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Past Talks

John Stewart EPRI

John Stewart
Sr. Technical Leader, Cyber Security, EPRI
Securing Grid Control Systems
Friday, January 12, 2018
Sudikoff L045 Trust Lab
12:00 Noon

M. Todd Henderson

M. Todd Henderson
Professor of Law, University of Chicago
Hacking Trust: How the Social Technology of Cooperation Will Revolutionize Government
Thursday, January 11, 2018
Room 003, Rockefeller Center
Sponsored by: Rockefeller Center

Dr. Liz Bowman

Dr. Elizabeth Bowman
U.S. Army Research Laboratory
Artificial Intelligence, Machine Learning and Information: Army Social Computing Research
Tuesday, December 5th
Haldeman 041 Kreindler Conference Room
4:00 PM

Dr. Fabio Pierazzi

Dr. Fabio Pierazzi
Royal Holloway University of London
Network Security Analytics for Detection of Advanced Cyberattacks
Tuesday, November 28th
Sudikoff Trust Lab (L045)
12:30 PM

V.S. Subrahmanian

V.S. Subrahmanian
Dartmouth Distinguished Professor in Cybersecurity, Technology, and Society
Bots, Socks, and Vandals
Tuesday, November 14th
Carson L01
5:00 PM 

Rand Beers

Rand Beers ('64)
Big Data, the Internet, and Social Media:  The Road to the November 2016 Election
Wednesday, November 8th
Haldeman 41 (Kreindler Conference Hall)
4:30 PM 

Fright Night Imge

Wanna See Something REALLY Scary?
ISTS Looks at the Dark Web on Halloween Night
Tuesday, October 31st
udikoff  045 Trust Lab (dungeon)
7:30 PM - RSVP
Space is Limited 

Sal Stolfo

Salvatore J. Stolfo 
Columbia University
A Brief History of Symbiote Defense
Tuesday, October 31st
Rockefeller 003
5:00 PM

Dan Wallach

STAR-Vote: A Secure, Transparent, Auditable and Reliable Voting System

Professor Dan Wallach
Rice University
Thursday April 27, 2017
Carson L01, 5:00 PM

Ben Miller Dragos

Pandora's Power Grid - What Can State Attacks Do and What Would be the Impact?

Ben Miller
Chief Threat Officer, Dragos, Inc.
Tuesday May 2, 2017
Kemeny 007, 4:30 PM
Brendan Nyhan




Factual Echo Chambers? Fact-checking and Fake News in Election 2016.

Professor Brendan Nyhan
Dartmouth College
Thursday May 4, 2017
Rocky 001, 5:00 PM

Dickie George


Espionage and Intelligence

Professor Dickie George
Johns Hopkins University
Thursday May 11, 2017
Rocky 001, 5:00 PM

Dan Wallach

A Nation Under Attack: Advanced Cyber-Attacks in Ukraine

Ukrainian Cybersecurity Researchers
Thursday April 6, 2017
Oopik Auditorium 5:30 PM

ISTS Information Pamphlet



Institute for Security, Technology, and Society
Dartmouth College
6211 Sudikoff Laboratory
Hanover, NH 03755 USA

Discovery of Trends in Activity-Aware Computing Environments

Project Summary

The use of mobile sensors is becoming increasingly commonplace in the everyday lives of people. Examples of sensors range from accelerometers, cameras and microphones on cell phones to special-purpose devices that capture physiological (e.g., EKG, GSR) or contextual information (e.g., temperature, location). These sensors can be used to automatically infer a range of human behavioral states (e.g., physical activities, emotional states, social interactions, and activities of daily living such as cooking or cleaning), the knowledge of which would be useful in a variety of applications, such as detecting anomalous and suspicious behavior, supporting emergency response efforts, tracking physical and cognitive health of individuals, and enhancing the user experience of social and communication technologies.

Much of the activity recognition research has so far focused on the analysis of one individual's sensor data in isolation. However, understanding the trends in activity patterns requires the analysis to move beyond individual to groups, which we believe will not only enable a broader range of applications but also reveal the privacy issues that are present in these scenarios. For example, can an individual be uniquely identified by his activities? Or are there enough similarities across people that can be exploited to anonymize a person's identity? In this project, we will focus on developing algorithms for discovering activity trends, deriving quantitative metrics for finding people who are behaviorally alike, and identifying possible strategies to address some of the privacy concerns that this research uncovers. Furthermore, we will explore the use of sensors on commercially available sensor-equipped mobile devices (such as the iPhone) and the possibility of tying some of our results into popular social applications (such as Facebook or ContextAwareIM).

Last Updated: 9/9/15