Transcript Complexity Analysis

ICFS
Instituto de Ciencias Forenses y de la Seguridad
Alvaro Ortigosa
Transatlantic Network
Security Initiative
Combining Technical Analysis
with Social Network Analysis for
an Early Warning System for
Cyber Attacks
IP: Sanjay Goel
SCADA Systems
Infrastructure Risk
• SCADA
systems
integrated
• Recent
reports claim
US power grid
compromised
• Possible link
between
blackouts and
terrorists
• Smart Grid
cause for
concern
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SCADA Systems
Infrastructure Risk
• There has been a
relative lack of
forthcoming information
on the attacks on the
critical infrastructure
• Probing and attacks
continue from several
sources (nations and
transnational groups)
• Attacks on the
infrastructure are
inevitable
• We need to intelligently
manage our risks
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SCADA Systems
Vulnerabilities in Infrastructure
1:58 pm
Eastlake
Ohio plant
shuts
down
3:06 pm A
First
Energy
345-KV
transmissi
on line
fails south
of
Cleveland
Ohio
4:10 pm Transmission lines
start tripping in Michigan and
Ohio blocking flow of power
East. Due to deficit
Generators shut down.
Causing blackout in the East
4:09 pm Voltage
sags as Ohio draws
2GW from Michigan
4:05 pm Sustained
power surge on
Ohio lines
3:17 pm Voltage dips
temporarily on Ohio portion
of grid causing power to
shift to another transmission
line which fails
3:41& 3:46 pm
2 breakers connecting
First Energy’s grid with
American Electric
Power tripped
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SCADA Systems
CAL-ISO Hacking
Hackers Victimize Cal-ISO
Dan Morain, June 09, 2001
For at least 17 days at the height of
the energy crisis, hackers mounted
an attack on a computer system
that is integral to the movement of
electricity throughout California…
The hackers' success, though
apparently limited, brought to light
lapses in computer security at the
target of the cyber-attack, the
California ISO, which oversees most
of the state's massive electricity
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transmission grid.
Power Grid
Incidents
2009
12 NOV; ONS, Brazil
Operador nacional do Sistema Eletrico (ONS)
is Brazil's national system operator responsible
for controlling the transmission of electricity as
well as the operation of generation facilities
throughout the nation. On November 12th, a
hacker gained access to its corporate network
but stopped short of accessing its operational
network.
Several prominent intelligence sources confirmed that there were a series of cyber
attacks in Brazil: one north of Rio de Janeiro in January 2005 that affected three
cities and tens of thousands of people, and another, much larger event beginning
on Sept. 26, 2007. The attack in the state of Espirito Santo affected more than
three million people in dozens of cities over a two-day period, causing major
disruptions. In Vitoria, the world's largest iron ore producer had seven plants
knocked offline, costing the company $7 million. It is not clear who did it or what the
motive was.
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Sanjay Goel, School of Business, UAlbany
Terrorism
Internet Use
• Mobilization of
public opinion /
sympathy
• Spread of
propaganda
• Solicitation of
new recruits,
donations
• Anonymous
non-traceable
communication
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Cyber Warfare
Russia & Georgia
'Cyberwar' Emerges Amid RussiaGeorgia Conflict
Georgia's recent conflict with Russia
over the fate of two separatist
provinces brought with it a first in
international cyber-warfare, as Georgia
faced a slew of Internet attacks.
Georgian government Web sites -including the president's office, the
parliament, and the foreign ministry
-- were defaced with anti-Georgian
or pro-Russian images. And
Georgia's Internet system was crippled,
as hackers manipulated computers to
flood government, news, and
information Web sites in a way that
renders them useless.
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Government Involvement
Chinese Espionage on Tibetan Exiles
Munk Center in Canada
shows that in less than 2
years, an electronic
spying operation in China
infiltrated at least 1,295
computers in 103
countries, including many
belonging to embassies,
foreign ministries and
other government offices,
as well as the Dalai
Lama’s Tibetan exile
centers in India, Brussels,
London and New York.
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Cyber Intelligence
Internet: An Arena for Terrorists
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Cyber Intelligence
“Looking for a Needle in a Haystack”
• Data-mining works when
– Search profile is well-defined
– Significant historical data for
predictions
– Low cost of false alarms
We failed to stop 9/11 despite
having critical intelligence
• In espionage, counterintelligence, or
terrorist plots
– Uncertainty of what data to ignore or
pay attention to
– Attacks often hard to predict (little
past data available)
– Avenues to hide involvement and
communication
– False positives could lead to arrest of
innocents and lost time on bad leads
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Cyber Intelligence
Attribution: Anonymity of the Internet
• No specific connection between real identity and internet
aliases (can be multiple web identities)
• How is this done?
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–
–
–
–
–
Anonymous web browsing, e.g. proxy servers
VoIP (e.g. Skype)
Private message boards
Chatrooms / IRC
Use of botnets (to send messages, relay, etc.)
Steganography with website / SPAM images
• Need intelligence techniques for assigning attribution
(means, motives, and opportunity)
Has anonymity gone too far?
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Cyber Intelligence
Tracking Incidents
• Countless ways in which computer can be used to
perform illegal activity
• Criminals leave behind traces that can be analyzed
– Evidence in several media forms, e.g., text, audio, image,
video
• Multiple sources of data are needed to corroborate
• We collect data from
• hacker blogs, websites, forums
• Network (logs, SNMP, etc.) using darknets,
honeynets, and other devices
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Cyber Intelligence
Social Network Analysis
•
•
Network Measures
• Density (number of dyads connected to
each other)
• Degree: Average number of connections
• Path length: Average # arcs in shortest
path between two nodes
• Clustering Coefficient: Measure of
grouping of nodes in graph
• Centralization: Measure of cohesion in
graph
Node Measures
• Degree: Number of connections of a node
• Betweenness: Critical link in the graph
• Closeness: Average distance to other
nodes
• Clique Count: # of cliques to which a node
belongs
Image Source: UMBC
HACKER
NETWORK
ANALYSIS ?
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Social Network Analysis
Alibaba Dataset
A 12 Member Terrorist Cell --connected with the Ali Baba Network
plans to “bake a cake” (build a
bomb) which will be targeted to blow
up a water treatment facility near
London. The plot takes place from
April to September of 2003
• A Simulated Signal Intelligence
and Human Intelligence
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–
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Approximately 800 reports.
8 month plot window.
409 named entities.
98 locations
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Robert Savell, School of Engineering, Dartmouith
Open Source Data
Proximity of concepts
• We are collecting data from targeted hacker forums/blogs/
websites
• Project Grey Goose
• Natural Language Processing is being used for analyzing
the data
• Process used for analyzing data
– Develop seed list of relevant concepts in domain of interest and
cluster web pages
– Develop concept graph for each cluster of documents, and use
concept co-occurrence distance and proximity filtering to reduce
edge density;
– Identify related communities of concept terms within each resulting
graph component.
– Manually assess each graph “community” and review the sets of
related pages for information of interest.
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Network Forensics
HoneyNet
• Honeynets are networks of honeypots
where all inbound and outbound traffic
is collected
– Multiple operating systems & applications
– Deploy services that closely match actual
conditions in the organization
• Any attempt to contact to the network
from outside is likely an attempt to
breach its security
• Any outbound activity is likely
evidence that a system has been
compromised.
• Hacking tools can fingerprint honey
pots/nets so they should be
camouflaged
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Network Forensics
DarkNet
• Darknet is a portion of routed, allocated IP space where no
active services or servers reside
– Consists of a server that gathers packets & flows that enter the Darknet
• Blocks contain no active hosts, thus traffic must be caused by
mis-configuration, backscatter from spoofed source
addresses, or scanning from worms and other probing.
• Can be used in conjunction with flow collectors, backscatter
detectors, sniffers and/or IDS boxes for further analysis
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Network Forensics
Distributed Darknet: Creating a Global Telescope
• Creating a network of darknets
across the globe with partners in
Israel, Spain, Russia, India, United
States
• Data can be collected in partner
country or addresses can point to
central data collection server in the
United States
• Comparing changes in behavior
across different darknets will help
identification of activity patterns and
identify malicious behavior
• Sharing honey net data further
improves analysis quality
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Securing the Internet
Conclusions
• Improve ability to detect attacks and respond
quickly (data collection and analysis)
• Collect global data
• Develop techniques for improving analysis
• Cooperative model based on shared intelligence
provides higher quality of alerts
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ICFS
Instituto de Ciencias Forenses y de la Seguridad
Próximamente: http://www.icfs.uam.es