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Secure Routing: Current routing schemes are resilient to simple failures, such as a node going down. Routes can be recomputed once the failed node is identified. However, in more catastrophic or adversarial settings, traditional routing approaches can perform poorly. Our work both evaluates previous approaches and also explores novel solutions.
We derived the notion of strong detection methods. A method implements strong detection if, given an inconsistency, the method identifies it, or there is no method that can identify it without changing/enhancing the routing protocol and state information collected. We also derived low-complexity strong detection methods for distance-vector, path-vector, and link-state routing protocols, and used them to explore the likelihood of detecting inconsistencies in these various classes of protocols.
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Multipath routing: In conventional single-path routing, intruders can easily compromise a data session by shutting down any intermediate node or link on the routing path that is being used by the data session. To address this problem, we consider distributed solutions that route a fixed throughput or the maximum possible throughput along the best set of multiple paths, such that the worst-case throughput loss due to a single-link attack is minimized. We also demonstrate that our distributed solutions are robust in response to various models of multi-link attacks.
In addition, to diagnose and correct failures in routing, we propose an efficient end-to-end inference algorithm that explores the behaviors of multiple paths and seeks to minimize the cost of recovering all network faults.
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Incentives: Nodes in mobile ad-hoc networks are often composed using nodes to forward traffic on behalf of one another. Without an appropriate incentive mechanism in place, situations can arise in which selfish nodes may refuse to forward traffic, since it provides them no direct benefit. We propose a credit exchange protocol for packet forwarding. A novel aspect of our proposed exchange is the decoupling of the notion of fairness from incentive. Using an algorithm that is distributed and adapts easily to changing network conditions, each node determines its own price of how much to charge for forwarding a packet, where price is a function of the various nodes' traffic demands and the routes that these demands take through the network. For any feasible allocation, each node's price is computed so that when each node achieves its throughput demand, the system is budget balanced. We show the conditions under which a unique pricing solution converges and all nodes are able to maintainsustainable and stable credit levels.
Data Persistence in Disaster Settings: Sensor networks deployed in disaster scenarios such as floods, fires, terrorist attacks or earthquakes pose an interesting design challenge since the sensor nodes used to collect and communicate data may themselves fail suddenly and unpredictably, resulting in the loss of valuable data. Furthermore, because these networks are often expected to be deployed in response to a disaster, or because of sudden configuration changes due to failure, these networks are often expected to operate in a "zero configuration" paradigm, where data collection and transmission must be initiated immediately, before the nodes have a chance to assess the current network topology. We design and analyze techniques to increase "persistence" of sensed data, so that data is more likely to reach a data sink, even as network nodes fail. We propose "Growth Codes", a novel data encoding technique which improves data persistence in a sensor network and accelerates delivery of distributed sensor data to the sink(s).
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Enabling Robot Navigation Through Sensor Nets: Recent approaches to robotic search and rescue have generally assumed the availabilty of hardware services such as GPS or magnetic compass. Our work examines how an ad-hoc sensor network can be used to guide robotic searchers towards beacon targets in absence of GPS and similiar services. We leverage a simple distributed algorithm to propogate a network-wide gradient towards beacon targets. Demo
Worm detection: It is a commonly held belief that IPv6 provides greater security against random-scanning worms by virtue of a very sparse address space. We show that an intelligent worm can exploit the directory and naming services necessary for the functioning of any network, and we model the behavior of such a worm. We explore via analysis and simulation the spread of such worms in an IPv6 Internet. Our results indicate that such a worm can exhibit propagation speeds comparable to an IPv4 random-scanning worm. We develop a detailed analytical model that reveals the relationship between network parameters and the spreading rate of the worm in an IPv6 world as well as develop a simulator based on our analytical model. Simulation results using parameters from real measurements indicate that an intelligent worm can spread surprisingly fast in an IPv6 world by using simple yet intelligent scanning strategies.
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P2P Pollution: P2P Systems are highly vulnerable to pollution attacks. We use fluid modeling to explore various strategies by both the polluters and the clients trying to get the valid copy.
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Old Projects:
SOS: Distributed Denial of Service (DDoS) Attacks are mounted by a malicious user or set of users who seek to block access to a particular target site by sending packets from multiple compromised network locations at the target. Our Secure Overlay Services (SOS) work investigated how to use overlay networks to proactively protect target sites, such as web servers, from direct attack.
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The project is also described by our colleagues and collaborators in the NSL Lab on their pages.