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National Computational Science University of Illinois at Urbana-Champaign 1 “Enabling Proactive Prediction, Avoidance, and Diagnosis by Providing Situational.

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Presentation on theme: "National Computational Science University of Illinois at Urbana-Champaign 1 “Enabling Proactive Prediction, Avoidance, and Diagnosis by Providing Situational."— Presentation transcript:

1 National Computational Science University of Illinois at Urbana-Champaign 1 “Enabling Proactive Prediction, Avoidance, and Diagnosis by Providing Situational Awareness to Human Operators” {a work in progress} Bill Yurcik National Center for Supercomputing Applications (NCSA) University of Illinois at Urbana-Champaign IBM Academy Conference on Proactive Problem Prediction, Avoidance, and Diagnosis April 28, 2003

2 National Computational Science University of Illinois at Urbana-Champaign 2 The Problem Current state of networked software systems –asymmetries of software bugs and security attacks –metrics show bad -> worse –increasing complexity of software systems –expectation of vigilant patching for vulnerabilities –point-and-click attack software requires little skill –surveys show insider security attacks greatest threat despite denial –critical infrastructures all depend on underlying automation Situational Awareness is Abysmal –“Is there a problem?” -> “Where is the problem?” -> “What is the problem?”

3 National Computational Science University of Illinois at Urbana-Champaign 3 Alternate Solutions 1)Acquiescence (learning to live with it) 2)Prevention (zero defect software engineering) 3)Detection (early and continuous) 4)Survivability (transparent recovery) a)human-in-the-loop decision-making for recovery b)autonomic computing (no human-in-the-loop) 5)Disaster Recovery and Backup 6)Deterrence (liability, retribution) …. Prediction? … either The Holy Grail or “Minority Report”

4 National Computational Science University of Illinois at Urbana-Champaign 4 Our Solution: SIFT Motivation: “Know Thy fill in the blank ” SIFT = Security Incident Fusion Tools NCSA Proposal – Increase Low-Level Situational Awareness to Human Operators (Anti-Autonomic Computing) –“Is there a problem?” -> “Where is the problem?” -> “What is the problem?” –leverage human cognitive abilities especially visual processing –continuous awareness of the security state of an entire network –Class B address space = 65K machines with 130K+ ports on each machine

5 National Computational Science University of Illinois at Urbana-Champaign 5 Prediction / Avoidance / Diagnosis Examples: –time-sequence of network-based attacks –software decay How? –Visualization –Profiling –Data Mining for Discovery

6 National Computational Science University of Illinois at Urbana-Champaign 6 Current Network Monitoring

7 National Computational Science University of Illinois at Urbana-Champaign 7 Discovery Across Network Logs

8 National Computational Science University of Illinois at Urbana-Champaign 8 Attributes Across Logs

9 National Computational Science University of Illinois at Urbana-Champaign 9 The Data Management Problem

10 National Computational Science University of Illinois at Urbana-Champaign 10 Four (4) Parallel Data Management Efforts

11 National Computational Science University of Illinois at Urbana-Champaign 11 SIFT Preliminary Results

12 National Computational Science University of Illinois at Urbana-Champaign 12 SIFT Preliminary Results: Security Monitoring Prototype LEGEND DRILL- DOWN VIEWS OPTIONS FOR 172 DIFFERENT VIEWS MAGNIFIER WIDGET NVisionIP

13 National Computational Science University of Illinois at Urbana-Champaign 13 Prototype Drill-Down Security Views

14 National Computational Science University of Illinois at Urbana-Champaign 14 Insights Thus Far … Humans are good at processing visual patterns (known) No expert knowledge required! Abstraction – finding the appropriate level of observation “What If” Question Bonanza Visual Debugging (problem-solving) The Millisecond Fantasy Holistic Macro/Micro Views vs Divide-and-Conquer Though we think in pictures, we are no good at describing pictures (save functions) Capturing the time dimension of high-dimension data via animation is incredibly engaging to humans Success depends on effective HCI –Looking at new ways to augment operators in complex environments… (anti-autonomic)

15 National Computational Science University of Illinois at Urbana-Champaign 15 Demo – NVisionIP:lite Cut to Demo and Pray it Works!


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