Data Driven Security Models and Analysis - July 2014

Public Audience
Purpose: To highlight project progress. Information is generally at a higher level which is accessible to the interested public. All information contained in the report (regions 1-3) is a Government Deliverable/CDRL.

PI(s): Ravi Iyer
Co-PI(s): Zbigniew Kalbarczyk
Researchers:

HARD PROBLEM(S) ADDRESSED
This refers to Hard Problems, released November 2012.

This research shares with three hard problems:
* Predictive security metrics - design, development, and validation
* Resilient architectures - in the end we want to use the metrics to achieve a measurable enhancement in system resiliency, i.e., the ability to withstand attacks
* Human behavior - data contain traces of the steps the attacker took, and hence inherently include some aspects of the human behavior (of both users and miscreants)

PUBLICATIONS

Report papers written as a result of this research. Include title, authors, venue published/presented, and a short description or abstract. Also, please identify which hard problem(s) the publication addressed.

[1] Paper submission: "An Experiment Using Factor Graph for Early Attack Detection," P. Cao, K.-W. Chung, A. Slagell, Z. Kalbarczyk, R. Iyer, submitted to Workshop on Learning from Authoritative Security Experiment Results (LASER) 2014.
[2] Present two posters at Symposium and Bootcamp on the Science of Security (HotSoS), (formerly SoS Community Meeting), April 8-9, 2014, Raleigh, NC, USA.
* "Preemptive Intrusion Detection," P. Cao, K. Chung, A. Slagell, Z Kalbarczyk, R Iyer
* "Personalized Password Guessing," P. Cao, H. Li, A. Slagell, K. Nahrstedt, Z Kalbarczyk, R. Iyer

ACCOMPLISHMENT HIGHLIGHTS

In this quarter we focused on a novel application of Factor Graphs to represent real-world security incidents and develop a scientifically sound methods for preemptive detection of attacks, i.e., before the system misuse.