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SUMMARY:Exploiting Temporal Complex Network Metrics in Mobile Malware Cont
 ainment - John Tang (University of Cambridge)
DTSTART:20110616T150000Z
DTEND:20110616T160000Z
UID:TALK31670@talks.cam.ac.uk
CONTACT:Eiko Yoneki
DESCRIPTION:Malicious mobile phone worms spread between devices via short-
 range Bluetooth contacts\, similar to the propagation of human and other b
 iological viruses. Recent work has employed models from epidemiology and c
 omplex networks to analyse the spread of malware and the effect of patchin
 g specific nodes. These approaches have adopted a static view of the mobil
 e networks\, i.e.\, by aggregating all the edges that appear over time\, w
 hich leads to an approximate representation of the real interactions: inst
 ead\, these networks are inherently dynamic and the edge appearance and di
 sappearance are highly influenced by the ordering of the human contacts\, 
 something which is not captured at all by existing complex network measure
 s.\nIn this paper we first study how the blocking of malware propagation t
 hrough immunisation of key nodes (even if carefully chosen through static 
 or temporal betweenness centrality metrics) is ineffective: this is due to
  the richness of alternative paths in these networks. Then we introduce a 
 time-aware containment strategy that spreads a patch message starting from
  nodes with high temporal closeness centrality and show its effectiveness 
 using three real-world datasets. Temporal closeness allows the identificat
 ion of nodes able to reach most nodes quickly: we show that this scheme re
 duces the cellular network resource consumption and associated costs\, ach
 ieving\, at the same time\, complete containment of malware in a limited a
 mount of time.\n
LOCATION:FW26\, Computer Laboratory\, William Gates Builiding
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