Related papers: Adaptive Security and Trust Management for Autonom…
Growing at a fast pace, modern autonomous systems will soon be deployed at scale, opening up the possibility for cooperative multi-agent systems. Sharing information and distributing workloads allow autonomous agents to better perform tasks…
Australia is a leader in autonomous systems technology, particularly in the mining industry, borne from necessity in a geographically dispersed and complex natural environment. Increasingly advanced autonomous systems are becoming more…
Autonomous systems increasingly rely on machine learning techniques to transform high-dimensional raw inputs into predictions that are then used for decision-making and control. However, it is often easy to maliciously manipulate such…
Android is the most widely deployed end-user focused operating system. With its growing set of use cases encompassing communication, navigation, media consumption, entertainment, finance, health, and access to sensors, actuators, cameras,…
Decentralized trust management is used as a referral benchmark for assisting decision making by human or intelligence machines in open collaborative systems. During any given period of time, each participant may only interact with a few of…
Autonomous navigation in maritime domains is accelerating alongside advances in artificial intelligence, sensing, and connectivity. Opaque decision-making and poorly calibrated human-automation interaction remain key barriers to safe…
Cloud computing has emerged as a crucial solution for handling data- and compute-intensive workflows, offering scalability to address dynamic demands. However, ensuring the secure execution of workflows in the untrusted multi-cloud…
In large-scale Internet of things networks, efficient medium access control (MAC) is critical due to the growing number of devices competing for limited communication resources. In this work, we consider a new challenge in which a set of…
The rapidly changing landscapes of modern optimization problems require algorithms that can be adapted in real-time. This paper introduces an Adaptive Metaheuristic Framework (AMF) designed for dynamic environments. It is capable of…
We propose a novel adaptive reinforcement learning control approach for fault tolerant control of degrading systems that is not preceded by a fault detection and diagnosis step. Therefore, \textit{a priori} knowledge of faults that may…
Software systems are increasingly making decisions on behalf of humans, raising concerns about the fairness of such decisions. Such concerns are usually attributed to flaws in algorithmic design or biased data, but we argue that they are…
Achieving long-term safety in uncertain/extreme environments while accounting for human preferences remains a fundamental challenge for autonomous systems. Existing methods often trade off long-term guarantees for fast real-time control and…
A human-swarm cooperative system, which mixes multiple robots and a human supervisor to form a heterogeneous team, is widely used for emergent scenarios such as criminal tracking in social security and victim assistance in a natural…
Checking software application suitability using automated software tools has become a vital element for most organisations irrespective of whether they produce in-house software or simply customise off-the-shelf software applications for…
Agentic AI systems -- Large Language Models (LLMs) augmented with planning, tool use, memory, and long-horizon interactions -- can execute complex tasks autonomously, but their multi-step trajectories introduce new failure modes that…
Computing systems form the backbone of many areas in our society, from manufacturing to traffic control, healthcare, and financial systems. When software plays a vital role in the design, construction, and operation, these systems are…
As organisations expand and interconnect, authorisation infrastructures become increasingly difficult to manage. Several solutions have been proposed, including self-adaptive authorisation, where the access control policies are dynamically…
Cooperative information shared among a multi-agent system (MAS) can be useful to agents to efficiently fulfill their missions. Relying on wrong information, however, can have severe consequences. While classical approaches only consider…
6G will fulfill the requirements of future digital healthcare systems through emerging decentralized computing and secure communications technologies. Digital healthcare solutions employ numerous low-power and resource-constrained connected…
Safe reinforcement learning has traditionally relied on predefined constraint functions to ensure safety in complex real-world tasks, such as autonomous driving. However, defining these functions accurately for varied tasks is a persistent…