1.
Raffael Marty, CEO
Cloud and Big Data
iTech Gulf, Kingdom of Bahrain
April 10th, 2014

2.
Security. Analytics. Insight.2
The Intersection of Three Domains
Big DataCloud
Security

3.
Security. Analytics. Insight.3
Why use the Cloud?
• Increased efficiency due to better use of resources (elasticity)
• More predictable cost
• Design with redundancy and failure tolerance needed
• Automation necessary, but that’s a good thing
• Outsource non core capabilities / responsibilities
!
New Use Cases / New Applications
• Enables new business models (pay as you go)
• Access to large compute and storage
Cloud

4.
Security. Analytics. Insight.4
• Storage has gotten cheap ($0.01 / GB)
• Access to large compute on demand
—> Use larger data to gain insights
!
!
• Search engines
• NoSQL / NewSQL / Key-value stores
• Map Reduce [really parallel computing (HPC)]
• On commodity hardware
• Bring compute to the data
Cloud has Enabled Big Data
Big Data = New technologies to deal with large
amounts of data

5.
Security. Analytics. Insight.5
Big Data Has Changed Data Analytics
“memory has become the new hard
disk, hard disks are the tapes of
years ago” -- unknown source

6.
Security. Analytics. Insight.6
Questions to answer:
• “Show me all documents mentioning ‘pixlcloud’”?
• “Which document contains the most relevant information about ‘bahrain’”?
Big Data Stack - Search
Raw Data (Documents)Storage
Search
Interface REST API Web Interface
Index

7.
Security. Analytics. Insight.7
Questions to answer: “Visualize user activity in clusters based on their behavior.”
Big Data Stack - Large-Scale Processing
Map Reduce
Distributed Filesystem
Impala, Stinger,
HawQ
SQL Layer
Analytics
Visualization
0xdata, Revolution
Tableau
Hadoop FileSystem (HDFS)

8.
Security. Analytics. Insight.
We can store and process PB of data …
• How to analyze the data? What algorithms, what technology, …
• How to get to insights?
• How to do data science on all of that data?
• Adopting machine learning / data mining to
larger amounts of data is hard
• Setups can get complicated - many components
8
Big Data - Limits

9.
Security. Analytics. Insight.9
Data Storage and Access
• Isolation management / data multi-tenancy
• Data retention issues
• Data dispersal and international privacy laws
• EU Data Protection Directive and U.S. Safe Harbor program
• Exposure of data to foreign governments and data subpoenas
Processing Infrastructure
• Application multi-tenancy
• Reliance on hypervisors
• Process isolation / Application sandboxes
What Has Changed

10.
Security. Analytics. Insight.10
Trusting vendor’s security model
• Obtaining support for investigations
• Inability to respond to audit findings
Risk = (Threat, Vulnerability)
• Hypervisor escaping
• Stored credentials
• Web ubiquity
• Shared resources
• Using external services
- Proprietary implementationscan’tbeexamined
- Availability of services
- Confidentialityof services
• Malicious insiders
• Data storage

11.
Security. Analytics. Insight.11
The Good
• Cloud homogeneity makes security auditing/testing simpler
• Clouds enable automated security management
• Redundancy / Disaster Recovery
• Distributed denial of service (DDoS) protection
The Bad
• Loss of physical control
• No more network-based Intrusion Detection
• No data leak prevention (DLP)
• Little network routing mechanisms
• Reliance on third parties
Changes in Security

12.
Big Data For Cyber Security & Intelligence
"There are 1000 ways for someone to steal information. If we knew
how, we could prevent it. Visualization helps find that one way.”
• Visualization to gain
insight into big data
• Cloud as an intelligence
and data sharing platform
• Security through insights
• Security as a profit center

13.
13
raffael.marty@pixlcloud.com