Artificial Intelligence Assisted Identity And Access Management
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Artificial Intelligence- Assisted Identity and Access Management
Author: Esther Chinwe Eze
language: en
Publisher: Deep Science Publishing
Release Date: 2025-02-16
As businesses come to appreciate the need for Identity and Access Management (IAM) to protect their environments, they ensure that only permitted users can access sensitive data and systems. Growing companies need robust IAM solutions that enable them to handle user authentication, permissions, and access control more effectively, therefore underlining their need. Still, security breaches have been a major headache, even with the advances in IAM technologies. Cybercriminals are constantly improving their techniques to bypass conventional IAM policies, which has resulted in many security incidents and data breaches. Dealing with these security issues offers a promising solution by integrating Artificial Intelligence (AI) and Machine Learning (ML). By helping IAM systems recognize possible attacks that traditional methods could miss, AI and ML technologies provide sophisticated features for spotting unusual behavior patterns. Once an IAM attack is underway, these tools may help better identify unauthorized access, privilege escalation, and other suspect behavior. Machine learning algorithms are particularly well suited for this task as they can constantly learn and adjust from information, enhancing their precision over time. This study investigates the use of ML algorithms to improve the security of IAM systems, concentrating mainly on identifying attacks aimed at IAM servers, including OpenIAM and WSO2. Using Python code and WEKA, the study applies and experiments with different machine learning approaches, such as classification algorithms that can discern atypical behavioral patterns that point to IAM assaults. The research seeks to raise the detection rate of these assaults using machine learning, therefore giving another level of security for IAM systems. The study measures the performance of the suggested solution and its ability to spot possible risks using thorough dataset development, training, and validation of the models. The results of this study underline how combining IAM systems with machine learning could provide more reactive, real-time protection from emerging threats. Although challenges, including data constraints and the difficulty of feature selection, still exist, the findings indicate that artificial intelligence and machine learning might greatly strengthen the resilience of IAM systems. Further investigation could refine the models for even higher precision and broaden their use to other security situations, thereby adding to the larger field of cybersecurity.
Identity Security for Software Development
Maintaining secrets, credentials, and nonhuman identities in secure ways is an important, though often overlooked, aspect of secure software development. Cloud migration and digital transformation have led to an explosion of nonhuman identities—like automation scripts, cloud native apps, and DevOps tools—that need to be secured across multiple cloud and hybrid environments. DevOps security often addresses vulnerability scanning, but it neglects broader discussions like authentication, authorization, and access control, potentially leaving the door open for breaches. That's where an identity security strategy focused on secrets management can help. In this practical book, authors John Walsh and Uzi Ailon provide conceptual frameworks, technology overviews, and practical code snippets to help DevSecOps engineers, cybersecurity engineers, security managers, and software developers address use cases across CI/CD pipelines, Kubernetes and cloud native, hybrid and multicloud, automation/RPA, IOT/OT, and more. You'll learn: The fundamentals of authentication, authorization, access control, and secrets management What developers need to know about managing secrets and identity to build safer apps What nonhuman identities, secrets, and credentials are—and how to secure them How developers work with their cross-function peers to build safer apps How identity security fits into modern software development practices
The Adoption and Effect of Artificial Intelligence on Human Resources Management
Author: Pallavi Tyagi
language: en
Publisher: Emerald Group Publishing
Release Date: 2023-02-10
Emerald Studies In Finance, Insurance, And Risk Management 7 explores how AI and Automation enhance the basic functions of human resource management.