Software Engineering Institute | Carnegie Mellon University
Software Engineering Institute | Carnegie Mellon University

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Publication Date

Joseph Giampapa
February 2014 - Presentation SCADA Resilience via Autonomous Cyber-Physical Agents

Topics: Cyber-Physical Systems

Slide presentation for the Ninth Annual Carnegie Mellon Conference on the Electricity Industry.

January 2014 - Poster Designing SCADA Systems for the Self-Verifiability of Their Security and Survivability

Topics: Cyber-Physical Systems

Authors: Joseph Giampapa

This poster describes a cyber-physical and agent-based approach to detecting and recovering from a false data injection attack on a power grid supervisory control and data acquisition (SCADA) system.

October 2013 - Conference Paper Test and Evaluation of Autonomous Multi-Robot Systems

Topics: Pervasive Mobile Computing

Authors: Joseph Giampapa

This powerpoint presentation was given at the NDIA Annual System Engineering Conference in October 2013.

July 2013 - Conference Paper Probabilistic Verification of Coordinated Multi-Robot Missions

Topics: Cyber-Physical Systems

In this paper, the authors advocate, formalize, and empirically justify an approach to compute quantitative utility of robotic missions using probabilistic model checking.

May 2013 - Conference Paper Towards a Quantitative Method for Assuring Coordinated Autonomy

This article introduces a reliability engineering assurance approach based on probabilistic model checking.

May 2010 - White Paper Edge Enabled Systems

Topics: Ultra-Large-Scale Systems

This paper describes the characteristics of edge systems and the edge organizations in which these systems operate, and make initial recommendations about how such systems and organizations can be created to serve the needs of users at the edge.

March 2010 - Presentation Overview of Distributed Constraint Satisfaction and Optimization

Topics: Ultra-Large-Scale Systems

This presentation describes problem-solving algorithms and presents Distributed Constraint Optimization Problems (D-COP) algorithms as a "toolbox" for agent-based modeling.