This document discusses security issues related to big data. It notes that while data was traditionally stored in structured formats, today over 80% of data created is unstructured and stored in various sources. This data is challenging to manage and derive value from. The document outlines various sources of big data like social media, IOT devices, and cloud apps. It states that data is now stored and processed in many locations, and security has been overlooked as technologies were rapidly adopted. The key gaps are a lack of native security, anonymity and privacy risks, and complex and varied data structures and sources. The document proposes extending best practices from structured data, knowing your data through discovery and cataloging, protecting data through encryption and monitoring, and building a

1. Title Text
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Big Data : The Forgotten Security Landmine
By:
Lenin Aboagye, Security Executive
lenin@kogni.io

2. Where
01
What
02
How
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AGENDA
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3. Traditionally Data has been stored in File systems, Databases, Network Shares, Emails etc..
Most of the Data generated was structured data and stored in Databases
01
Where did we start from - and fast forward to today?
Today , App Developer Magazine reports that more data was created in 2017 than in the
previous 5,000 years of humanity, and Gartner estimates that nearly 80 percent of this data is
unstructured, meaning it lives in formats like PDFs, images and videos. The process of
managing, structuring and deriving value from this growing cache of information is challenging,
time-consuming and expensive — if it happens at all

4. • Paperless: Every organization is going Digital..
Grocery Chains, Digital Notary, Digital Banking,
Digital Lending Processes(scanning everything),
Esign(DocuSign)
• Ease of Content Creation : Social Media, Business
Apps
• Mobile Capture : Every second we capture and
send Data
• IOT: Connected anywhere and
everywhere(Thermostat, TV, Cars, Planes, Product
tracking etc..), Data Center Sensors
01
How and where is this Data coming from?
Media
Web
Cloud
IOT
Databases

5. 01
Where is this data being stored and processed and why?

6. • Rapidly adopted technology, Capability
before Security
• Multiple sources of data, different Varieties
of data, Volume, Velocity
• No one really knows what data is being put
into big data lakes
• Security Governance Gaps..bulk of your
data is no longer in your databases
• There are not many security Data Scientist
and Data Scientist do not want to deal with
security
01 Why Important for business but security Forgotten?
Source: CA Study on big data

7. Data is harder to track now01

8. • No Natively Defined Security:
Encryption, Policy Management,
Compliance & Risk Management
• Anonymity and Privacy: User
identity, behaviors etc..
• Varied and Complex:
 Data structure: Structured, Semi-
Structured and Unstructured Data
 Sources: Server data, email data,
cloud apps and mobile device data
 Data consumers: High-level
executive, B2B, B2C
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What is the GAP and how do we bridge it?
• Goldmine for PII
 Reams of data all flowing into
centralized system
• Few security people have big data
experience
• Data Brokers-e.g Cambridge
Analytica
• Current Security Solutions simply do
not work..DLP, Data Activity
Monitoring Tools, Database
Encryption
• Lack of products on market

9. 01
What is the GAP and how do we bridge it?

10. • Extend best practices in structured Data to Big Data
• Know your Data: Data Discovery, Data Cataloging, reduce number of sensitive data locations
• Protect your Data: Encryption, Redaction, Tokenization, Authorization
• Monitor, Monitor, Monitor
• Watch out for Anomalies, User and System activity monitoring, Policy violations and build
predictive models with Big Data
• Build a data centric security and risk model
01 Solve the Big Data Conundrum

11. 01
When it comes to Big Data

12. Thank you!!
THE WHY | DATA SECURITY01