Research advances in automated red teaming

Authors:
James Decraene;Fanchao Zeng;Malcolm Yoke Hean Low;Suiping Zhou;Wentong Cai
Affiliations:
Nanyang Technological University, Singapore;Nanyang Technological University, Singapore;Nanyang Technological University, Singapore;Nanyang Technological University, Singapore;Nanyang Technological University, Singapore
Venue:
SpringSim '10 Proceedings of the 2010 Spring Simulation Multiconference
Year:
2010

Citing 18
Cited 2

A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimisation: NSGA-II

PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
Artificial War: Multiagent-Based Simulation of Combat

Artificial War: Multiagent-Based Simulation of Combat
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results

Evolutionary Computation
Optimal computing budget allocation for multi-objective simulation models

WSC '04 Proceedings of the 36th conference on Winter simulation
Investigating the dynamics of competition: coevolving red and blue simulation parameters

WSC '05 Proceedings of the 37th conference on Winter simulation
Fundamentals of Computational Swarm Intelligence

Fundamentals of Computational Swarm Intelligence
Evolutionary Computation: Toward a New Philosophy of Machine Intelligence (IEEE Press Series on Computational Intelligence)

Evolutionary Computation: Toward a New Philosophy of Machine Intelligence (IEEE Press Series on Computational Intelligence)
A case study of the development and use of a mana-based federation for studying U.S. border operations

Proceedings of the 38th conference on Winter simulation
Automated red teaming: a proposed framework for military application

Proceedings of the 9th annual conference on Genetic and evolutionary computation
Using the MANA agent-based simulation tool to evaluate and compare the effectiveness of ground-based and airborne communications jammers in countering the IED threat to ground convoys

SpringSim '07 Proceedings of the 2007 spring simulation multiconference - Volume 2
A Study on the Performance of Substitute Distance Based Approaches for Evolutionary Many Objective Optimization

SEAL '08 Proceedings of the 7th International Conference on Simulated Evolution and Learning
Automated red teaming: an objective-based data farming approach for red teaming

Proceedings of the 40th Conference on Winter Simulation
Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility

Future Generation Computer Systems
Constraint handling in multiobjective evolutionary optimization

IEEE Transactions on Evolutionary Computation
Application of multi-objective bee colony optimization algorithm to automated red teaming

Winter Simulation Conference
Fuzzy-Pareto-Dominance and its application in evolutionary multi-objective optimization

EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Characterizing warfare in red teaming

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Multiobjective optimization and multiple constraint handling with evolutionary algorithms. I. A unified formulation

IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans

Evolutionary design of experiments using the MapReduce framework

Proceedings of the 2011 Summer Computer Simulation Conference
Effective crowd control through adaptive evolution of agent-based simulation models

Proceedings of the Winter Simulation Conference

Quantified Score

Hi-index	0.01

Visualization

Abstract

We present, combine and apply novel research advances to Automated Red Teaming (ART). ART is an automated vulnerability assessment tool which is employed to uncover the hard-to-predict and potentially critical elements of military operations. ART is principally based on the use of agent-based modelling/simulation, data farming and evolutionary computation. In this paper, we present two distinct computational methods to address multiple issues of ART: constraint handling and computing budget. These novel techniques originate from the research fields of evolutionary computation and cloud computing. These techniques are applied to a military toy model which was developed with the agent-based simulation platform MANA. We then discuss another potential bottleneck of ART: many-objective optimization. The aim of this research is to optimize ART to best assist defense experts in operational analysis and, ultimately, in critical decision making.