UMD - University of Maryland

These publications were done for the Lablet activities at this school, and were listed in the Quarterly Reports back to the government. Please direct any comments to research (at) securedatabank.net if there are any questions or concerns regarding these publications.

UMD - University of Maryland, College Park
Topic: Trust, Recommendation Systems, and Collaboration
Title: A Fresh Look at Network Science: Interdependent Multigraphs Models Inspired From Statistical Physics
Author(s): J.S. Baras
Hard Problem: Scalability and Composability, Policy-Governed Secure Collaboration, Human Behavior
Abstract: Baras, J.S., "A fresh look at network science: Interdependent multigraphs models inspired from statistical physics," Communications, Control and Signal Processing (ISCCSP), 2014 6th International Symposium on , vol., no., pp.497,500, 21-23 May 2014
doi: 10.1109/ISCCSP.2014.6877921
We consider several challenging problems in complex networks (communication, control, social, economic, biological, hybrid) as problems in cooperative multi-agent systems. We describe a general model for cooperative multi-agent systems that involves several interacting dynamic multigraphs and identify three fundamental research challenges underlying these systems from a network science perspective. We show that the framework of constrained coalitional network games captures in a fundamental way the basic tradeoff of benefits vs. cost of collaboration, in multi-agent systems, and demonstrate that it can explain network formation and the emergence or not of collaboration. Multi-metric problems in such networks are analyzed via a novel multiple partially ordered semirings approach. We investigate the interrelationship between the collaboration and communication multigraphs in cooperative swarms and the role of the communication topology, among the collaborating agents, in improving the performance of distributed task execution. Expander graphs emerge as efficient communication topologies for collaborative control. We relate these models and approaches to statistical physics. (ID#:14-2618)
URL: http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6877921&url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel7%2F6862736%2F6877795%2F06877921.pdf%3Farnumber%3D6877921
Publication Location: Proceedings 6th International Symposium on Communications, Control and Signal Processing (ISCCSP 2014)

UMD - University of Maryland, College Park
Topic: Trust, Recommendation Systems, and Collaboration
Title: Using Trust in Distributed Consensus With Adversaries in Sensor and Other Networks
Author(s): X. Liu and J.S. Baras
Hard Problem: Scalability and Composability, Policy-Governed Secure Collaboration, Human Behavior
Abstract: From UMD.edu: Extensive research efforts have been devoted to distributed consensus with adversaries. Many diverse applications drive this increased interest in this area including distributed collaborative sensor networks, sensor fusion and distributed collaborative control. We consider the problem of detecting Byzantine adversaries in a network of agents with the goal of reaching consensus. We propose a novel trust model that establishes both local trust based on local evidences and global trust based on local exchange of local trust values. We describe a trust-aware consensus algorithm that integrates the trust evaluation mechanism into the traditional consensus algorithm and propose various local decision rules based on local evidence. To further enhance the robustness of trust evaluation itself, we also provide a trust propagation scheme in order to take into account evidences of other nodes in the network. Then we show by simulation that the trust aware consensus algorithm can effectively detect Byzantine adversaries and excluding them from consensus iterations even in sparse networks with connectivity less than 2f + 1, where f is the number of adversaries. These results can be applied for fusion of trust evidences as well as for sensor fusion when malicious sensors are present like for example in power grid sensing and monitoring (ID#:14-2619)
URL: https://www.isr.umd.edu/~baras/publications/papers/2014/X_%20Liu_J_S_%20Baras_Using_Trust_in_Distributed_Consensus.html
Publication Location: Proceedings of 17th International Confernce on Information Fusion (FUSION 2014)

UMD - University of Maryland, College Park
Topic: Trust, Recommendation Systems, and Collaboration
Title: Soft Contract Verification
Author(s): Nguyen, Tobin-Hochstadt, Van Horn
Abstract: Phuc C. Nguyen, Sam Tobin-Hochstadt, and David Van Horn. 2014. Soft contract verification. InProceedings of the 19th ACM SIGPLAN international conference on Functional programming (ICFP '14). ACM, New York, NY, USA, 139-152. DOI=10.1145/2628136.2628156 http://doi.acm.org/10.1145/2628136.2628156
Behavioral software contracts are a widely used mechanism for governing the flow of values between components. However, run-time monitoring and enforcement of contracts imposes significant overhead and delays discovery of faulty components to run-time.

To overcome these issues, we present soft contract verification, which aims to statically prove either complete or partial contract correctness of components, written in an untyped, higher-order language with first-class contracts. Our approach uses higher-order symbolic execution, leveraging contracts as a source of symbolic values including unknown behavioral values, and employs an updatable heap of contract invariants to reason about flow-sensitive facts. We prove the symbolic execution soundly approximates the dynamic semantics and that verified programs can't be blamed.

The approach is able to analyze first-class contracts, recursive data structures, unknown functions, and control-flow-sensitive refinements of values, which are all idiomatic in dynamic languages. It makes effective use of an off-the-shelf solver to decide problems without heavy encodings. The approach is competitive with a wide range of existing tools - including type systems, flow analyzers, and model checkers - on their own benchmarks. (ID#:14-2620)
URL: http://dl.acm.org/citation.cfm?id=2628156
Publication Location: proceedings of The 19th ACM SIGPLAN International Conference on Functional Programming 2014


UMD - University of Maryland, College Park
Topic: Verifcation of Hyperproperties
Title: Temporal Logics for Hyperproperties
Author(s): Michael R. Clarkson, Bernd Finkbeiner, Masoud Koleini, Kristopher K. Micinski, Markus N. Rabe, and Cesar Sanchez
Abstract: Available from Springer the via link listed below. (ID#:14-2621)
URL: http://link.springer.com/chapter/10.1007%2F978-3-642-54792-8_15
Publication Location: Conference on Principles of Security and Trust 2014

Note:

Articles listed on these pages have been found on publicly available internet pages and are cited with links to those pages. Some of the information included herein has been reprinted with permission from the authors or data repositories. Direct any requests via Email to SoS.Project (at) SecureDataBank.net for removal of the links or modifications to specific citations. Please include the ID# of the specific citation in your correspondence.