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Past Talks

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
S
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


2012BrochureCover

 

Institute for Security, Technology, and Society
Dartmouth College
6211 Sudikoff Laboratory
Hanover, NH 03755 USA
info.ists@dartmouth.edu

Early Worm Detection

A Subproject for Process Query Systems (PQS)

An attacker often selects a target machine only after broad scans to identify all vulnerable machines within a certain range of IP addresses. Unfortunately, current network routers often obscure scanning activity, since the routers will drop any scanning traffic directed toward a machine that does not actually exist. With this "loss" of scanning traffic, it is much harder for a security analyst to identify the scan in the first place or understand its scope. At the same time, however, routers do generate error messages (Internet Control Message Protocol (ICMP) Unreachable) when traffic is directed at nonexistent machines. By collecting these error messages, IRIA can provide security analysts with a much better view of scanning activity, allowing them to detect impending attacks that they might otherwise miss.

  • Simulating Realistic Network Worm Traffic for Worm Warning System Design and Testing [PDF Format]
  • Designing a Framework for Active Worm Detection on Global Networks [PDF Format]
  • Using Sensor Networks and Data Fusion for Early Detection of Active Worms [PDF Format]
  • Early Detection of Internet Worms [HTML]
  • Early Detection of Internet Worm Activity by Metering ICMP Destination Unreachable Activity [PDF Format]

  • Principal Investigator: George Bakos, Vincent Berk, Robert Gray