Identity Management

Machine Learning for Identity Access Management

Identity and Access Management is constantly evolving across critical functions including data security, authentication, synchronizing internal data, enabling consumer contact preference management and meeting privacy compliance requirements to name a few.

According to Forrester Research’s Report, Top Trends Facing Shaping IAM in 2019, January 3, 2019 “Protecting the enterprise from data breaches, malicious insiders and fraud remains a top business priority and is driving demand for smarter identity analytics that can dynamically detect anomalous user activity.”  simMachines similarity based explainable AI (XAI) technology is a perfect fit for this challenge given its ability to explain anomalous behavior.

Similarity Based Explainable AI (XAI) Provides Actionable Intelligence for IAM Analytics

Explainable machine learning is critical for not only detecting security risks, but also in explaining what the key factors are in order to understand and prevent them from occurring

simMachines Provides Unparalleled Transparency Into AI Predictions

High precision with local prediction transparency

Single pass prediction and clustering function

Easy to use, with advanced capabilities for Data Scientists

Dynamically weighted factors by prediction

Used controlled cluster granularity

Predictive factors easily integrate into decision systems

Identity Access Management Requires Explainable Threat Detection and Constant Monitoring Through Automated Insights

Review & Investigation

System audits and investigative analysis demands transparency into machine behavior

Explainable Detection

An expanding range of breach techniques driven by more sophisticated methods and increasing vulnerabilities requires explainable anomaly detection technologies

Patterns & Trends

New identity theft techniques can emerge quickly and scale fast, taxing the most sophisticated detection systems that now must constantly monitor for new patterns to enable preventative action

Know What Your Machine Knows

Identity access management professionals need machine learning applications that provide full explainability for each and every prediction, to understand access breach causes and their defining factors, enable investigation and review, detect new emerging patterns and constantly monitor changes and differences in identity theft and breach methods.  simMachines XAI technology leverages proprietary algorithms to provide precise predictions and automated insights at speed and scale to accomplish these goals.

One Class Learner for Explainable Anomaly Alerts

Algorithms train on normal behavior to detect what is not normal, including complex combinations of high dimensionality signals.

Machine Driven Explainable IAM Predictions

Similarity combined with metric distance functions provide state of the art precision with full explainability at a local level, nearest neighbors, and analytics on similar events. 

Dynamic Predictive Clustering for IAM Insights

Individual identity predictions are automatically clustered into dynamic predictive segments that reveal weighted features in order of importance for fast, deep and rich analysis. Export as needed to preferred BI tools.

Anomalous Pattern Detection, Trending & Analysis

Similarity provides the ideal tool for identifying anomalous behavior. Similarity’s inherent explainability enables investigation, understanding, analysis and communication of unusual activity.

Flexible Deployment Options Including Restful APIs

Software can be supported in on-premise, private cloud or hosted cloud environments for production or development applications.

Access to Data Scientists and Expert Customer Support

Tier II support from our expert data scientist and client support resources ensure you have quick and easy access to the resources you may need to solve problems and innovate solutions.

Use cases

simMachines supports a variety of use cases around Identity and Access Management.

Recent news in IdentityALL NEWS ON OUR BLOG

You Don’t Have to Sacrifice Machine Learning Precision for Explainability
Dave Irwin | 13, December

Artificial intelligence and machine learning are rapidly on the rise. Having just attended Forrester’s Data Strategy and Insights Conference in Orlando, FL, we heard these terms frequently mentioned in many presentations.

*The Insights-Driven Business, July 2016, Forrester Research

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