Visible to the public Biblio

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Presentation
Xinyu Zhou, University of Maryland at College Park, David Nicol, University of Illinois at Urbana-Champaign.  2017.  Trust-Aware Failure Detector in Multi-Agent Systems.

Poster presented at the 2017 Science of Security UIUC Lablet Summer Internship Poster Session held on July 27, 2017 in Urbana, IL.

Journal Article
Dong Jin, Illinois Institute of Technology, David Nicol, University of Illinois at Urbana-Champaign.  2015.  Parallel Simulation and Virtual-machine-based Emulation of Software-defined Network. ACM Transactions on Modeling and Computer Simulation. 26(1)

The emerging software-defined networking (SDN) technology decouples the control plane from the data plane in a computer network with open and standardized interfaces, and hence opens up the network designers’ options and ability to innovate. The wide adoption of SDN in industry has motivated the development of large-scale, high-fidelity testbeds for evaluation of systems that incorporate SDN. In this article, we develop a framework to support OpenFlow-based SDN simulation and distributed emulation, by leveraging our prior work on a hybrid network testbed with a parallel network simulator and a virtual-machine-based emulation system. We show how to exploit typical SDN controller behaviors to handle performance issues caused by the centralized controller in parallel discrete-event simulation. In particular, we develop an asynchronous synchronization algorithm for passive SDN controllers and design a two-level architecture for active SDN controllers. We evaluate the system performance, showing good scalability. Finally, we present a case study, using the testbed, to evaluate network verification applications in an SDN-based data center network. CCS Concepts: Networks→Network simulations; Computing methodologies→Simulation

Conference Paper
Hoang Hai Nguyen, University of Illinois at Urbana-Champaign, Kartik Palani, University of Illinois at Urbana-Champaign, David Nicol, University of Illinois at Urbana-Champaign.  2017.  An Approach to Incorporating Uncertainty in Network Security Analysis. Symposium and Bootcamp for the Science of Security (HotSoS 2017).

Attack graphs used in network security analysis are analyzed to determine sequences of exploits that lead to successful acquisition of privileges or data at critical assets. An attack graph edge corresponds to a vulnerability, tacitly assuming a connection exists and tacitly assuming the vulnerability is known to exist. In this paper we explore use of uncertain graphs to extend the paradigm to include lack of certainty in connection and/or existence of a vulnerability. We extend the standard notion of uncertain graph (where the existence of each edge is probabilistically independent) however, as signi cant correlations on edge existence probabilities exist in practice, owing to common underlying causes for dis-connectivity and/or presence of vulnerabilities. Our extension describes each edge probability as a Boolean expression of independent indicator random variables. This paper (i) shows that this formalism is maximally descriptive in the sense that it can describe any joint probability distribution function of edge existence, (ii) shows that when these Boolean expressions are monotone then we can easily perform uncertainty analysis of edge probabilities, and (iii) uses these results to model a partial attack graph of the Stuxnet worm and a small enterprise network and to answer important security-related questions in a probabilistic manner.

David Nicol, University of Illinois at Urbana-Champaign, Vikas Mallapura, University of Illinois at Urbana-Champaign.  2014.  Modeling and Analysis of Stepping Stone Attacks. 2014 Winter Simulation Conference.

Computer exploits often involve an attacker being able to compromise a sequence of hosts, creating a chain of "stepping stones" from his source to ultimate target. Stepping stones are usually necessary to access well-protected resources, and also serve to mask the attacker’s location. This paper describes means of constructing models of networks and the access control mechanisms they employ to approach the problem of finding which stepping stone paths are easiest for an attacker to find. While the simplest formulation of the problem can be addressed with deterministic shortest-path algorithms, we argue that consideration of what and how an attacker may (or may not) launch from a compromised host pushes one towards solutions based on Monte Carlo sampling. We describe the sampling algorithm and some preliminary results obtained using it.