CERIAS Weekly Security Seminar – Purdue University
Vast resources are devoted to predicting human behavior in domainssuch as economics, popular culture, and national security, but thequality of such predictions is often poor. Thus, it is tempting toconclude that this inability to make good predictions is a consequenceof some fundamental lack of predictability on the part of humans.However, recent work offers evidence that the failure of standardprediction methods does not indicate an absence of humanpredictability but instead reflects:1. misunderstandings regarding which features of human dynamicsactually possess predictive power2. the fact that, until recently, it has not been possible to measurethese predictive features in real world settings.This talk introduces some of the science behind these basicobservations and demonstrates their utility in various case studies.We begin by considering social groups in which individuals areinfluenced by the behavior of others. Correctly identify andunderstanding the social forces in these situations can increase theextent to which the outcome of a social process can be predicted inits very early stages. This finding is then leveraged to designprediction methods which outperform existing techniques for predictingsocial network dynamics. We also look at the analysis of thepredictability of adversary behavior in the co-evolutionary "armsraces" that exist between attackers and defenders in many domains. Ouranalysis reveals that conventional wisdom regarding these co-evolvingsystems is incomplete, and provides insights which enable thedevelopment of predictive methods for computer network security. About the speaker: David Zage is a senior member of Sandia National Laboratories in theCyber Analysis R&D group. His main research interest are in the areasof security, networking, and distributed systems. David received hisPh.D. in computer science from Purdue University in 2010 and his B.S.in computer science from Purdue in 2004.
En liten tjänst av I'm With Friends. Finns även på engelska.