Data Sovereignty in Multi Regional Identity Systems

Critical National Infrastructure (CNI) sectors, including energy, water, and transportation, are increasingly interdependent, yet they remain siloed by centralized Identity and Access Management (IAM) systems that act as single points of failure.This research proposes a novel Federated Identity and Access Management (FIAM) framework that establishes cross-sector trust through a hybrid architecture combining Blockchain-based Decentralized Identity (DID) and Federated Learning (FL).By utilizing a permissioned blockchain, the framework eliminates the reliance on central certificate authorities, providing an immutable and transparent ledger for Verifiable Credentials (VCs).To address the "static trust" limitation of traditional blockchain systems, a Federated Learning layer is integrated to perform real-time anomaly detection.This layer enables individual CNI sectors to collaboratively train a global threat detection model on sensitive access logs without exposing raw data, thus preserving operational privacy while enhancing collective security.Experimental evaluation conducted via a Hyperledger Fabric and Flower (FL) prototype demonstrates that the framework maintains a low authentication latency of <3 seconds and achieves a 98.8% accuracy in detecting identity-based spoofing and lateral movement attacks.The results indicate that the proposed "Trust-but-Verify" logic effectively balances the high-availability requirements of CNI with the need for a decentralized, privacy-preserving security posture.This work provides a scalable blueprint for resilient, cross-sector identity ecosystems capable of defending against sophisticated, multi-stage cyber threats in national infrastructure.

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.

Organizations may increase data security and operational efficiency by connecting Salesforce with Identity and Access Management (IAM) systems like Saviynt. This study delves deeply into the details of this revolution that is being encouraged to shift towards IAM software and potential drawbacks such as excessive provisioning and implementation issues. The study illuminated excellent practices and emphasized the importance of constant monitoring by using secondary theme analysis and qualitative research as proof. The findings indicate Saviynt as a viable solution and provide detailed information for firms seeking a smooth and secure integration path.

This paper discusses methods for preventing SQL (Structured Query Language) injections in identity and access control (IAM) systems. SQL injections represent one of the most serious threats to web security, allowing attackers to gain unauthorized access to and modify data. The main security methods include filtering input data, using prepared statements and parameterization, implementing stored procedures, restricting access rights, and regularly updating software. Effective privilege management and database activity monitoring also play a key role in preventing attacks. The introduction of these measures helps protect confidential information, ensures reliable authentication and authorization, and maintains data integrity. The paper highlights the importance of an integrated approach to database security in the face of growing cyber threats.

Building an identity and access management (IAM) system that satisfies business needs and can evolve over time with the ever-changing business environment, is always a challenging endeavour. This calls for the need of an ontology based adaptive IAM metamodel, which can adapt to and instantiated for different situations. To achieve this objective, the first step is to identify the relevant elements and their relationships for developing a detailed IAM ontology. Thus, this paper mainly focuses on the review of the available key models as a starting point for the identification of relevant elements and relationships for the development of the adaptable and yet generic metamodel for our industry research partner. This paper uses the graph modelling approach to present the identified elements and their relationship as an ontology, which can be used for developing the metamodel.

The widespread adoption of passwordless authentication methods, such as YubiKey and passkeys, represents a significant shift in Identity and Access Management (IAM) systems. While these technologies offer enhanced security by mitigating vulnerabilities associated with traditional passwords, their success hinges on effectively balancing robust security with user experience and accessibility. This article comprehensively analyzes YubiKey and passkey implementations, examining their impact on user interaction, cross-platform compatibility, and setup processes. We explore critical accessibility considerations, including challenges faced by users with physical disabilities and the inclusivity of biometric systems. The article also investigates the delicate balance between security and convenience, emphasizing the importance of user education and support in fostering adoption. By evaluating current implementations and projected technological advancements, we provide insights into the future landscape of passwordless authentication. Our findings underscore the crucial role of user-centric design in developing secure, accessible, and inclusive authentication systems, paving the way for a more secure and user-friendly digital ecosystem.

In an era where digital assets are the lifeblood of organizations, protecting them from unauthorized access and internal threats has become a top priority. Modern Privileged Access Management (PAM) tools have emerged as indispensable solutions to tackle these challenges effectively. This paper aims to provide an in - depth exploration of the capabilities offered by state - of - the - art PAM tools. These tools empower organizations to identify, manage, and fortify privileged accounts across their IT infrastructure. Key features encompass automated credential vaulting, regular password rotation, and robust session management to mitigate the risks associated with credential theft and unauthorized access. Additionally, PAM solutions enforce granular access controls, facilitate multi - factor authentication, and harness advanced analytics to detect and respond to anomalous activities swiftly. The seamless integration of PAM tools with Identity and Access Management (IAM) systems not only streamlines user provisioning but also enhances compliance reporting, ensuring adherence to regulatory standards. By harnessing the power of modern PAM tools, organizations can bolster their cybersecurity posture, neutralize insider threats, and successfully navigate the ever - evolving threat landscape of today.

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.

Identity (ID) management systems have evolved based on traditional data modelling and authentication protocols that are facing security, privacy, and trust challenges with the growth of Internet of Things (IoT). Research surveys reveal that blockchain technology offers special features of self-sovereign identity and cryptography that can be leveraged to address the issues of security breach and privacy leaks prevalent in existing ID management systems. Although research studies are recently exploring the suitability of blockchain based support to existing infrastructure, there is a lack of focus on IoT ecosystem in the secured ID management with data provenance of digital assets in businesses. In this paper, we propose a blockchain based ID management system for computing assets in an IoT ecosystem comprising of devices, software, users, and data operations. We design and develop a proof-of-concept prototype using a federated and distributed blockchain platform with smart contracts to support highly trusted data storage and secure authentication of IoT resources and operations within a business case scenario.

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 and access management (IAM) functions as a core component for today’s enterprises managing digital identities and their access to resources. However, IAM systems are quite isolated from other applications with useful information resulting in individual data pots. By interconnecting these systems, important information on relevant IAM entities like criticality or usage information can be additionally gathered for further improvement. Current IAM landscapes within enterprises are not prepared for such challenges as the data needs to be harmonised, analysed, and verified. Within this work a state-of-the-art IAM architecture in enterprises and existing shortcomings are defined. Based on these, an extended IAM architecture scheme is proposed and described in detail. Key component is the integration of additional information sources for mutual benefit in IAM and external applications. Finally, the approach is applied to two use cases based on real data. They originate from our conducted IAM projects and show the feasibility of the proposed architecture.

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.

Identity and Access Management (IAM) is essential for cybersecurity architecture because of the increasing complexity of the digital enterprise. The research investigates how Artificial Intelligence (AI) transforms Identity and Access Management (IAM) by establishing context-aware systems that function adaptively through automated identity governance capabilities. Concepts from traditional IAM infrastructure face challenges when implementing dynamic access models because they base their function on manual processes and static policies in their design. Machine learning combined with behavioral analytics and orchestration capabilities installed across the entire IAM lifecycle by AI can solve these issues, from authentication procedures to authorization functions and continuing through entitlement governance until policy execution. AI integration establishes continuous authentication with behavioral biometrics and conducts real-time anomaly detection through unsupervised learning models to enable proactive threat mitigation through risk-adaptive access controls. Through AI, the discovery and automation of access rights become possible because systems use actual user activities and organizational settings to refine and certify proper access definitions. The automation systems help organizations comply with GDPR and HIPAA by delivering immediate policy changes while providing auditable access decision logs. The research document evaluates how AI contributes to creating IAM infrastructure that can adapt because it uses predictive load-balancing techniques, self-healing orchestration mechanisms, and autonomous incident response capabilities. The document shows how IAM unites with Security Operations Centers (SOCs) by correlating identity signals with wider security monitoring data to enhance security detection visibility and coordinated response. This report reveals through technical precision and industry examples that AI-driven IAM functions as a security defense system and a business-enabling power for operational speed, compliance adherence, and digital safety in organizational networks. The research highlights AI's critical position in creating security for contemporary identity perimeters.

Information security is shifting from a traditional perimeter-based approach to an identity-based approach where the organization’s boundaries are where their digital identities exist. The organization has multiple stakeholders having access to various organization resources. Systems and applications are part of organization resources that help them achieve their business goals. These systems and applications are internally or externally exposed to allow all stakeholders to have seamless access, thus making identity and access management a big challenge. Identity and Access Management (IAM) is a fundamental part of information security. It plays a critical role in keeping the organization’s information security posture resilient to cyber attacks. This paper will identify various components of an IAM solution that are essential and should be considered while implementing and assessing the IAM solution and provides a high-level IAM framework that will allow information security professionals to assess the IAM security posture of an organization.

174 Background: The Screening Activity Report (SAR), a supplementary tool for primary care providers (PCPs), was released in April, 2014. Providers are able to access this comprehensive report securely via an online solution and view the screening activity of their patients across Cancer Care Ontario (CCO)’s three organized cancer screening programs; breast, cervical and colorectal. The objectives of the SAR are to improve the quality of cancer screening by increasing provincial screening rates, improving the rate of appropriate follow-up of abnormal results and promote the alignment of cancer screening practices with CCO’s evidence-based clinical guidelines. Methods: CCO partnered with eHealth Ontario in 2012 to leverage their identity and access management system to provide safe and secure online access to the report. Since this time, CCO has implemented a multi-faceted campaign to support registrations to the system, encourage report access, and gather feedback on how to improve the report for future iterations. Using a detailed methodology developed by a wide range of subject matter experts at CCO, the SAR employs numerous provincial data sources to provide an overview of the patient rosters. Actionable categories are assigned at the patient level using a unique algorithm based on the latest clinical guidelines. Results: Previous to April 2014, the SAR was referred to as the ColonCancerCheck SAR (CCC SAR) as it included colorectal cancer screening data only. The last release of the CCC SAR was in October, 2013. At this time 4,824 providers were registered to the identity and access management system and adoption of this report had reached 31% after being available for five months to providers. To date, 4,992 providers are now registered and adoption of the April SAR has already reached 27% after being available for almost two months. Conclusions: The SAR is the first tool of its kind to make widespread use of eHealth’s identity and access management system service and target a broad user base of PCPs. The successful launch of the SAR has provided key insights into how technology can be leveraged to share provincial data in a meaningful way with providers and support them in improving the quality of cancer screening.