments. This research proposes a novel architecture for multi-regional Identity and Access Management (IAM) systems to preserve data sovereignty while enabling unified customer identity experiences. The architecture ensures region-specific data storage, consent-aware data sharing, and regulatory compliance.

Large scale networked systems, such as Identity Management (IdM) systems and software defined networks (SDN), have contributed to technological evolution. They simplify user and network device management. However, they strengthen Distributed Denial-of-Services (DDoS) attacks. These attacks are able to compromise system availability and harm legitimate users. The main approaches against DDoS attacks apply external resources (replication) or try to detect DDoS attacks. The first approach increases solution cost. The second is prone to high false positives. In other contexts, research into resilient approaches has increased for addressing emergent threats. In this work, we advocate that networked systems can self-manage to provide resilience. We propose a framework to guide the system design to follow the ideas defended in this thesis. The framework comprises the survival, collaboration, and analysis modules. Following the framework, networked systems can preserve their lifetime without external computer resources. The DDoS attack mitigation process starts when the system capacity overcomes a pre-established threshold. A protocol and a scheme showcase the framework over IdM systems and SDN. We conducted performance evaluations by experiments and simulations. Results show an increase in throughput and a decrease in latency of essential services when we use the proposed framework.

This paper describes the identity management system (IdMS) by defining system and user requirements. Additionally, it introduces the IdMS concept that approaches the things identity management. Moreover, the paper deeply describes the IdMS features using unified modelling language (UML) diagrams such as class, system, and sequence diagrams to show the main system functionalities. Ultimately, the suggested system is evaluated by comparing it with the existing systems and discussing the fulfilment of user and system requirements.

The proliferation of Internet of Things (IoT) devices in smart environments has created unprecedented challenges in identity management and security. Traditional centralized identity management systems face scalability, privacy, and single-point-of-failure issues when applied to IoT ecosystems. This paper presents a novel blockchain-based framework for decentralized identity management in smart IoT environments. Our proposed framework leverages blockchain technology's immutable ledger, smart contracts, and cryptographic mechanisms to provide secure, scalable, and privacy-preserving identity management for IoT devices. The framework incorporates a multi-layered security architecture that includes device authentication, access control, and identity verification mechanisms. Experimental results demonstrate that our approach achieves 99.7% authentication accuracy with reduced latency compared to traditional centralized systems. The framework also provides enhanced privacy protection through zero-knowledge proofs and selective disclosure mechanisms. This research contributes to the advancement of secure IoT identity management and provides a foundation for future developments in decentralized IoT security

Internet of Things (IoT) ecosystems are becoming increasingly ubiquitous and heterogeneous, adding extra layers of complexity to secure communication and resource allocation. IoT computing resources are often located at the network edge and distributed across many heterogeneous sensors, actuators, and controller devices. This makes it challenging to provide the proper security mechanisms to IoT ecosystems in terms of manageability and maintainability. In an IoT ecosystem, computational resources are naturally distributed and shareable among their constituency, which creates an opportunity to distribute heavy tasks to them. However, resource allocation in IoT requires secure and complex communication and coordination mechanisms, which existing ones do not adequately support. In this paper, we present Secure Actor-based Model for IoT Communication (SecIoTComm), a model for representing secure IoT communication. SecIoTComm aims to represent secure IoT communication properties and design and implement novel mechanisms to improve their programmability and performance. SecIoTComm separates the communication and computation concerns, achieving design modularity in building IoT ecosystems. First, this paper presents the syntax and operational semantics of SecIoTComm. Then, we present an IoT framework implementing the key concepts of the model. Finally, we evaluate the developed framework using various performance and scalability metrics.

Fog-to-Cloud (F2C) is a novel paradigm aimed at increasing the benefits brought by the growing Internet-of-Things (IoT) devices population at the edge of the network. F2C is intended to manage the available resources from the core to the edge of the network, allowing services to choose and use either a specific cloud or fog offer or a combination of both. Recognized the key benefits brought by F2C systems, such as low-latency for real-time services, location awareness services, mobility support and the possibility to process data close to where they are generated, research efforts are being made towards the creation of a widely accepted F2C architecture. However, in order to achieve the desired F2C control framework, many open challenges must be solved. In this paper, we address the identity management challenges and propose an Identity Management System (IDMS) that is based on the fragmentation of the network resource IDs.

The Internet of Things (IoT) compromises multiple devices connected via a network to perform numerous activities. The large amounts of raw user data handled by IoT operations have driven researchers and developers to provide guards against any malicious threats. Blockchain is a technology that can give connected nodes means of security, transparency, and distribution. IoT devices could guarantee data centralization and availability with shared ledger technology. Federated learning (FL) is a new type of decentralized machine learning (DML) where clients collaborate to train a model and share it privately with an aggregator node. The integration of Blockchain and FL enabled researchers to apply numerous techniques to hide the shared training parameters and protect their privacy. This study explores the application of this integration in different IoT environments, collectively referred to as the Internet of X (IoX). In this paper, we present a state-of-the-art review of federated learning and Blockchain and how they have been used in collaboration in the IoT ecosystem. We also review the existing security and privacy challenges that face the integration of federated learning and Blockchain in the distributed IoT environment. Furthermore, we discuss existing solutions for security and privacy by categorizing them based on the nature of the privacy-preservation mechanism. We believe that our paper will serve as a key reference for researchers interested in improving solutions based on mixing Blockchain and federated learning in the IoT environment while preserving privacy.

Current identity management systems are not concerned with user privacy. Users must assume that identity providers and service providers will ensure their privacy, which is not always the case. This paper proposes an extension of existing Federated Single Sign-On (FSSO) systems that adopts the beneficial properties of the User- Centric Identity Management (UCIM) model. This new identity management system allows the users to control and enforce their privacy requirements while still retaining the convenience of single sign on over a federation of service providers. Coloured Petri Nets are used to formally model the new identity management system to provide assurance that the privacy goals are achieved. To our knowledge, Coloured Petri Nets have not been used to model privacy in identity management systems before.

A user-centric federated single sign-on system