Hey Everyone! 👋

Since my post last month I have been thinking about integration of AI with IAM. So I started learning more and came up with PoC: an Adaptive Identity and Access Management (IAM) solution that leverages machine learning to dynamically adjust access controls based on real-time risk assessments. 🌟

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Why Adaptive IAM?

In today’s digital landscape, traditional IAM systems often fall short in addressing sophisticated security threats. Adaptive IAM enhances security by continuously monitoring user behavior and context, making real-time adjustments to access permissions. This approach not only improves security but also ensures a seamless user experience for legitimate users.

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The Power of Machine Learning

I utilized the Isolation Forest model, an unsupervised learning algorithm, to detect anomalies in user login patterns. By analyzing features such as login timestamps, IP addresses, and device information, the model assigns a risk score to each login attempt. High-risk logins trigger additional security measures or denial of access, while low-risk logins allow seamless access.

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Implementation Highlights

• User Interface: I used Bootstrap for UI as its easier to use and help with creating clean design for poc. Successful logins display a happy party sign 🎉, while failed logins show a danger sign ⚠️, making the user experience intuitive and engaging.

• Seamless Integration: The solution is built using Python and Flask, ensuring easy integration and scalability. By storing each login attempt, including the risk score and denial reason, in an SQLite database, we maintain a comprehensive record for further analysis.

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Live Demo and Results

I created a live demo showcasing the solution in action. When users log in, the system evaluates their behavior in real-time:

Adaptive Identity and Access Management Solution using Machine Learning - Watch Video

• Successful Login: Users see a cheerful dashboard, welcoming them with a happy party sign 🎉.

• Failed Login: Users are met with a warning, explaining the high-risk nature of their attempt with a danger sign ⚠️.

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This project exemplifies how machine learning can revolutionize IAM, making it more responsive and secure. 🚀

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Feel free to reach out if you have any questions or want a deeper dive into the project.

#TechInnovation #CyberSecurity #MachineLearning #IAM #Python #Flask #AdaptiveSecurity