41 citations · 82 across the 22 of their papers we have counts for
24 papers
Zero-Trust Network Access (ZTNA)
Vasilios Mavroudis
Zero-Trust Network Access (ZTNA) marks a significant shift in network security by adopting a "never trust, always verify" approach. This work provides an in-depth analysis of ZTNA,…
CybORG++: An Enhanced Gym for the Development of Autonomous Cyber Agents
Harry Emerson, Liz Bates, Chris Hicks +1
CybORG++ is an advanced toolkit for reinforcement learning research focused on network defence. Building on the CAGE 2 CybORG environment, it introduces key improvements, including…
Entity-based Reinforcement Learning for Autonomous Cyber Defence
Isaac Symes Thompson, Alberto Caron, Chris Hicks +1
A significant challenge for autonomous cyber defence is ensuring a defensive agent's ability to generalise across diverse network topologies and configurations. This capability is…
Autonomous Network Defence using Reinforcement Learning
Myles Foley, Chris Hicks, Kate Highnam +1
In the network security arms race, the defender is significantly disadvantaged as they need to successfully detect and counter every malicious attack. In contrast, the attacker nee…
Environment Complexity and Nash Equilibria in a Sequential Social Dilemma
Mustafa Yasir, Andrew Howes, Vasilios Mavroudis +1
Multi-agent reinforcement learning (MARL) methods, while effective in zero-sum or positive-sum games, often yield suboptimal outcomes in general-sum games where cooperation is esse…
Mitigating Deep Reinforcement Learning Backdoors in the Neural Activation Space
Sanyam Vyas, Chris Hicks, Vasilios Mavroudis
This paper investigates the threat of backdoors in Deep Reinforcement Learning (DRL) agent policies and proposes a novel method for their detection at runtime. Our study focuses on…
A View on Out-of-Distribution Identification from a Statistical Testing Theory Perspective
Alberto Caron, Chris Hicks, Vasilios Mavroudis
We study the problem of efficiently detecting Out-of-Distribution (OOD) samples at test time in supervised and unsupervised learning contexts. While ML models are typically trained…
Online Convex Optimisation: The Optimal Switching Regret for all Segmentations Simultaneously
Stephen Pasteris, Chris Hicks, Vasilios Mavroudis +1
We consider the classic problem of online convex optimisation. Whereas the notion of static regret is relevant for stationary problems, the notion of switching regret is more appro…
Extraction Propagation
Stephen Pasteris, Chris Hicks, Vasilios Mavroudis
Running backpropagation end to end on large neural networks is fraught with difficulties like vanishing gradients and degradation. In this paper we present an alternative architect…
A Hierarchical Nearest Neighbour Approach to Contextual Bandits
Stephen Pasteris, Chris Hicks, Vasilios Mavroudis
In this paper we consider the adversarial contextual bandit problem in metric spaces. The paper "Nearest neighbour with bandit feedback" tackled this problem but when there are man…
Canaries and Whistles: Resilient Drone Communication Networks with (or without) Deep Reinforcement Learning
Chris Hicks, Vasilios Mavroudis, Myles Foley +3
Communication networks able to withstand hostile environments are critically important for disaster relief operations. In this paper, we consider a challenging scenario where drone…
Reward Shaping for Happier Autonomous Cyber Security Agents
Elizabeth Bates, Vasilios Mavroudis, Chris Hicks
As machine learning models become more capable, they have exhibited increased potential in solving complex tasks. One of the most promising directions uses deep reinforcement learn…
Inroads into Autonomous Network Defence using Explained Reinforcement Learning
Myles Foley, Mia Wang, Zoe M +2
Computer network defence is a complicated task that has necessitated a high degree of human involvement. However, with recent advancements in machine learning, fully autonomous net…
Nearest Neighbour with Bandit Feedback
Stephen Pasteris, Chris Hicks, Vasilios Mavroudis
In this paper we adapt the nearest neighbour rule to the contextual bandit problem. Our algorithm handles the fully adversarial setting in which no assumptions at all are made abou…
An Interface between Legacy and Modern Mobile Devices for Digital Identity
Vasilios Mavroudis, Chris Hicks, Jon Crowcroft
In developing regions a substantial number of users rely on legacy and ultra-low-cost mobile devices. Unfortunately, many of these devices are not equipped to run the standard auth…
Adaptive Webpage Fingerprinting from TLS Traces
Vasilios Mavroudis, Jamie Hayes
In webpage fingerprinting, an on-path adversary infers the specific webpage loaded by a victim user by analysing the patterns in the encrypted TLS traffic exchanged between the use…
Snappy: Fast On-chain Payments with Practical Collaterals
Vasilios Mavroudis, Karl Wüst, Aritra Dhar +2
Permissionless blockchains offer many advantages but also have significant limitations including high latency. This prevents their use in important scenarios such as retail payment…
Bounded Temporal Fairness for FIFO Financial Markets
Vasilios Mavroudis
Financial exchange operators cater to the needs of their users while simultaneously ensuring compliance with the financial regulations. In this work, we focus on the operators' com…
Libra: Fair Order-Matching for Electronic Financial Exchanges
Vasilios Mavroudis, Hayden Melton
While historically, economists have been primarily occupied with analyzing the behaviour of the markets, electronic trading gave rise to a new class of unprecedented problems assoc…
Market Manipulation as a Security Problem
Vasilios Mavroudis
Order matching systems form the backbone of modern equity exchanges, used by millions of investors daily. Thus, their operation is strictly controlled through numerous regulatory d…
Towards Low-level Cryptographic Primitives for JavaCards
Vasilios Mavroudis, Petr Svenda
JavaCard is a multi-application security platform deployed to over twenty billion smartcards, used in applications ranging from secure payments to telecommunications. While the pla…
Eavesdropping Whilst You're Shopping: Balancing Personalisation and Privacy in Connected Retail Spaces
Vasilios Mavroudis, Michael Veale
Physical retailers, who once led the way in tracking with loyalty cards and `reverse appends', now lag behind online competitors. Yet we might be seeing these tables turn, as many…
VAMS: Verifiable Auditing of Access to Confidential Data
Alexander Hicks, Vasilios Mavroudis, Mustafa Al-Bassam +2
We propose VAMS, a system that enables transparency for audits of access to data requests without compromising the privacy of parties in the system. VAMS supports audits on an aggr…
A Touch of Evil: High-Assurance Cryptographic Hardware from Untrusted Components
Vasilios Mavroudis, Andrea Cerulli, Petr Svenda +3
The semiconductor industry is fully globalized and integrated circuits (ICs) are commonly defined, designed and fabricated in different premises across the world. This reduces prod…