Click to edit Master title style



Similar documents
CLOUD ANALYTICS: Empowering the Army Intelligence Core Analytic Enterprise

This Conference brought to you by

Army Intelligence Industry Day Foundation Layer Technology Focus Areas

G2 Industry Day JULY Mr. Stephen Kreider PEO IEW&S. G2 Industry Day 29 July 2015 CLEARED FOR PUBLIC RELEASE

How To Build A Cloud Based Intelligence System

Take the Red Pill: Becoming One with Your Computing Environment using Security Intelligence

Providing On-Demand Situational Awareness

Data Refinery with Big Data Aspects

Enterprise Organizations Need Contextual- security Analytics Date: October 2014 Author: Jon Oltsik, Senior Principal Analyst

Machine Data Analytics with Sumo Logic

Cognitive and Organizational Challenges of Big Data in Cyber Defense

Big Data & Security. Aljosa Pasic 12/02/2015

White Paper. How Streaming Data Analytics Enables Real-Time Decisions

Applied Research Laboratory: Visualization, Information and Imaging Programs

How Using Big Data in Security Helps (and Hurts) Us

Department of Defense INSTRUCTION

HOW TO DO A SMART DATA PROJECT

Semantic Chat for Command, Control, and Intel Beyond Text

Cyber Security. BDS PhantomWorks. Boeing Energy. Copyright 2011 Boeing. All rights reserved.

Patterns of Information Management

New Technology Capabilities

A Primer on Cyber Threat Intelligence

Department of Defense INSTRUCTION. Measurement and Signature Intelligence (MASINT)

Security as Architecture A fine grained multi-tiered containment strategy

Are You Ready for Big Data?

Are You Ready for Big Data?

Threat Intelligence: Friend of the Enterprise

With DDN Big Data Storage

Autonomy Consolidated Archive

How To Create An Insight Analysis For Cyber Security

Enterprise Capabilities Descriptions

Cyber Watch. Written by Peter Buxbaum

PALANTIR CYBER An End-to-End Cyber Intelligence Platform for Analysis & Knowledge Management

Open Platform. Clinical Portal. Provider Mobile. Orion Health. Rhapsody Integration Engine. RAD LAB PAYER Rx

Cloud Monitoring and Auditing with CADF (Cloud Auditing and Data Federation)

Leveraging Big Data Technologies to Support Research in Unstructured Data Analytics

Advanced Visibility. Moving Beyond a Log Centric View. Matthew Gardiner, RSA & Richard Nichols, RSA

Active Response: Automated Risk Reduction or Manual Action?

Navy Information Dominance Industry Day

Augmented Search for Web Applications. New frontier in big log data analysis and application intelligence

V ID E O A N A LYT ICS

The Big Data Paradigm Shift. Insight Through Automation

Workforce Management: Introducing a Policy Rules Engine to Industrial Security Adrian Fielding, Honeywell Damian Vassallo, RightCrowd

BUSINESS VALUE OF SEMANTIC TECHNOLOGY

Case Management and Real-time Data Analysis

Intelligent Business Operations and Big Data Software AG. All rights reserved.

Applications of Deep Learning to the GEOINT mission. June 2015

Can We Become Resilient to Cyber Attacks?

NEEDLE STACKS & BIG DATA: USING EVENT STREAM PROCESSING FOR RISK, SURVEILLANCE & SECURITY ANALYTICS IN CAPITAL MARKETS

Solera Networks, A Blue Coat Company SOLERA NETWORKS BIG DATA SECURITY ANALYTICS

5 Keys to Unlocking the Big Data Analytics Puzzle. Anurag Tandon Director, Product Marketing March 26, 2014

SHARING THREAT INTELLIGENCE ANALYTICS FOR COLLABORATIVE ATTACK ANALYSIS

What do Big Data & HAVEn mean? Robert Lejnert HP Autonomy

Our Data & Methodology. Understanding the Digital World by Turning Data into Insights

WHITE PAPER SPLUNK SOFTWARE AS A SIEM

Trends and Research Opportunities in Spatial Big Data Analytics and Cloud Computing NCSU GeoSpatial Forum

DoD Strategy for Defending Networks, Systems, and Data

Network Security Deployment (NSD)

IBM Security IBM Corporation IBM Corporation

YOU VS THE SENSORS. Six Requirements for Visualizing the Internet of Things. Dan Potter Chief Marketing Officer, Datawatch Corporation

North Highland Data and Analytics. Data Governance Considerations for Big Data Analytics

Big Data Platform (BDP) and Cyber Situational Awareness Analytic Capabilities (CSAAC)

Improvised Explosive Device Network Analysis

The Lab and The Factory

Security strategies to stay off the Børsen front page

The following was presented at DMT 14 (June 1-4, 2014, Newark, DE).

XpoLog Center Suite Log Management & Analysis platform

A Vision for Operational Analytics as the Enabler for Business Focused Hybrid Cloud Operations

This Conference brought to you by

Data Driven Assessment of Cyber Risk:

Government Technology Trends to Watch in 2014: Big Data

PSG College of Technology, Coimbatore Department of Computer & Information Sciences BSc (CT) G1 & G2 Sixth Semester PROJECT DETAILS.

Increase Agility and Reduce Costs with a Logical Data Warehouse. February 2014

Big Data and Analytics: Getting Started with ArcGIS. Mike Park Erik Hoel

場 次 :C-3 公 司 名 稱 :RSA, The Security Division of EMC 主 題 : 如 何 應 用 網 路 封 包 分 析 對 付 資 安 威 脅 主 講 人 :Jerry.Huang@rsa.com Sr. Technology Consultant GCR

Solving big data problems in real-time with CEP and Dashboards - patterns and tips

Framing the Issue What are Usability and UCD? What do they have to do with Security? Current State of Usability in EHRs Role and Activities of NIST

Unified Security, ATP and more

Leveraging Network Infrastructure to Bring Critical Information to Users

Niara Security Intelligence. Overview. Threat Discovery and Incident Investigation Reimagined

Security and privacy for multimedia database management systems

Solutions to Trust. NEXThink V5 What is New?

Visualization, Modeling and Predictive Analysis of Internet Attacks. Thermopylae Sciences + Technology, LLC

STATEMENT BY DAVID DEVRIES PRINCIPAL DEPUTY DEPARTMENT OF DEFENSE CHIEF INFORMATION OFFICER BEFORE THE

Emerging Geospatial Trends The Convergence of Technologies. Jim Steiner Vice President, Product Management

ORACLE MANUFACTURING EXECUTION SYSTEM FOR DISCRETE MANUFACTURING

Flattening Enterprise Knowledge

GXP WebView GEOSPATIAL EXPLOITATION PRODUCTS (GXP )

Transcription:

Click to edit Master title style UNCLASSIFIED//FOR OFFICIAL USE ONLY Dr. Russell D. Richardson, G2/INSCOM Science Advisor UNCLASSIFIED//FOR OFFICIAL USE ONLY 1

UNCLASSIFIED Semantic Enrichment of the Data Entity Centric Precision Increasing Semantic Richness Solving the Precision / Recall Conundrum with Semantic Enrichment of the Data Concepts/Summarization (e.g. Terrorist Cell Leaders) Resolved Entity (John with ID xxxxx) Entity (Person, Object, Organization, Location) Semantically Labeled Data Po opulation Cen ntric Recall Increasing Anonymity Non- Attributable Aggressively Index Enabled by fine grain security and compliance enforcement De Anonymization of Large Data Sets Detect / Match Behaviors and Patterns Massive Data Sets for Anomaly / Change Detection Massive Data Aggregation for Machine Analytics, Baselining, and Trend Analysis Multi token/lemma/contexual Element/ Part of Speech (Noun, Pronoun, Punctuation) Token (Aggressively Indexed Words) Determine that Two Patterns of Life are the Same but Not Necessarily Whose Pattern of Life Indications and Warnings Non Attributable Aggregate Behavior Determine Avg Traffic Speed by Tracking Cell Movement Determine the Sentiment of a Town, City, Region, Country UNCLASSIFIED 2

Extending Cloud-Enabled Advanced Analytics UNCLASSIFIED All-Source Analytics for Big Data with Advances in Geospatial Indexing, Voice Index and Search, Biometric i Entity Management, Motion Imagery Tracks, Multi-INT Visualization, Collection Management, Support for Mobile Devices, Powerful Compute Platforms, Multi-Level Security, IC Shared Software,. Mobile Voice Motion Imagery Tracks

Click to edit Master title style Fusion Challenges Social Media All Source INTs Person Location Tipping and Cueing Pattern of Life Analysis Alerts & Notifications Information and Situation Sensors Information requests Tactical Reports HUMINT Biometrics DOMEX SIGINT GEOINT Cyber Org Unit ISR Optimization Persistent and Total Entity and Asset Tracking in Entity Database Threat Characterization COA Analysis Continuously & Always Correlating All Data into the Entity Database Challenges 1. Cross INT Correlation 2. Entity Resolution and Disambiguation 3. Scale of the Entity Database 4. Velocity of Data Collection and Processing 5. Dt Determining ii Ptt Patterns of Life and Major Combat Operations with Tolerance to Errors 6. Ranking Threat Severity and Timing 7. Optimizing / Synchronizing ISR 8. Real time Tipping and Cueing 4

Click to edit Need Master to Work title Entity style Tracking Threat Characterization Social Media Reports/ HUMINT Biometrics DOMEX SIGINT GEOINT Cyber Entity Database Person Location Org Unit 4 Optimize ISR ISR Form Links Precorrelat ted Linked Data base P1 P2 P3 P4 P5 L1 L2 L3 L4 O1 O2 O3 O4 O5 Persist Tracks 3 COAs (T2,L3) (T3,L3) (T4,L3) (T1,O1) (T3,L3) (T3,L2) (T1,L2) (T2,L2) (T3,L3) (T1,L1) (T2,L2) (T3,L3) (T1,P1) (T2,P1) (T1,P4) (T3,P3) (T1,P4) (T2,P5) (*,L1) (T1,P1) (T3,L3) 1 2 U1 U2 (T1,L1) (T1,L1) (T2,L1) (T2,L1) (T3,L3) (T3,L3) U3 U4 U5 T1 (P1,L1) (P3,L1) (T3,L3) T2 (P1,L1) (P2,L3) (T3,L3) T3 (P1,L3) (P3,L3) (T3,L3) T4 (P2,L3) (T2,L1) (T3,L3) T5 Same Time, Same Place L2 may be an important location as many P s have been reported being there Patterns of Life Determined P1 and P3 share location pattern Infer P3 at L1 as O1 is at L1 Location of P1 over time 5

The DCGS-A ICITE Cloud (aka Red Disk) Click to edit Master title style at-scale Entity Database Sensors Sources SIGINT MTI WAMI FMV TED Fires Harmony USMFT Collection Mgmt Open Source Mission Command Audio etc Velocity & Content EDH Provenance TDF Metadata tagging Geo temporal extraction Entity extraction and nomination Artifact enrichment Security Labeling Metrics more RTAAP NIFI / Storm Real Time Advanced Analytics Pipeline updating analytics earliest as possible. Data Interoperability Decreases Information Enterprise Context Burden Full Spectrum Analytic Awareness Artifacts, Terms Statements Analytics and indexes updated wrt to each artifact Maximally correlated data Contextual based navigation All data under a common representation to enable assess to all layers Cross corpus analytics without custom code Signatures are analyzed in real time Logical representation needs to be consistent in order for the physical model and view to be dynamic M/R MR Data Access Process User s authorizations and roles are matched to data security labels UCD Enrichment Analytics and indexes wrt to the entire corpus, Bulkand incremental updates Data sharing Analyst s conclusions enrich the UCD DIAS User s Authorizations Community Partners Classes of relationships determined at various points No all relationships need to be explicitly expressed correlations enable this All analytic disciplines together with correlated data among all disciplines Analytic models are represented in the UCD 6