@conference {
	title = {Coalition Formation and Trust in Collaborative Control},
	author = {Baras, John S., Jiang, Tao., Hovareshti, Pedram.},
	year = {2009},
	month = {08/2009},
	abstract = {We consider the collaboration of autonomous agents as a coalitional game subject to constraints, like communication, trust or reputation. We analyze the tradeoff between the benefits of collaboration and these constraints (or costs of collaboration) via dynamic, iterative stochastic games. The agents can observe locally the actions of other agents in their neighborhood and decide whether to collaborate or not in a distributed asynchronous manner. Trust values are taken into consideration when agents act and collaborate. Specifically they affect the selection of agents to collaborate with. We consider only problems where the information used for either estimating reputations or deciding on strategies is mostly local; i.e. from the neighbors of each agent. We show that randomized algorithms emerge as the agents try to reach the maximum payoff. We also investigate the topology of the formed network by studying the second largest eigenvalue of the corresponding graph, and describe its effects on control performance.},
	address = {Budapest, Hungary},
	booktitle = {European Control Conference 2009 (ECC {\textquoteright}09)},
	pages = {pp.1197-1202}
}
@conference {
	title = {A Composite Trust Model and its Application to Collaborative Distributed Information Fusion},
	author = {Matei, Ion., Baras, John S., Jiang, Tao.},
	year = {2009},
	month = {07/2009},
	abstract = {We consider distributed state estimation of~linear dynamic systems, observed by various sensors, as a problem in information fusion. We introduce a novel model of trust, using weights on the graph links and nodes that represent the sensor network. These weights can represent several interpretations of trustworthiness in sensor networks. We describe three algorithms that integrate distributed Kalman filtering with these trust weights. We consider two interpretations of these trust weights as information accuracy and reliability. We show that by appropriate use of these weights the distributed estimation algorithm avoids using information from untrusted sensors. Simulation experiments further demonstrate the behavior of these algorithms.},
	address = {Seattle, WA},
	booktitle = {12th International Conference on Information Fusion (Fusion 2009)},
	pages = {pp. 1950-1957}
}
@conference {
	title = {Coalition Formation through Learning in Autonomic Networks},
	author = {Jiang, Tao., Baras, John S.},
	year = {2009},
	month = {05/2009},
	abstract = {Autonomic networks rely on the cooperation of participating nodes for almost all their functions. However, due to resource constraints, nodes are generally selfish and try to maximize their own benefit when participating in the network. Therefore, it is important to study mechanisms, which can be used as incentives for cooperation inside the network. In this paper, the interactions among nodes are modeled as games. A node joins a coalition if it decides to cooperate with at least one node in the coalition. The dynamics of coalition formation proceed via nodes that interact strategically and adapt their behavior to the observed behavior of others. We present conditions that the coalition formed is stable in terms of Nash stability and the core of the coalitional game.},
	address = {Istanbul, Turkey},
	booktitle = {International Conference on Game Theory for Networks (GameNets09)},
	pages = {pp.10-16}
}
@conference {
	title = {Performance Comparison of Two Sequential Change Detection Algorithms on Detection of In-band Wormholes},
	author = {Zheng, Shanshan., Jiang, Tao., Baras, John S.},
	year = {2009},
	month = {03/2009},
	abstract = {This paper compares the performance of parametric and non-parametric sequential change detection algorithms for detecting in-band wormholes in wireless ad hoc networks. The algorithms considered are the non-parametric cumulative sum (NP-CUSUM) and the repeated sequential probability ratio test (R-SPRT). Theoretical performance of the two is compared using metrics that take into account the algorithms{\textquoteright} repeated nature, and the advantage of the parametric method is illustrated. On the other hand, connections between the parametric and non-parametric methods are made in the proposed worst-case adversary model, where the non-parametric method is shown to be more robust to attack strategy changes. Experimental evaluation of wormhole detection schemes based on the two algorithms is presented. This work has implications for both the theoretical understanding and practical design of wormhole detection schemes based on parametric and nonparametric change detection algorithms.},
	address = {Baltimore, MD},
	booktitle = {Conference on Information Sciences and Systems (CISS 2009)},
	pages = {pp.270-275}
}
