METHODS FOR PREVENTING SQL INJECTION IN IDENTITY AND ACCESS MANAGEMENT (IAM) SYSTEMS

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.

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.

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.

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.

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.

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.

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.

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.

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.

Modern firms rely on HRMS (human resource management system) and IAM (identity and access management) to manage staff and protect personal information. A human resource management system, or HRMS, is a comprehensive set of tools to manage an employee's stay with a firm, from recruiting to performance review and even off boarding. In other terms, identity and access management (IAM) is a security solution that restricts access to specific systems and maintains digital identities. Its primary purpose is to keep unauthorized persons from accessing important information.

Some Internet of Things (IoT) platforms use blockchain to transport data. The value proposition of IoT is the connection to the Internet of a myriad of devices that provide and exchange data to improve people’s lives and add value to industries. The blockchain technology transfers data and value in an immutable and decentralised fashion. Security, composed of both non-intentional and intentional risk management, is a fundamental design requirement for both IoT and blockchain. We study how blockchain answers some of the IoT security requirements with a focus on intentional risk. The review of a sample of security incidents impacting public blockchains confirm that identity and access management (IAM) is a key security requirement to build resilience against intentional risk. This fact is also applicable to IoT solutions built on a blockchain. We compare the two IoT platforms based on public permissionless distributed ledgers with the highest market capitalisation: IOTA, run on an alternative to a blockchain, which is a directed acyclic graph (DAG); and IoTeX, its contender, built on a blockchain. Our objective is to discover how we can create IAM resilience against intentional risk in these IoT platforms. For that, we turn to complex network theory: a tool to describe and compare systems with many participants. We conclude that IoTeX and possibly IOTA transaction networks are scale-free. As both platforms are vulnerable to attacks, they require resilience against intentional risk. In the case of IoTeX, DIoTA provides a resilient IAM solution. Furthermore, we suggest that resilience against intentional risk requires an IAM concept that transcends a single blockchain. Only with the interplay of edge and global ledgers can we obtain data integrity in a multi-vendor and multi-purpose IoT network.

Identity and Access Management (IAM) is an emerging solution for authenticating and authorising individuals. This begins with determining an individual's 'identity' through identification and verification processes. Then it becomes vital for every organisation or institution to authenticate these individuals and to authorise access to resources in addition to limiting risks. An empirical study was undertaken to elicit IAM challenges that occur within the South African Social Security Agency (SASSA), which is responsible for the distribution of grants to underprivileged citizens. This paper presents the problems being experienced by SASSA and its stakeholders in the IAM domain and a possible solution to resolve a few of these problems. An important point noted during this case study was that IAM increases the need for the federation of databases so as to ensure ease of use and single sign-on (SSO), as well as improving the security processes.

As cyber threats continue to evolve, organizations are increasingly adopting advanced security frameworks such as Zero Trust Architecture (ZTA) to protect their digital assets. ZTA operates under the principle of "never trust, always verify," acknowledging that both internal and external networks may be compromised. Integrated with Identity and Access Management (IAM), ZTA offers a dynamic security model, requiring continuous authentication and authorization for every access request. This integration ensures that sensitive resources are protected by enforcing multifactor authentication, behavioral analysis, and micro-segmentation, which collectively reduce the risk of attacks. A critical aspect of ZTA is its focus on continuous authentication and the principle of least privilege. Unlike traditional IAM systems, which grant static access, ZTA dynamically adjusts access based on real-time conditions, such as user behavior, location, and the sensitivity of data. This reduces the attack surface and minimizes lateral movement within the network. Additionally, ZTA promotes network segmentation, using IAM frameworks to enforce strict access control for each network segment. This limits the potential damage if an attacker compromises one segment. Studies have shown that ZTA is highly effective in mitigating insider threats, reducing the attack surface, and enhancing the resilience of infrastructure. While challenges remain in terms of scalability and integration complexity, the security benefits are undeniable. The increasing use of AI, machine learning, and quantum computing is expected to further strengthen ZTA's security capabilities. As organizations face more sophisticated cyber threats, ZTA is likely to become a standard in cybersecurity strategies, providing a robust, adaptable solution to protect valuable digital assets.

Identity and Access Management (IAM) has emerged as a cornerstone of information security in multi-cloud environments, where organizations leverage diverse services across multiple platforms. As enterprises increasingly adopt cloud-first strategies and distribute resources across an average of nearly five cloud providers, maintaining consistent identity controls presents significant challenges. The complex nature of these distributed architectures often creates fragmented security policies, inconsistent authentication mechanisms, and critical visibility gaps that adversaries actively exploit. This article presents a comprehensive framework for strengthening IAM in multi-cloud settings through five essential components: unified identity management, adaptive authentication, policy harmonization, federated access solutions, and advanced monitoring capabilities. Organizations can address the inherent security challenges of multi-cloud environments by centralizing identity repositories, implementing dynamic verification based on contextual factors, standardizing security policies, enabling seamless cross-platform authentication, and leveraging AI-enhanced monitoring. The framework addresses how these integrated components enable enterprises to maintain robust security controls despite the heterogeneous nature of diverse cloud ecosystems, providing practical guidance for implementing effective IAM strategies that balance security requirements with operational efficiency and user experience.

The rapid proliferation of IoT devices across various industries has amplified the importance of secure and efficient identity and access management (IAM). This chapter explores the integration of blockchain technology for decentralized authentication in IoT ecosystems, addressing critical limitations of traditional authentication methods. Key discussions include the challenges posed by the resource-constrained nature of IoT devices and the dynamic behavior of IoT networks. The chapter delves into cryptographic solutions optimized for IoT environments and evaluates the balance between security, scalability, and performance. The potential benefits of decentralized approaches, such as improved resilience, enhanced privacy, and reduced reliance on central authorities, are critically assessed alongside their inherent challenges. Emerging trends and future directions for leveraging blockchain to enhance IoT device security are also highlighted. This comprehensive analysis aims to guide researchers and industry professionals toward developing robust, scalable IAM solutions for IoT.