Towards a Framework for Automatic Firewalls Configuration via Argumentation Reasoning

Firewalls have been widely used to protect not only small and local networks but also large enterprise networks. The configuration of firewalls is mainly done by network administrators, thus, it suffers from human errors. This paper aims to solve the network administrators' problem by introducing a formal approach that helps to configure centralized and distributed firewalls and automatically generate conflict-free firewall rules. We propose a novel framework, called ArgoFiCo, which is based on argumentation reasoning. Our framework automatically populates the firewalls of a network, given the network topology and the high-level requirements that represent how the network should behave. ArgoFiCo provides two strategies for firewall rules distribution

Policy support for autonomous swarms of drones

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

Argumentation-based policy analysis for drone systems

The use of drone systems is increasing especially in dangerous environments where manned operations are too risky. Different entities are involved in drone systems’ missions and they come along with their vast varieties of specifications. The behaviour of the system is described by its set of policies that should satisfy the requirements and specifications of the different entities and the system itself. Deciding the policies that describe the actions to be taken is not trivial, as the different requirements and specifications can lead to conflicting actions. We introduce an argumentation-based policy analysis that captures conflicts for which properties have been specified. Our solution allows different rules to take priority in different contexts. We propose a decision making process that solves the detected conflicts by using a dynamic conflict resolution based on the priorities between rules. We apply our solution to two case studies where drone systems are used for military and disaster rescue operations