Geo Intelligence India

13-14 Jun 2013

New Delhi

Do lafzon ki hai DATA ki kahani...............

Ek hai ZERO....duja hai ONE.....

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Big Spatial Data

Security

WELCOME

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BIG SPATIAL DATA has been with us for ages in various forms…but pretty invisible!!

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5Ancient Egypt

River nile

Engineers used to try data analysis to predict crop yields

6695 Km long

Basic Intro

Concepts

Perceptions

Challenges

…the 15 min route to THANK YOU slide

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An English professor wrote the words :

“A Woman without her man is nothing”

On the chalk board and asked his students to punctuate it correctly….

“A Woman,without her man,is nothing”.

“A Woman: Without her, man is nothing”

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A greater scope of Geo Int info

New kinds of Geo data and analysis

Real time Geo information

Data influx from new technologies

Non traditional forms of Geo data

Large volumes of Geo data

The latest buzzword

Social media data

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Series 1

DEFINING BIG SPATIAL DATA

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How we understand it ?

Spatial data sets exceeding capacity of current computing systems……

….to manage, process or analyze the data with reasonable effort

due to Volume, Velocity, Variety and Veracity

DEFINING BIG SPATIAL DATA

BIG SPATIAL DATA9

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DATA is Exploding in

Volume Velocity VARIETY

While decreasing in

Veracity

DEFINING BIG SPATIAL DATA

BIG SPATIAL DATAFinding actionable info in Massive volumes of both structured and unstructured geo data that is so large and complex that it’s difficult to process with traditional database and software techniques……

Volume

Velocity

VARIETY

VERACITY

Data at rest

Data in Motion

Data in Manyforms

Data in Doubt

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90% of data in the world was created in the last 2 years

2.5 EB of data is created

every day

U.S. drone aircraft sent back 24 years

worth of video footage in 2009

Gigabyte (GB) - 1,024MBTerabyte (TB) - 1,024GBPetabyte (PB) - 1,024TBExabyte (EB) - 1,024PB

* Estimated revenue FY 2013

growth of geospatial data is outpacing both software and services and is set to become a major contributor to the overall growth of the industry

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100% security is a mythNo one has said this!!!

But it remains a fact

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Increasing attack surface

The technology is ready….

But are we ready ?

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DISASTER RELIEF

FINANCIAL

FRAUD DETECTION

CALL CENTER REQUESTS

DISEASE SURVEILLANCE

INSURANCE

RETAIL

TELECOMMUNICATIONS

UTILITIES

ECO-ROUTING

The otherof the

side story

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Security challenges before we adopt Big spatial data

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Distributed programming frameworks

Ek

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Distributed programming frameworks

Input fileMap Intermediate

Combining Shuffle Output File

Local Reduce Reduce

Mapper performs computation& outputs a key/value pairs

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Reducer combines the values belonging to each distict key and outputs the result

Utilise parallilism in computation & storage to process massive amounts of data

MAP REDUCE

FRAMEWORK

Splits the input data-set into independent chunks which are processed

in a completely parallel manner

Aggregate results from map phase

performs a summary operation

Schedules and re-runs tasks

Splits the input

Moves map outputs to reduce inputs

Receive the results

Distributed programming frameworks

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So challenge is not storage but it is I/O speed

One Machine

4 i/o ChannelsEach channel : 100 MB/s

10 Machine’s

4 i/o ChannelsEach channel : 100 MB/s

Read 1 TB

45 Min 4.5 Min

Untrusted Mappers

Securing the data in the presence of an untrusted mapper

Distributed programming frameworks

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NO SQL ISSUES

TWO24

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First off : the name

NoSQL is not “NEVER SQL”

NoSQL is not “No To SQL “

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NoSQL

Is simply

Not Only SQL!!!!!

MongoDB

Redis

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NoSQL DB are still evolving with

respect to security infrastructure

Data storage & transaction logs

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STORAGE TIERS

- Multi-tiered storage media

- Necessitated by scalable size

- Different categories of data- Different types of storage

Data storage & transaction logs

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Lower tier means reduced security, loose access controls

Keeping track of data location

Data storage & transaction logs

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INPUT VALIDATION/FILTERING

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How can we trust data ?

Validating data when source of input data is not reliable?

Filtering malicious data @ BYOD

Input validation/filtering

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REAL TIME MONITORING

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Humongous number of alerts!!!!

False positives

Filtering malicious data @ BYOD

REAL TIME MONITORING

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Secure communication

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End to end security ?

Data encryption : attribute based encryption!!!to be made richer

Secure communication

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Granular audits

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New attacks will keep happening…and to find out we need detailed audit logs

Missed true positives

Granular audits

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PRIVACY ISSUES

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EG : How a retailer was able to identify that a teenager was pregnant before her father knew

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PRIVACY ISSUES

In the world of big data,privacy invasion is a business model

And...

We Also Have cloud with us?

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At 1.4% in 2011-12 Cloud was a very small percentage of the total IT spend

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Pace of Big Spatial Data adoption has been

Sluggish

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There is unlikely to be a day soon in near

future when we have a

“FIND TERRORIST”

BUTTON

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We have mostly been reactive till

date…..

46USE KERBEROS FOR NODE AUTHENTICATION – (BUT WE KNOW IT’S A PAIN TO SET UP)

STRINGENT POLICIES

STANDARD TO INTRA COUNTRY LAWS

EXHAUSTIVE LOGS

SECURE COMMUNICATION

STRINGENT POLICIES

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