building secure relationships across the enterprise
DESCRIPTION
A Breakout Session by Chris Silveira, Manager of Fraud Intelligence at Guardian Analytics. Presentation from the 2014 IRM Summit in Phoenix, ArizonaTRANSCRIPT
Building Secure Relationships Across The EnterpriseIdentity Management and Behavioral Analytics
Guardian Analytics
Proven at Hundreds of Companies
Pioneered individual behavioral analytics to fundamentally change fraud prevention/security
Patented technology
Online and mobile portals
Employee portals and access
Payments
25 million accounts protected
3 trillion in assets protected
2 billion sessions protects
National and community banks
Leading Security Technology
"Guardian Analytics…has a proven and effective fraud detection risk-scoring engine."
"Guardian Analytics possesses one of the clearest visions
for how to tackle fraud management.”
Deep Experience Detecting Unauthorized Access and Activity
Strong Relationships Starts With Trust and Confidence
Control who users are and what their relationship is
Analyze if users are who they say they are and doing what they are supposed to
Identity Relationship Management
Consumer
Employee
Partner
Behavioral Analytics and Anomaly Detection
Extending Relationships Starts With Trust and Confidence
Consumer
Employee
Partner
Know who users are and what their relationship is
Verify that users are who they say they are and doing what they are supposed to
Extend relationships and engagement (information, services, devices, etc.) without
increasing risk
Trust & Confidence
Identity Relationship Management
Behavioral Analytics and Anomaly Detection
Cloud Apps
The Problem: Bad Actors Hide Behind Good Credentials
Consumer
Employee
Partner
External user compromised
Employees compromised or misuse privileges
Partners/ contractors
compromised
Financials
Data stores
Internal & External Bad Actors
Cloud apps
On-prem apps
Identity Relationship Management
Cloud Apps
Bad Behavior Always Stands Out
Consumer
Employee
Partner
External user compromised
Employees compromised or misuse privileges
Partners/ contractors
compromised
Cloud Apps
Financials
Data stores
On-prem apps
User behavior
Device/IPInformation
Authentication & MFA
Application Access
Administrative Activities
Day and Time
• Each user has typical behavior
• Bad actors will do something unusual relative to typical or legitimate activity
Identity Relationship Management
FraudMAP Analyzes Access Through OpenAM
Consumer
Employee
Partner
External user compromised
Employees compromised or misuse privileges
Partners/ contractors
compromised
User behavior
Device/IPInformation
Authentication & MFA
Application Access
Administrative Activities
Day and Time
a
Behavioral Analytics
Are users exhibiting any suspicious behavior?
Is access from an expected machine configuration?
Is it a suspicious device
Is their MFA workflow normal?
Is the user in a typical location or following a typical travel pattern?
Is the application access at an expected time or frequency
Are profile or authorization changes unusual?
Identity Relationship Management
Behavioral Analytics/ Anomaly Detection in Action
Demonstration
Actionable User Risk Assessment
Consumer
Employee
Partner
External user compromised
Employees compromised or misuse privileges
Partners/ contractors
compromised
User behavior
Device/IPInformation
Authentication & MFA
Application Access
Administrative Activities
Day and Time
a
Behavioral Analytics
Alert Enterprise
Real-time stepped-up authentication
Identity Relationship Management
Integrated Identity Management and Behavioral Analytics
Consumer
Employee
Partner
Enhance security Proactively identify credential compromise or misuse
Enhance complianceUncover policy violations
Increase automation Drive risk-based decisions
Increase visibility Maintain historical and contextual view of user behavior
Extend relationships and enhance engagementGain confidence to open information, services, devices
Identity Relationship Management
Behavioral Analytics and Anomaly Detection
Additional Examples – Behavioral Analytics
Screen shots.
Thank You