Argumentation-based policy analysis for drone systems

Karafili, Erisa; Lupu, Emil; Arunkumar, Saritha; Bertino, Elisa

doi:10.1109/uic-atc.2017.8397414

Cited by 6 publications

(8 citation statements)

References 12 publications

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“…An important challenge that arrises during the coordination and planning phases of drone systems, especially in collaborative scenarios, is the decision process of applicable actions for particular cases. A policy analysis for drone systems is developed in [19] that is able to capture and solve conflicting rules, and improve the efficiency of the used set of rules, based on argumentation and abductive reasoning [16], in particular it uses preference-based argumentation [6,24,5]. The work in [19] does not deal with the notion of swarm of drones and their operation.…”

Section: Related Workmentioning

confidence: 99%

“…A policy analysis for drone systems is developed in [19] that is able to capture and solve conflicting rules, and improve the efficiency of the used set of rules, based on argumentation and abductive reasoning [16], in particular it uses preference-based argumentation [6,24,5]. The work in [19] does not deal with the notion of swarm of drones and their operation. This analysis is an extension of the one proposed in [18,21], that is used for enabling data sharing in different contexts by enforcing the correct data sharing agreements, and during forensics investigations for attributing cyber attacks to attackers [17].…”

Section: Related Workmentioning

confidence: 99%

“…This example highlights the possible conflicts between policies such as rules (8) and (10) with (7), in Section 4, and clearly in any policy system a strategy for dealing with conflicts is required. A proposed solution would be to use the argumentation and abductive reasoning procedure introduced in [18,21], and more specifically for drones [19], where the rules are left as they are, and priorities between them are introduced. The priority relation between rules is denoted by ≺, where r 1 ≺ r 2 means that rule r 2 takes priority over rule r 1 .…”

Section: Communications Between Dronesmentioning

confidence: 99%

“…The rules for sharing information and data can be different for both of them, e.g., more restrictive from the military drones side. For future work in managing the different behavioural rules between the two types of drones we suggest to use the policy analysis introduced in [19]. In the case there is a need of performing data alteration, or restriction of data quality when information is shared between drones that have different owners and different relations between each other, we propose to use the data alteration mechanism introduced in [20].…”

Section: Policy Sharingmentioning

confidence: 99%

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Policy Support for Autonomous Swarms of Drones

Cullen

Karafili

Pilgrim

et al. 2018

Lecture Notes in Computer Science

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In recent years drones have become more widely used in military and non-military applications. Automation of these drones will become more important as their use increases. Individual drones acting autonomously will be able to achieve some tasks, but swarms of autonomous drones working together will be able to achieve much more complex tasks and be able to better adapt to changing environments. In this paper we describe an example scenario involving a swarm of drones from a military coalition and civil/humanitarian organisations that are working collaboratively to monitor areas at risk of flooding. We provide a definition of a swarm and how they can operate by exchanging messages. We define a flexible set of policies that are applicable to our scenario that can be easily extended to other scenarios or policy paradigms. These policies ensure that the swarms of drones behave as expected (e.g., for safety and security). Finally we discuss the challenges and limitations around policies for autonomous swarms and how new research, such as generative policies, can aid in solving these limitations.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Communications Between Dronesmentioning

confidence: 99%

Section: Policy Sharingmentioning

confidence: 99%

See 2 more Smart Citations

Policy Support for Autonomous Swarms of Drones

Cullen

Karafili

Pilgrim

et al. 2018

Lecture Notes in Computer Science

Self Cite

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“…Argumentation-based reasoning [28] together with abductive reasoning can be used for policy analysis with incomplete, conflicting and context-dependent knowledge. The policy analysis introduced in [29]- [31] uses argumentation and abductive reasoning. This analysis through the use of abductive reasoning can identify conflicting policies, as well as redundant and missing ones.…”

Section: Abductive Reasoningmentioning

confidence: 99%

Verification techniques for policy based systems

Karafili

Pipes

Lupu

2017

2017 IEEE SmartWorld, Ubiquitous Intelligence &Amp; Computing, Advanced &Amp; Trusted Computed, Scalable Computing &Amp; Commun

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Verification techniques are applied to policy based systems to ensure design correctness and to aid in the discovery of errors at an early stage of the development life cycle. A primary goal of policy verification is to evaluate the policy's validity. Other analyses on policy based systems include the identification of conflicting policies and policy efficiency evaluation and improvement. In this work, we present a discussion and classification of recent research on verification techniques for policy based systems. We analyse several techniques and identify popular supporting verification tools. An evaluation of the benefits and drawbacks of the existing policy analyses is made. Some of the common identified problems were the significant need of computational power, the limitation of the techniques to particular policy model, which restrict their extension to other policy models and the lack of efficient conflicts resolution methods. We use the evaluation results for discussing the further challenges and future research directions that will be faced by policy verification techniques. In particular, we discuss specific requirements concerning verification techniques for coalition policies systems and autonomous decision making.

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