@conference {
	title = {Broadband Mobile Wireless Infrastructures: The Next {\textquoteleft}Massive Impact{\textquoteright} Paradigm Shift},
	author = {Baras, John S.},
	year = {2006},
	month = {07/2006},
	address = {Tokyo, Japan},
	organization = {Fujitsu Laboratories, Kawasaki}
}
@conference {
	title = {Vehicle Wireless Networks},
	author = {Baras, John S.},
	year = {2006},
	month = {07/2006},
	address = {Tochigi, Japan},
	organization = {HONDA R\&D Center}
}
@conference {
	title = {Scalable and Distributed Control Laws for Network flow Optimization},
	author = {Chen, Huigang., Baras, John S.},
	year = {2006},
	month = {07/2006},
	abstract = {We investigate the design of scalable and distributed control laws for flow control in a large network - equivalently an optimization problem. We identify the implications of the desired "plug-and-play{\textquoteright} property of of such protocols and propose design principles upon which our algorithm should be built: the class of our algorithms must achieve little extra communication cost and global asymptotic stability. General structural properties of such algorithms are presented and we finally provide an algorithm which satisfies our design principles for a network with heterogeneous delays.},
	address = {Kyoto, Japan},
	booktitle = {17th International Symposium on Mathematical Networks and Systems},
	pages = {pp. 42-49}
}
@conference {
	title = {Linear Iterations on Ordered Semirings for Trust Metric Computation and Attack Resiliency Evaluation},
	author = {Theodorakopoulos, George., Baras, John S.},
	year = {2006},
	month = {07/2006},
	abstract = {Within the realm of network security, we interpret the concept of trust as a relation among entities that participate in various protocols. Trust relations are based on evidence created by the previous interactions of entities within a protocol. In this work, we are focusing on the evaluation of trust evidence in Ad Hoc Networks. Because of the dynamic nature of Ad Hoc Networks. Because of the dynamic nature of Ad Hoc Networks, trust evidence may be uncertain and incomplete. Also, no pre-established infrastructure can be assumed. The evaluation process is modelled as a path problem on a directed graph, where nodes represent entities, and edges represent trust relations. We develop a novel formation of trust computation as linear interactions on ordered semirings. Using the theory of semirings, we analyze several key problems on the performance of trust algorithms. We also analyze the resilience to attacks of the resulting schemes.},
	address = {Kyoto, Japan},
	booktitle = {Proceedings of the 17th International Symposium on Mathematical Networks and Systems},
	pages = {pp. 509-514}
}
@conference {
	title = {B-ROC Curves for the Assessment of Classifiers over Imbalanced Data Sets},
	author = {Cardenas, Alvaro A., Baras, John S.},
	year = {2006},
	month = {07/2006},
	abstract = {The class imbalance problem appears to be ubiquitous to a large portion of the machine learning and data mining communities. One of the key questions in this setting is how to evaluate the learning algorithms in the case of class imbalances. In this paper we introduce the Bayesian Receiver Operating Characteristic (B-ROC) curves, as a set of tradeoff curves that combine in an intuitive way, the variables that are more relevant to the evaluation of classifiers over imbalanced data sets. This presentation is based on section 4 of (C{\textasciiacute}ardenas, Baras, \&amp; Seamon 2006).},
	address = {Boston, Massachusetts},
	booktitle = {21st National Conference on Artificial Intelligence, (AAAI 06) Nectar track,},
	pages = {pp. 1581-1584}
}
@conference {
	title = {Evaluation of Classifiers Practical Considerations for Security Applications},
	author = {Cardenas, Alvaro A., Baras, John S.},
	year = {2006},
	month = {07/2006},
	abstract = {In recent years several tools based on statistical methods and machine learning have been incorporated in security related tasks involving classification, such as intrusion detection systems (IDSs), fraud detection, spam filters, biometrics and multimedia forensics. Measuring the security performance of these classifiers is an essential part for facilitating decision making, determining the viability of the product, or for comparing multiple classifiers. There are however relevant considerations for security related problems that are sometimes ignored by traditional evaluation schemes. In this paper we identify two pervasive problems in securityrelated applications. The first problem is the usually large class imbalance between normal events and attack events. This problem has been addressed by evaluating classifiers based on cost-sensitive metrics and with the introduction of Bayesian Receiver Operating Characteristic (B-ROC) curves. The second problem to consider is the fact that the classifier or learning rule will be deployed in an adversarial environment. This implies that good performance on average might not be a good performance measure, but rather we look for good performance under the worst type of adversarial attacks. In order to address this notion more precisely we provide a framework to model an adversary and define security notions based on evaluation metrics},
	address = {Boston, MA},
	booktitle = {AAAI Workshop on Evaluation Methods for Machine Learning}
}
@conference {
	title = {Evaluation of Classifiers: Practical Considerations for Security Applications},
	author = {Cardenas, Alvaro A., Baras, John S.},
	year = {2006},
	month = {07/2006},
	abstract = {In recent years several tools based on statistical methods and machine learning have been incorporated in security related tasks involving classification, such as intrusion detection systems (IDSs), fraud detection, spam filters, biometrics and multimedia forensics. Measuring the security performance of these classifiers is an essential part for facilitating decision making, determining the viability of the product, or for comparing multiple classifiers. There are however relevant considerations for security related problems that are sometimes ignored by traditional evaluation schemes. In this paper we identify two pervasive problems in security related applications. The first problem is the usually large class imbalance between normal events and attack events. This problem has been addressed by evaluating classifiers based on cost-sensitive metrics and with the introduction of Bayesian Receiver Operating Characteristic (B-ROC) curves. The second problem to consider is the fact that the classifier or learning rule will be deployed in an adversarial environment. This implies that good performance on average might not be a good performance measure, but rather we look for good performance under the worst type of adversarial attacks. In order to address this notion more precisely we provide a framework to model an adversary and define security notions based on evaluation metrics.},
	address = {Boston, Massachusetts},
	booktitle = {AAAI Workshop on Evaluation Methods for Machine Learning}
}
@conference {
	title = {Modeling and Synthesis of Networked Systems},
	author = {Baras, John S.},
	year = {2006},
	month = {07/2006},
	address = {Paris, France},
	booktitle = {Joint CTS-HYCON Workshop on Nonlinear Research and Hybrid Control}
}
@conference {
	title = {Ray-Tracing Simulation of the NICT Channel Measurements},
	author = {Sayrafian, Kamran., Neekzad, Behnam., Perez, Julio., Baras, John S.},
	year = {2006},
	month = {07/2006},
	address = {San Diego, CA},
	booktitle = {IEEE Standard 802.15.3c mm-Wave channel modeling subgroup}
}
@conference {
	title = {Modeling Key Agreement in Multi-Hop Ad Hoc Networks},
	author = {Crescenzo, Giovanni Di., Striki, Maria., Baras, John S.},
	year = {2006},
	month = {07/2006},
	abstract = {Securing multicast communications in ad hoc networks has become one of the most challenging research directions in the areas of wireless networking and security. This is especially true as ad hoc networks are emerging as the desired environment for an increasing number of civilian, commercial and military applications, also addressing an increasingly large number of users. In this paper we study a very basic security question for Ad Hoc Networks: Key Agreement against passive adversaries. Despite being a widely studied area in wired networks, the problem becomes significantly more challenging for ad hoc networks, and even more for sensor networks, due to lack of trusted entities, infrastructures, full connectivity, routing structures, and due to severe limitations on the resources and capabilities of network nodes. In this paper we perform a comprehensive investigation of Key Agreement over resource constrained ad hoc networks. First, we formally model the key agreement problem over multi-hop ad hop networks, and we directly extend known key agreement protocols for wired networks, and evaluate the efficiency of such approaches. We then go beyond natural extensions of such protocols, by proposing non-trivial extensions based on efficient topology-driven simulations of logical networks over an arbitrary physical network, in order to optimize the most significant metrics of interest for such networks: i.e. bandwidth, latency, processing cost. Indeed, the resulting protocols are significantly more efficient in some or all of the above metrics, as our analytical results indicate},
	address = {Vancouver, Canada},
	booktitle = {2006 International Wireless Communications and Mobile Computing Conference},
	pages = {pp. 39-44}
}
