This article consists of a collection of slides from the author's conference presentation.

Disruption-Tolerant Networks (DTNs) deliver data in network environments composed of intermittently connected nodes. Just as in traditional networks, malicious nodes within a DTN may attempt to delay or destroy data in transit to its destination. Such attacks include dropping data, flooding the network with extra messages, corrupting routing tables, and counterfeiting network acknowledgments. Many existing methods for securing routing protocols require authentication supported by mechanisms such as a public key infrastructure, which is difficult to deploy and operate in a DTN, where connectivity is sporadic. Furthermore, the complexity of such mechanisms may dissuade node participation so strongly that potential attacker impacts are dwarfed by the loss of contributing participants. In this paper, we use connectivity traces from our UMass DieselNet project and the Haggle project to quantify routing attack effectiveness on a DTN that lacks security. We introduce plausible attackers and attack modalities and provide complexity results for the strongest of attackers. We show that the same routing with packet replication used to provide robustness in the face of unpredictable mobility allows the network to gracefully survive attacks. In the case of the most effective attack, acknowledgment counterfeiting, we show a straightforward defense that uses cryptographic hashes but not a central authority. We conclude that disruption-tolerant networks are extremely robust to attack; in our trace-driven evaluations, an attacker that has compromised 30% of all nodes reduces delivery rates from 70% to 55%, and to 20% with knowledge of future events. By comparison, contemporaneously connected networks are significantly more fragile.

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Most large network management centers have relatively low skilled personnel as their first level operations staff. Many organizations attempt to cope with this situation by restricting the set of problems these people have to deal with to those which are well understood and documented. Several software packages exist which can correlate and filter incoming events from the network and present a select subset to the operator. Unfortunately, programming these fault management applications requires considerable expertise and effort. Often, once the initial development is done, the implementation remains static, while the network itself is dynamic. This paper proposes a methodology for documenting known faults and responses, programming fault correlation engines, continuously examining real behavior, and feeding the result back into the programming process. This results in a continuous improvement in fault management intelligence, with corresponding improvement in network availability and thus value of the network to the organization.