An architecture for adversarial planning

Applegate, Celia; Elsaesser, Christopher; Sanborn, Jim

doi:10.1109/21.47820

Cited by 31 publications

(18 citation statements)

References 14 publications

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“…Prominent among approaches with specific emphasis on adversarial actions is Adversarial Planner (AP)-a state-based, application-independent, hierarchical-task-network planner [23]. Its adversarial reasoning process models the Army's action-reactioncounteraction COA planning protocol.…”

Section: Possible Approaches Criteria and Tradeoffsmentioning

confidence: 99%

Building a Tool for Battle Planning: Challenges, Tradeoffs, and Experimental Findings

Kott

Budd²,

Ground³

et al. 2005

Appl Intell

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Use of knowledge-based decision aids can help alleviate the challenges of planning complex operations. We describe a knowledge-based tool capable of translating a high-level concept for a tactical military operation into a fully detailed, actionable plan, producing automatically (or with human guidance) plans with realistic degree of detail and complexity. Tight interleaving of planning, adversary estimates, scheduling, routing, attrition and consumption processes comprise the computational approach of this tool. Although originally developed for Army large-unit operations, the technology is generic and also applies to a number of other domains, particularly in critical situations requiring detailed planning within a constrained period of time. In this paper, we focus particularly on the engineering tradeoffs in the design of the tool. An experimental comparative evaluation indicated that the tool's performance compared favorably with human planners.

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Section: Possible Approaches Criteria and Tradeoffsmentioning

confidence: 99%

Building a Tool for Battle Planning: Challenges, Tradeoffs, and Experimental Findings

Kott

Budd²,

Ground³

et al. 2005

Appl Intell

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“…In 1981, Jaime G. Carbonell, a famous professor in CarnegieMellon University, developed an approach to reasoning about adversarial behaviour called "counterplanning" that maintains a strategic view of plan conflicts [6]. In 1990, Carol Applegate provided an architecture for adversarial planning [7].…”

Section: Introductionmentioning

confidence: 99%

A Model of Counterplanning with Variable Object Set

Liu¹,

Ouyang²,

Gu³

et al. 2017

dtetr

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ABSTRACT In recent years, the research for the counterplanning and the planning with variable object set has been regarded as difficult problem. In this paper, we effectively combine them under the graphplan framework, and provide a model of counterplanning with variable object set. It can create beneficial objects and delete useless objects, so as to achieve the goals of our agents and block or stop adversarial agents' goals. The model can be widely used in intrusion detection system, network security, military area, commercial battlefield, and other fields.

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“…Some good work has developed honeypot computers and "honeynets", computer systems and networks whose purpose is to entrap attackers to obtain information about their attack methods [18]; these are a simple passive form of deception. [1] suggests a general approach to planning defenses automatically in adversarial situations, including classic military tactics like deception; [8] suggests ways to encourage maladaptive behavior in enemy organizations. [10] and [19] provide ideas for modeling attacks on computer systems, the former suggesting some interesting ideas about deception in defense.…”

Section: Introductionmentioning

confidence: 99%

A model of deception during cyber-attacks on information systems

Rowe

IEEE First Symposium onMulti-Agent Security and Survivability, 2004

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Deception is a classic INTRODUCTIONDeception is an important two-agent psychological phenomenon with many applications to information security. Deception can occur offensively, as when attackers try to fool our information systems into giving away secrets or destroying themselves, or it can occur defensively, as when a computer pretends by exaggerated processing delays to succumb to a denial-of-service attack so the attacker goes away. Little systematic analysis has been paid to the concept of deception in information systems, however. Most writers assume methods of deception are intuitively obvious or comprise only a few categories. But there are many possible kinds of deception, some quite subtle. And deceptions can be automated. So it is important in defense of our information systems that we develop a better theory of deception and ways to translate it into security practices.

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An architecture for adversarial planning

Cited by 31 publications

References 14 publications

Building a Tool for Battle Planning: Challenges, Tradeoffs, and Experimental Findings

Building a Tool for Battle Planning: Challenges, Tradeoffs, and Experimental Findings

A Model of Counterplanning with Variable Object Set

A model of deception during cyber-attacks on information systems

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