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Modern artificial intelligence relies on networks of agents that collect data, process information, and exchange it with neighbors to collaboratively solve optimization and learning problems. This article introduces a novel distributed…
The specification and enforcement of network-wide policies in a single administrative domain is common in today's networks and considered as already resolved. However, this is not the case for multi-administrative domains, e.g. among…
The Internet of Things (IoT) necessitates robust access control mechanisms to secure a vast array of interconnected devices. Most of the existing IoT systems in practice use centralized solutions. We identify the problems in such solutions…
Nowadays many companies have available large amounts of raw, unstructured data. Among Big Data enabling technologies, a central place is held by the MapReduce framework and, in particular, by its open source implementation, Apache Hadoop.…
Large language models (LLMs) are increasingly deployed over knowledge bases for efficient knowledge retrieval and question answering. However, LLMs can inadvertently answer beyond a user's permission scope, leaking sensitive content, thus…
Today, with the continued growth in using information and communication technologies (ICT) for business purposes, business organizations become increasingly dependent on their information systems. Thus, they need to protect them from the…
Controlling resource usage in distributed systems is a challenging task given the dynamics involved in access granting. Consider, for instance, the setting of floating licenses where access can be granted if the request originates in a…
With the increasing penetration of renewable energy resources, power systems face new challenges in balancing power supply and demand and maintaining the nominal frequency. This paper studies load control to handle these challenges. In…
Today's control systems are often characterized by modularity and safety requirements to handle complexity, resulting in hierarchical control structures. Although hierarchical model predictive control offers favorable properties, achieving…
We consider access control for IoT systems that involves shared accesses to the IoT devices as well as their data. Since IoT devices are dispersed all over the edge of the Internet, traditional centralized access control has problems.…
An authorisation has been recognised as an important security measure for preventing unauthorised access to critical resources, such as devices and data, within the Internet of Things (IoT) networks. Existing authorisation methods for the…
Relationship-based access control (ReBAC) provides a high level of expressiveness and flexibility that promotes security and information sharing, by allowing policies to be expressed in terms of chains of relationships between entities.…
Blockchain technology enables stakeholders to conduct trusted data sharing and exchange without a trusted centralized institution. These features make blockchain applications attractive to enhance trustworthiness in very different contexts.…
This paper discusses distributed approaches for the solution of random convex programs (RCP). RCPs are convex optimization problems with a (usually large) number N of randomly extracted constraints; they arise in several applicative areas,…
The paper investigates stochastic resource allocation problems with scarce, reusable resources and non-preemtive, time-dependent, interconnected tasks. This approach is a natural generalization of several standard resource management…
Security requirements in distributed software systems are inherently dynamic. In the case of authorization policies, resources are meant to be accessed only by authorized parties, but the authorization to access a resource may be…
Administrative Role Based Access Control (ARBAC) models deal with how to manage user-role assignments (URA), permission-role assignments (PRA), and role-role assignments (RRA). A wide variety of approaches has been proposed in the…
It is known that reinforcement learning (RL) is data-hungry. To improve sample-efficiency of RL, it has been proposed that the learning algorithm utilize data from 'approximately similar' processes. However, since the process models are…
Large Language Model (LLM)-based agent systems are increasingly deployed for complex real-world tasks but remain vulnerable to natural language-based attacks that exploit over-privileged tool use. This paper aims to understand and mitigate…
The paper provides a framework for the assessment and optimization of the total risk of complex distributed systems. The framework takes into account the risk of each agent, which may arise from heterogeneous sources, as well as the risk…