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AFRL / FAA Programs Status Report. Lt. Matt Manger Rome Research Site 6 May 2003. Overview. CyberWolf Air Force Enterprise Defense (AFED) Distributed Agents for Information Warfare (DAIWatch). CyberWolf Outline. Program Description Task Goals Progress. Objective Architecture

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afrl faa programs status report

AFRL / FAA Programs Status Report

Lt. Matt Manger

Rome Research Site

6 May 2003

overview
Overview
  • CyberWolf
  • Air Force Enterprise Defense (AFED)
  • Distributed Agents for Information Warfare (DAIWatch)
cyberwolf outline
CyberWolf Outline
  • Program Description
  • Task Goals
  • Progress
  • Objective
  • Architecture
  • Device Experts (DE)
  • Problem Statement
  • Implementation
cyberwolf objective
Cyberwolf Objective
  • Objective
    • Develop a versatile, scaleable, and extensible enterprise security management and CND tool
    • Utilizes expert system rule-based correlation of IDS and network management events
  • Goal
    • Reduce the workload of network security personnel responsible for maintaining security of the enterprise while at the same time providing more accurate network situational assessment information
cyberwolf problem
CyberWolf Problem

Long-suffering, overworked

Security Administrator

Millions of

Enterprise Security Events,

cyberwolf architecture
CyberWolf Architecture

Just a Few Incidents Worthy of Human Attention

Much happier

Security

Administrator

(only deals with

a few incidents).

CyberWolf

Manager

Lower-Intensity Alert Stream from “Device Experts”

NT

Device

Experts

UNIX Log

Device

Experts

Router

Device

Experts

COTS IDS

Device

Experts

Firewall

Device

Experts

Many More

Device

Experts

Millions of Events, Some With Security Implications

cyberwolf implementation
CyberWolf Implementation

CyberWolf Manager

Systems, IDS,

Network Elements &

Other Devices

SecurSite

Information Rich GUI

- Instant Visibility to Threats

- Simple English Descriptions

- Color-coded and Prioritized

Security Incident List

CyberWolf Experts

  • Capture Event Data from
  • Enterprise Security Components
  • - Translate Events into
  • Cyberwolf Syntax
  • - Provide Analysis and Filtering
  • Decentralized Intelligence for
  • Maximum Scalability

AutoAdvisor

Rule-based Correlation Engine

- Automatically Tracks Incidents

- Automates Analysis and Response

- Ships with build-in tracking tools

- Easily Add Custom Enterprise Rules

Learning Repository Database

- Cumulative Tracking of all

Events, Alerts, and Incidents

- Searchable for Creating Reports

and Audit trails

KnowledgeBase

Device-Specific Information

- Expert Analysis of Device Output

- Update Device Rules and Tables

- Controls Alert Stream Using

Expert-defined Thresholds

Real-time

Email & Pager

Alerts

Automated

Trouble Ticket

Submission

Incidents!

Events

SafePath

Encrypted and

Authenticated

Socket-based

Communications

Alerts

cyberwolf device experts
CyberWolf Device Experts

Each DE utilizes less than 3% of CPU during operation

  • Gauntlet v4.5/5.5 Firewall DE
  • SideWinder Firewall DE
  • Raptor Firewall DE
  • Pix Firewall DE
  • Zone Alarm DE
  • Black Ice DE
  • RealSecure v6.0 IDS DE
  • NetRadar IDS DE
  • Snort IDS DE
  • ASIMM/CIDDs DE (Gov’t only)
  • HP Openview NNM DE
  • SNMP DE
  • Nmap DE
  • Cisco Router DE
  • Ascend Router DE
  • Windows 95/98/NT/2000 DE
  • Solaris DE
  • Linux DE
  • ASIM/CIDDs
cyberwolf faa goals
CyberWolf / FAA Goals
  • Phase 1
    • Demo of CyberWolf’s automated attack analytics capabilities for the CSIRC
  • Phase 2
    • Input from ISS sensors not currently connected to the CSIRC (ISS RealSecure). Removal of discrepancies of sensor input including false positives, data reduction, cross correlation and integration.
cyberwolf faa progress
CyberWolf / FAA Progress
  • Money on contract in late February
  • Beginning evaluation later this month
  • Contract to be completed by September
afed outline
AFED Outline
  • Program Description
  • Task Goals
  • Progress
  • Quad Chart
  • Components
  • Architecture
  • Capabilities
afed quad
AFED Quad
        • Objectives
  • Provide a Defense-in-Depth capability that integrates existing event information:
    • Policy Enforcement; Change/Configuration Management; Threat & Vulnerability Assessment with Countermeasure recommendations; Intrusion Detection; Network Management
  • Fuse Information Assurance (IA) and Network Management data into a Common Enterprise Picture
  • Provide a consistent visual environment for information portrayal

Infrastructure

Interface

  • Approach
  • Spiral tech exploration, development, validation, and feedback process
  • Payoffs
  • Integrates existing enterprise sensors and provides enhanced Information Assurance and Enterprise Defense capabilities in support of the AF Protect-Detect-React/Restore model.
  • Assists in the automated detection and reporting of information attacks, containment and restoration of compromised systems, and planning/protection of enterprise assets.
  • Supports entire NOSC mission bycross-sharing of data among NOSC crew
  • Automated Reporting for Containment and IO Targeting
  • Mission Situational Assessment
  • Automated Courses of Action

Transition Agents: ESC/DIGC, ESC/DIW

End Users: MAJCOM NOSCs, AFNOSC, CAOC-x

afed goals
AFED Goals
  • Merge network management and security tools and data to provides a better enterprise picture
  • Provide analysts with improved host, security, and course of action information
    • Simplify access to data via drill down menus from the same GUI
  • Reduce the workload of analysts
    • Provide data correlation capabilities
  • Combines network and host based sensors
  • Demonstrates R&D technology to operational units
afed architecture
AFED Architecture

Enterprise

Management

Situational

Assessment

ALPHA

CHARLIE

BRAVO

DELTA

Information

Operations

Vulnerabilities

Risk Analysis

Open Source

(DNS, Whois)

Network Control

(Firewalls, Routers)

Host/Network

Intrusion Detection

Network/Link

Management

Action/Protection

Preemptive

Measures

&

Courses of

Action

Reporting

Analyst/Organization Rules

  • Security Policies
  • Complex Attack Methodologies
  • INFOCON Rules
  • Reporting Rules
  • Courses of Action

Oracle Database

Algorithms/KB

  • Schema/Tables
  • Access Policies
  • Peer-to-Peer Sharing

Data Storage

&

Analysis

Visualization

  • Data Reduction
  • Fusion
  • Correlation
  • Data Mining
  • Trend Analysis
  • Knowledge Base
  • Advanced Intrusion Detection
  • Analysts GUI Screens
  • System Operation/ Control (WEB)

Sensor

Input

afed components
AFED Components

Visualization/Control

Decision Support/COA

Reporting

Java GUI

Web

Incident

Report

ARS

NetFlare

Policy Enforcement

Avi

Hierarchy

AFSSI 5027

CMU

NetFlare

Vulnerability Assessment

TVC

Host Based Agents

ISS

DAIWF

Outpost

Network Mgmt

CyberWolf

HPOV

IntrusionDetection

Sidewinder

ASIM/CIDD

JIDS

Sidewinder

Raptor

NetRadar

ITA

AIA

Correlation

&

Data Mining

Real Secure

Cisco

NetRanger

ASIM

DB Data Direct

Other Data

Web Srv

Cmd/Config

App

Svrs

AFED/AIDE

RT DB

AFED

Trend DB

App

Svrs

App

Svrs

Bridge

Automated Response

afed capabilities
AFED Capabilities
  • Intrusion Detection
    • Merges event and session data from COTS/GOTS sensors (e.g., ASIM/CIDDS, Netradar, Real Secure, …)
    • Translates outputs into standard categories
  • Visualization
    • Provide a consistent visual environment
    • Data views customized for crew positions
  • Policy Enforcement
    • Allows users to define and alert on site policies
    • Allows sites to map network and monitors changes in host OS and services
  • DAA/CTO
    • Automates DAA and CTO processes
    • Verify and update CTO information via monitoring
afed capabilities1
AFED Capabilities
  • Vulnerability Assessment
    • Commercial Network scanner integrated
    • Host based checks performed
  • Network Management
    • Provides correlation between network events and intrusion events
    • Provides access to host software and hardware inventories to assist identifying vulnerabilities, and security compliance
  • Modeling & Simulation
    • Allows decision makers to perform tradeoff analysis of course-of-actions
  • Reporting
    • Automate the reporting process
afed faa goals
AFED / FAA Goals
  • Optimization of IDS rule sets
    • Using AFED, operator reduced daily events by 60% at AFRL site
  • Cross site/sensor correlation
    • Hierarchical reporting capability
  • Comparison of different sensors
afed faa progress
AFED / FAA Progress
  • Funds contracted in late February
  • Received 1 months worth of sensor data
    • Awaiting additional sensor’s data
  • Data loaded into AFED database and appropriate data views created
  • Administrator beginning to examine/optimize rule set
slide22

an ISO 9000 Certified Company

Distributed Agents for Information Warfare (DAIWatch)

daiwatch outline
DAIWatch Outline
  • Program Description
  • Task Goals
  • Progress
  • Discriminators
  • Architecture
  • Technology
  • Benefits
daiwatch discriminators
DAIWatch Discriminators

DAIWatchTM provides information security protection against the most sophisticated attackers including the Cyber Terrorist vs. the current emphasis of commercial products on hackers

  • Firewalls and related layered products cannot protect the network from internal activities: DAIWatch approach is host based.
  • Current technologies are signature based: DAIWatch uses activity recognition
  • Existing Systems are stovepiped: DAIWatch integrates across existing information system monitors
  • Current Software is static: DAIWatch uses smart dynamic agents.
daiwatch technology
DAIWatch Technology

1

  • Sensor Agents
  • Login Times
  • Files accessed
  • Programs Executed
  • Physical Configuration (e.g. modem)
  • Fusion Agent Functions
  • Profile User Activity
    • Individual
    • Role-based
    • (engineer, accountant, etc)
  • Identify Anomalies
  • Recognize Network Abuse/Attacks
daiwatch architecture
DAIWatch Architecture

Existing information security systems are designed to prevent remote entry from casual hackers. Professionals gain entry by stealing, buying or guessing passwords; or through casual employees such as maintenance staff. DAIWF integrates data from conventional security systems with internally deployed sensors to find these most sophisticated attackers.

750+ computers per various hubs and subnets

Wandering agent roams the network looking for malicious code and other configuration issues.

Wireless Devices

DAIWatch Components

Mobile Sensor Agent

Wandering Sensor Agent

Broker Agent

Distribution Manager

Fusion Agent

Control/Management

Mobile agents are automatically deployed where needed based on risk.

DAIWatch maintains database and fuses information from all over network to find sophisticated threats and reduce false alarms from simple traffic analysis..

IDS

Router

Broker agents collect data from existing devices (e.g. firewalls) and DAIWatch Sensors.

Internet

Firewall

daiwatch benefits
DAIWatch Benefits

Next Generation Network Security Manager Focused on Sophisticated Attacks

  • Protects the Network - Recognizes Network Attacks, Especially Sophisticated Ones (Eg. Man-in-the-middle) Including Insider/Masquerader Threats
  • Reduces Liability Exposure - Improves Compliance With New Government Mandates (E.G. GLB, Unauthorized Access)
  • Saves Money (H/W) - Identifies Network Abuse (Webservers, Login Anomalies, Software Install, Policy Violations, Etc.)
  • Saves Money (Staff) - Reduces System Administration Time Via Reasoning, Presentation and Drilldown of Data From Other Security Products
  • Improves Effectiveness of Security System - Identifies Intentional and Inadvertent Security Holes (Eg. Mis-configured Firewall)
daiwatch faa goals
DAIWatch / FAA Goals
  • Provide real time insider and outsider threat analysis for all network areas including health status of the network.
  • Phase 1
    • Deploy to limited number of machines and receive accreditation to progress
  • Phase 2
    • Initial deployment of approximately 40-50 hosts would provide an opportunity for demonstrating the assessment and value of this tool in a controlled network environment.
daiwatch faa progress
DAIWatch / FAA Progress
  • Funds contracted on 12 March 2003
  • FAA received DAIWatch Server
  • ORINCON/FAA set up the server and configured DAIWatch
  • 1 Windows 2000 client installed and running
  • Undergoing 1 week evaluation
  • Waiting for approval software evaluation board
  • Status / User Meeting on 15 May - ORINCON/FAA
summary
Summary
  • CyberWolf
  • Air Force Enterprise Defense (AFED)
  • Distributed Agents for Information Warfare (DAIWatch)
questions

Questions??

Lt. Matt Manger

Rome Research Site

[email protected]

(315) 330-1874

6 May 2003

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