George Cybenko

Research Interests

Information systems and theory

Education

BSc, Mathematics, University of Toronto 1974
MA, Mathematics, Princeton University 1975
PhD, Mathematics, Princeton University 1978

Awards

SPIE Eric A. Lehrfeld Award, 2016
USAF Commander’s Public Service Award, 2016

Startups

FlowTraq (Riverbed)
Co-Founder and Chief Scientist

Research Projects

Agent-based systems engineering

Agent-based systems engineering

Agent-based systems engineering aims to successfully cross-fertilize the fields of systems engineering and artificial intelligence. Systems engineering (control, signal processing and communications) focuses primarily on physical domains that can be characterized by rich mathematical dynamics while artificial intelligence deals with human perception, decision making and action. Goals of such cross-fertilization are to explore the modeling, performance and scientific foundations of software agent systems using ideas from classical systems engineering and computer engineering.
Deception detection

Deception detection

Deception detection aims to automatically detect and infer the intentions behind deceptive actions. Our objectives are to 1) develop a framework for categorizing and classifying errors that may be committed by an expert, since not all errors are deception; and 2) design algorithms for automatic deception detection capable of providing detailed evidential information and explanation of deception intent, plus analysis of the deception's impact. Like insider threat, deception detection can occur in any number of scenarios and domains, and insider threat and deception detection are often interrelated.
Insider threat

Insider threat

Insider threat and deception detection are two areas that focus on user actions and their impacts upon the systems with which they interact. Insider threat aims to understand and prevent malicious activities that are instigated by "trusted" users on complex computer/information systems. Such activities cover a broad spectrum ranging from simple theft of confidential data to the more subtle alteration of system performance and/or information. For the latter, examples can include minor perturbation of a component specification in a manufacturing process resulting in a rippling effect of final component failure to influencing the decision-makers by modifying their information flow and content. The goal is to model insider threat in order to predict behavior and ultimately infer their goals and intentions.
Process query systems

Process query systems

Process query systems have applications that involve using databases or datastreams of events to detect instances of processes. In those applications, events provide evidence that is used to infer the existence and estimate the states of the various processes of interest. Examples of such applications include: network and computer security; network management; sensor network tracking; military situational awareness; and critical infrastructure monitoring and protection.