SOCELLBOT: A New Botnet Design to Infect Smartphones via Online Social

Networking

2012 25th IEEE Canadian Conference on Electrical and Computer Engineering(CCECE)

Speaker: 呂映萱102/10/24

Mahammad Reza Faghani and Uyen Trang Nguyen

Outline• Abstract• Introduction• The proposed SoCellBot• Simulation• Results• Conclusion

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Abstract• Smartphone • Online Social network(OSN)• A new cellular botnet named SoCellBot

o Harder to detecto More resilient to bot failureso More cost-effective to cellular bots

• Raising awareness of new mobile botnets• Preventive measures to deter SoCellBot

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Introduction

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OSNs

• Why are OSNs?1. Most cellular network providers offer OSN access to their clients free

of charge.2. Messages exchanged in OSNs are usually encrypted.3. The topology of an OSN-based botnet is more resilient to bot failures

or unavailability thanks to the highly clustered structure of the social network graph.

The proposed SoCellBot

• SoCellBot Infects smartphones with malware• The medium to recruit bots is OSN

o Unlike SMS-based botnets, SoCellBot incurs small monetary costs.

• Architectureo Propagation mechanismo Command and Control channel o Botnet topology maintenance

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The proposed SoCellBot

• Propagation Mechanismo Using social engineering techniques

• Eye-caching web link

• Infiltration

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The proposed SoCellBot

• Command and Control Channelo Online social network messaging system (OSNMS)o Using an algorithm to disguise the commands to be normalo Sending message to a random user in Facebook is possible

• Infected users then infect their friends

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The proposed SoCellBot

• SoCellBot Botnet Topologyo Ensured to be connectedo It is Resilient to bot failures and unavailability

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Simulation• OSN Model and Graphs

• Characteristics of OSNo Degreeo Clustering coefficiento High clusteringo Low average network distance

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Simulation Parameters• Original OSN

o 3 OSNs of size 5000, 10000, 15000o Using the algorithm by Holme and Beom to generate

• Equivalent random graphs(ERG)o Creating ERG by using an algorithm by Viger and Latapy

• Why ERG ?o ERG helps a malware to propagate faster than the original OSN grapho An attacker may be able to obtain the graph of OSN using a tool such

as R[12] or Pajek[2]

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Simulation• Malware Propagation Model

1. Randomly choosing a node(user) for infiltration2. If (the user executes the command)

• The user’s smartphone sends out a message to his/her friends, directing them to the malicious content (adjacent vertices in the social network graph)

• Upon receiving the message, each friend will execute the malware with a probability p

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Simulation• Setting fields to each command

o A unique sequence number (SN)• SNs help to minimize the number of duplicate messages

o Time-to-live (TTL)• A good estimate for the TTL is the diameter of the OSN graph

• How to avoid detection?o After receiving a command, a node checks the SN to see if it has seen the

message before.• if (message is new)

o TTL-1o Forwarding the message to its one-hop neighbors (adjacent

vertices)• else if (message is duplicate)

o The node simply discards it

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Results• ….

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As p from 0.5 to 1,the malware propagate faster

Results

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The first set of experiments- Scenario 2 and 3

Results

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Conclusion• OSNs are more suitable for mobile botnet

communications than the traditional SMS• The highly clustered structure of OSNs make the

botnet immune from random node failures

• Disadvantageo It doesn’t show us the preventive measure

• Cautions is the parent of safety

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