There is an increasing trend towards federated distributed systems, i.e., systems that are operated jointly by multiple different organizations or individuals. The interests of the participants in such a system are often highly diverse and/or in conflict with one another; for example, participants may be business competitors or based in hostile nations. Thus, federated systems are inherently vulnerable to insider attacks: the participants can try to subvert the system, exploit it for their own benefit, or attack other participants.
However, the participants in a federated system are typically connected in the 'offline world' as well, e.g., through social networks or business relationships. This context can be leveraged to handle misbehavior through well-known, time-tested techniques like accountability and transparency. For example, if one participant can detect and prove that another participant has misbehaved, she can sue that participant for breach of contract.
The goal of this research is to develop a key technology for enabling this approach, namely a reliable and general way to generate and verify evidence of misbehavior in federated systems. The project (i) studies the fundamental tradeoffs, requirements, and inherent costs of creating evidence; (ii) develops new algorithms for efficiently supporting different kinds of evidence; and (iii) evaluates these algorithms in the context of practical systems.
The project is integrated with Penn's new undergraduate program in Market and Social Systems Engineering. It will produce and freely distribute software that can be used to defend federated systems against attacks and malicious insiders.
