Title
Detecting Route Attraction Attacks in Wireless Networks
Abstract
Selecting high performance routes in wireless networks requires the exchange of link quality information among nodes. Adversaries can manipulate this functionality by advertising fake qualities for links; by doing so, they can attract routes and subsequently launch pernicious attacks. Our measurements suggest that malicious route attraction can fatally impact throughput. We design a framework that is effective against both independent and colluding attackers. In the latter case, we consider both local and remote colluders. With local collusion, malicious nodes exchange and advertise fake routing information to increase the probability of being selected as relays. Remote collusion refers to nodes residing in distant parts of the network that (i) create sybil identities in a local neighborhood and / or (ii) utilize link quality reports to advertise fake links. Our framework combines packet signing and frequency hopping to accurately detect the adversaries. We implement the framework on our testbed and conduct experiments to assess its efficacy. We observe that our framework provides significant throughput benefits by detecting attackers with 90% accuracy.
Year
DOI
Venue
2011
10.1109/MASS.2011.44
MASS
Keywords
Field
DocType
local collusion,local neighborhood,fake routing information,detecting route attraction attacks,impact throughput,link quality information,malicious nodes exchange,fake link,malicious route attraction,link quality report,fake quality,wireless networks,throughput,measurement,routing,vectors
Wireless network,Computer science,Computer security,Network packet,Testbed,Computer network,Telecommunication security,Attraction,Throughput,Frequency-hopping spread spectrum,Collusion
Conference
ISSN
ISBN
Citations 
2155-6806
978-1-4577-1345-3
2
PageRank 
References 
Authors
0.36
0
6
Name
Order
Citations
PageRank
Mustafa Y. Arslan134018.06
Konstantinos Pelechrinis269248.45
Ioannis Broustis342529.27
Srikanth V. Krishnamurthy464561.55
Prashant Krishnamurthy51222104.71
Prasant Mohapatra64344304.46