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Cyber Security for SDN Moshe Markovitz Gen. Res. C.E.O Celare 6/21/2016 | © 2016 Proprietary and Confidential Information of Celare | 1

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Page 1: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Cyber Security for SDN

Moshe Markovitz Gen. Res. C.E.O Celare

6/21/2016 | © 2016 Proprietary and Confidential Information of Celare | 1

Page 2: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Agenda

Introduction of BATM – CELARE

SDN – How to attack ? What can we do to defend?

Celare solutions

Summery

6/21/2016 | © 2016 Proprietary and Confidential Information of Celare | 2

Page 3: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

BATM – Celare introduction of BATM – Celare

21-Jun-163 Company Confidential

Page 4: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

CELARE Cyber Systems is subsidiary of the BATM Advanced Communications group - London Stock Exchange (LSE:BVC)

Market focus - provides comprehensive Cyber Security solutions for Utilities, Defense, Governments, Homeland security and critical infrastructures organizations.

Cyber security solutions:T-Metro-XG - Network security platform for Encryption and Cyber defense.

NETWIZ - Network visibility solution that provides organizations an overall understanding what is happening on the network enabling most effective management of even the most hidden network threats.

About CELARE

6/21/2016 | © 2016 Proprietary and Confidential Information of Celare | 4

Page 5: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

CELARE Cyber Systems is the Cyber Arm of BATM Advanced Communications group

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Global Headquarters

Regional

Headquarters

R&D

Centers

Sales and Support

Offices

Partners

Warehouse

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BATM Established 1992

CELARE Cyber Systems Established at 2012

BATM www.batm.com Advanced Communications group -

London Stock Exchange (LSE:BVC)

CELARE is subsidiary of the BATM

6/21/2016 | © 2016 Proprietary and Confidential Information of Celare | 5

Page 7: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

SDN – How to attack ? What can we do to defend?

21-Jun-167 Company Confidential

Page 8: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Methods of Attack

Purpose of Attack

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Page 9: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

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Page 10: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

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Software-Defined Networks structure

Page 11: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

SDN ARCHITECTURE - ATTACK VECTORS

Customer requirements – To protect all SDN Layers from Cyber attacks

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Most SDN architecture models have three layers:

– lower layer of SDN-capable network devices

– middle layer of SDN controller(s),

– higher layer that includes the applications and services that request or configure.

We can anticipate several attack vectors on SDN systems. The more common SDN security concerns include attacks at the various SDN architecture layers.

Page 12: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

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Page 13: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

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Page 14: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Operationalizing the Network with SDN

An attacker would like :

see what flows are in use and what traffic is being permitted across the network.

eavesdrop on southbound communication between the network element and the controller.

This information could be useful for a replay attack or simply for reconnaissance purposes.

SDN systems are deployed within data:

Data Center Interconnect (DCI) protocols such as Network Virtualization using Generic Routing Encapsulation (NVGRE), Stateless Transport Tunneling (STT), Virtual Extensible LAN (VXLAN), Cisco Overlay Transport Virtualization (OTV), Layer 2 Multi-Path (L2MP), TRILL-based protocols (Cisco FabricPath, Juniper QFabric, Brocade VCS Fabric), Shortest Path Bridging (SPB), among others.

These protocols may lack authentication and any form of encryption to secure the packet contents. These new protocols could possess

Standardization are the best news for Hackers 14

Page 15: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Attacks at Controller Layer con.

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SDN controller runs on a general purpose operating system(Linux operating system) then the vulnerabilities of that OS become vulnerabilities for the controller.

Often times the controllers are deployed into production using the default passwords and no security settings configured. .

Attacker can created his own controller and got network elements to believe flows from the “rogue” controller.

to those flows from the perspective of the production controller. In this case, the attacker would have complete control of the network

Page 16: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

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PROTECT

Page 17: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Actions for Governments Cyber protection is a National effort :

• What to protect from ?

• Risk assessment survey – analysis of the situation – What are the Gaps ? Critical security gaps in current situation

– What are the external internal threats

– Critical asset over view situation

• Creating a master plan for 5 years

• Developing an operational concept for Cyber protection

• Technical design systems solution

• Forming special units educating and training

• Allocating resources

Page 18: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Cyber Security Implementation

CCSPhysical Infra.

ACVMS

Platforms

• Strong platforms and endpoints hardening• OT-specific events collection & Traffic Analysis• Full Network Compartmentalization• Segmentation & data flow control• Interfaces monitoring & ICD enforcement

• One-way Data Diode Protection

Page 19: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Cyber Security Implementation

CCSPhysical Infra.

ACVMS

Platforms

• Strong platforms and endpoints hardening• OT-specific events collection & Traffic Analysis• Full Network Compartmentalization• Segmentation & data flow control• Interfaces monitoring & ICD enforcement

• One-way Data Diode Protection

• Security events collection and analysis• Online APT monitoring• Real-time Anomaly Detection• Security Analytics & Root-Cause Analysis• Passive & Proactive threat management

• Network Segmentation• Centralized Authentication, Authorization & Access (AAA)

Management• Centralized Security Policy Management• Distributed, redundant Security Repository• Virtualization and Storage Security Implementation• Endpoint security & Access Control• Platforms Security Hardening

• Network Segmentation• Physical and Logical Network Separation• External Interfaces Protection

• Endpoint Strong Authentication• Traffic Encryption and Signing• Network Access Control• Full (Success/Failure) Security Logging• Data Flow control and monitoring

Page 20: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Cyber Security Implementation

CCSPhysical Infra.

ACVMS

Platforms

• Strong platforms and endpoints hardening• OT-specific events collection & Traffic Analysis• Full Network Compartmentalization• Segmentation & data flow control• Interfaces monitoring & ICD enforcement

• One-way Data Diode Protection

• Security events collection and analysis• Online APT monitoring• Real-time Anomaly Detection• Security Analytics & Root-Cause Analysis• Passive & Proactive threat management

• Network Segmentation• Centralized Authentication, Authorization & Access (AAA)

Management• Centralized Security Policy Management• Distributed, redundant Security Repository• Virtualization and Storage Security Implementation• End-point security & Access Control• Platforms Security Hardening

• Network Segmentation• Physical and Logical Network Separation• External Interfaces Protection

• Endpoint Strong Authentication• Traffic Encryption and Signing• Network Access Control• Full (Success/Failure) Security Logging• Data Flow control and monitoring

Page 21: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Cyber Security Implementation

CCSPhysical Infra.

ACVMS

Platforms

Page 22: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

The OLS Model (Operational Learning System)

IntelligenceRegulationsTerror

IncidentsIrregular

Events

Research, Analysis & Data

Fusion

Attack Scenario

AlertTraining program Procedures Technology

Page 23: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

– Comprehensive cyber security suite for NRP

– Full OT/SCADA cyber protection

– External/internal interface protection

– Integrated cyber-security and C&C

– Cyber-security training facility

APT

Page 24: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Dome

Vendors (Exploits, Patches)

Reputation

Resources

DarkNet

Intelligence

Agreements

External

Feeds

GuardRangeResponse

CyberWorx

Page 25: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Comprehensive Cyber Training Facility

Page 26: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

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Intel Inside-Malware Inside

Cyber crime Photos of an NSA “upgrade” factory show Cisco router getting implant

Servers, routers get “beacons” implanted at secret locations by NSA’s TAO team

by Sean Gallagher - May 14 2014, 10:30pm JDT

Page 27: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Access & Transport Encryption

6/21/2016 | © 2016 Proprietary and Confidential Information of Celare | 27

Ministry #1Public Network

Site B

Site C

Site A

Site F Site E

NAVY AIR Force

AIR ForceNAVY

Internet

Page 28: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Transport Encryption

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Ministry #1Public Network

Data Center #1

MOD

Data Center #2

Ministry #2 Ministry #3

Internet

Page 29: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Proposed Collaboration model

CELARE will provide T-Metro-XG platform which was originally

developed for the IMOD.

The platform supports both Network Encryption in HW and

Network visibility for Cyber defense.

Celare will provide network SW infrastructure and all support for

development.

Stage 1: VTU will develop encryption capabilities (HW based) on

the T-Metro-XG

Stage 2: Adding network visibility capabilities

Local production capability options

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Page 30: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Proposed Collaboration model

Czech product with full control on:

Logistic chain

» Preventing logistic chain attacks

Production

» No HW threats

Proprietary and secure encryption.

» Secure transport for classified information

Can work and interoperable with any commercial networks

equipment

Flexibility to use leased network infrastructure from local

operators

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Page 31: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

How to Monitor Multi Campus Segmented Network

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Page 32: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Network Visibility

Network Visibility is similar but much more

complex

X1000 of protocols,Hugh amount of

network elements

Page 33: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Example: Incident Management in multiple government agencies

Rule : large amount of Data

after 5PM

Dest IP From Russia

New Rule : large amount of Data & Dest is in Russia

Checking backHistorical DB on Russia

Communications

INFORMATION SHARING BTW ALL

AGENCIES

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Page 34: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Example: Chain Attack Event Investigation and action

Suspicions Direct traffic between 2

computers

Infection

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Page 35: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

NetWiz Cyber defense Solution

21-Jun-1635 Company Confidential

Page 36: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

The Challenges

Insider threats !

Attacks via Global International links

Assumption: Even heavily secured networks have vulnerabilities and

probably are already infected (HUMINT , lack of procedures, targeted attack).

Networks become huge and complex

New threats are not detected by conventional security technologies ( FW,

DLP…)

How to identify new & unknown threats (APT’s) ?

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Page 37: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Building the infrastructure for large scale network based cyber network system

Big Data reservoir

Full cycle threat Detection:

Collection, Recording, Analytics, Reporting, Detection Unknown Threats detection based on network anomalies algorithms

Behavioral forensic tools to better understand what is happening in the network

Tracking Suspicious user behavior and content

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Solution Requirements

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Page 38: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Use Case : Large Enterprise

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Page 39: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Use case: Government Enterprise network

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Page 40: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Use case: Government private cloud

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Page 41: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Monitoring the Links within the Campuses and Internet Gateways.Monitoring VPN connection between sitesNon Intrusive network connection using smart sensorsCreating global view of Network Traffic Protocol classificationMetadata extraction

Sending all relevant sessions information to central monitoringBig Data Analysis indexingRule based engine to detect

Threats and malwares Network anomalies Network policy Abuse Correleating suspicions events (One site, Several sites)

API to other detection systemsReporting to central government SIEM

NetWizTM Performs Internal and External Monitoring and establish 24/7 incident monitoring

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Page 42: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Collection: Large deployment of Integrated Switch/Probes located at the network edge Full session reconstruction Metadata and content extraction

Aggregation: Oracle Big Data appliance – distributed file system Recording & indexing Real-time and batch analytics – filtering, aggregation & correlation Network Situational Awareness Investigation, Information discovery & analytics

Detection: User data reconstruction and analysis Network anomaly, Prediction …… Detectors searching threats on collected data

NetWizTM Solution Overview

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Page 43: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Over 2000 Recognized protocols and applications by signature/behavior

MobileMobile P2P P2P VOIPVOIP StreamingStreaming WEBWEB InstantMessaging

InstantMessaging MailMail File TransferFile Transfer

RemoteAccess

RemoteAccess

Native IPNative IP

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Page 44: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

NETWIZTM Cyber Solution Overview

Conceptual Architecture

Aggregator

NoSQLDatabase

HDFS

OEP

Graph

Applications & Services

Detectors Analytics Learning

Network

Metadata

PCAP’s

Statistics

External

Configuration

Logs

Analytical DB

System MD Store

Analyst Desktop

Information Discovery

Reports

Ad-hoc Queries

Analytics

Enrichment

Insights & Alert

Service Request(Start Session) EnrichmentGet

Index

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Page 45: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

NoSQL Database:

Central DB for all Data (Input\Output)

Scalable data capacity & throughput

OEP Stream processor:

Enables easy definition of complex Network Rule set and can be activate immediately

Monitor streams in real-time

Filtering - New stream filtered for specific criteria

Pattern Matching - Notification of detected event patterns, e.g. events A, B and C occurred within 15 minute window

Graph DP & Visualization

Advanced property graph stored on the DB

Building the actual network dynamically

NetWizTM Big Data Analytics - Enables effective investigation and forensic of network incidents

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Page 46: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

TLV Interception Visualization tool (User Behavior)

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Page 47: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Visualization & Information Discovery

• Solution designed to be Event driven

• Supports GEO/Maps

• Advanced graphs and filters• Network Situational Awareness

• Facet search

• Solution designed to be Event driven

• Supports GEO/Maps

• Advanced graphs and filters• Network Situational Awareness

• Facet search

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Page 48: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Event DashboardInformation Discovery• Solution designed to be Event driven• Supports GEO/Maps• Advanced graphs and filters• Network Situational Awareness

• Solution designed to be Event driven• Supports GEO/Maps• Advanced graphs and filters• Network Situational Awareness

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Page 49: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Information Discovery Events Dashboard

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Page 50: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

DashboardInformation Discovery Events

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Page 51: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Graph DB Visualization

Internal Network Visualization

• Intuitive visualization

• Visual filters

• Advanced search: nodes & links

• Zoom for details

• Multiple views

• Intuitive visualization

• Visual filters

• Advanced search: nodes & links

• Zoom for details

• Multiple views

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Page 52: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

• Monitoring multiple links with speeds up to 40Gbps

• Agnostic to physical link (SDH, PTN, Ethernet) and Transport protocol (IP, MPLS)

• Distributed & Low cost

• Open architecture and scalable

• Low cost Switch/probes enable flexible deployment over the network

• Integrated with Any Big Data & tools

• Based on standard analytics tools and products (e.g. Oracle Endeca, OEP, Open Source)

• Open API for external systems and 3rd party applications and Algorithms

Solution Benefits

Page 53: Cyber Security for SDN › data › Markowitz.pdfBuilding the infrastructure for large scale network based cyber network system Big Data reservoir Full cycle threat Detection: Collection,

Thank You

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