BT Group (United Kingdom)

Fibre-optic sensing technology is transforming seafloor monitoring by enabling dense, continuous measurements across vast distances using existing telecommunication infrastructure. Distributed acoustic sensing (DAS) and optical interferometry [1] have demonstrated remarkable potential for earthquake detection, ocean dynamics monitoring, and hazard early warning. However, for these technologies to be used for these applications, the transfer function between environmental perturbations and measured optical signal changes in submarine cables needs to be known.We present the, to the best of our knowledge, first controlled-environment characterisation of submarine cable responses to active seismic and acoustic sources, comparing DAS and optical interferometry measurements with ground-truth data from 58 geophones, 20 three-component seismometers, and microphones [2]. Our results reveal three key findings:In contrast with proposed theoretical models [3], our interferometric measurements show first-order sensitivity to broadside seismic sources, enabling localisation of arrivals along straight fibre links.We identify a previously unreported fast-wave phenomenon, attributed to seismic energy coupling into the cable's metal armour and propagating at velocities exceeding 3.5 km/s, significantly altering recorded waveforms.We compared measurements between adjacent fibres within the same cable. Results show significant discrepancies between the measured waveforms, which should be considered in applications operating in a similar frequency range as our tests.These findings show the complexity of submarine cable mechanics and their impact on optical sensing performance. Understanding these processes is critical for calibrating transfer functions and improving the reliability of fibre-based geophysical observations. In addition to these findings, we also discuss the limitations of our methodology, which primarily arise from the limited range of seismic source frequencies available. Our work presents a first step towards understanding the complex transfer function of environmental perturbations to optical signals in subsea cables, advancing the vision of large-scale, cost-effective Earth observation systems.[1] Marra, G. et al. Optical interferometry–based array of seafloor environmental sensors using a transoceanic submarine cable. Science 376 (6595), 874–879 (2022)[2] Fairweather, D.M., Tamussino, M., Masoudi, A. et al. Characterisation of the optical response to seismic waves of submarine telecommunications cables with distributed and integrated fibre-optic sensing. Sci Rep 14, 31843 (2024)[3] Fichtner, A., Bogris, A., Nikas, T. et al. Theory of phase transmission fibre-optic deformation sensing. Geophysical Journal International, 231(2), 1031–1039, (2022)

Voice over Internet Protocol (VoIP) has transitioned from a novel technology to a cornerstone of organizational communication. However, the accelerated pace of VoIP adoption has amplified exposure to sophisticated security vulnerabilities. These vulnerabilities pose risks to confidentiality, availability, and integrity, and adversaries are increasingly targeting weaknesses in signaling protocols, media handling, device configurations, and network architectures. A unified, robust, and context-aware security model for VoIP is of great importance. This qualitative research paper delves into the existing vulnerabilities that continue to plague current VoIP infrastructures. Drawing from technical documentation, operational records, and security event analysis, the study provides an in-depth examination of vulnerabilities across different components of VoIP systems. The research also investigates recurrent patterns in VoIP security vulnerabilities, such as protocol weaknesses, misconfigurations, architectural inconsistencies, and inadequate policy enforcement. Moreover, it analyzes systemic factors that contribute to the persistence of these vulnerabilities across different organizations. Based on the insights gained, the study outlines a unified framework for security enhancements that focuses on strengthening architectural controls, harmonizing policy measures, and incorporating adaptive defense mechanisms. The results highlight that VoIP resilience cannot be solely achieved through isolated countermeasures but rather through a holistic, multilayered approach that collectively addresses technical, operational, and organizational gaps. This framework offers valuable contributions to the existing discourse by providing a unified pathway toward robust VoIP security, improved governance, and enhanced infrastructural resilience.

Abstract Process task duration data often exhibit multiple peaks, indicating differences in, for example, customer ages and preferences, resource capabilities or the day/hour of a week. This heterogeneous data, which captures diverse customer patterns, should be represented using different models, resulting in an overall mixture model. This paper introduces gamma mixture models to represent various customer patterns in task duration data, with a focus on automating the fitting process. The approach involves a two-stage procedure: first, divide-and-conquer using peak-, equidistance- and cluster-based techniques to partition data, and automatically fit gamma distributions to each subset. The second stage then improves the fitted mixture model by directly searching the log-likelihood surface. The method is compared with the expectation–maximization (EM) algorithm and an open tool (HyperStar), using both artificially generated datasets and a publicly available hospital billing dataset, demonstrating its effectiveness and time efficiency in modelling heterogeneous process duration data. Furthermore, a case study on process conformance checking is conducted using the hospital billing dataset, highlighting a potential application area for the method in process mining.

It is easy to point out why a method should not be a black box, but it is hard to define what would make it sufficiently transparent.

The use of holographic reconfigurable surfaces (RHSs) for energy efficiency (EE) maximization in MIMO links is studied. Two RHSs are considered, one at the transmitter and one at the receiver, and their reflection coefficients are optimized together with the beamforming structure. The optimization of the two RHSs is carried out in closed-form, assuming a single data stream is transmitted. The performance of the proposed optimization is analyzed numerically, revealing that the use of RHSs can provide significantly higher EE compared to massive antenna arrays, while still providing satisfactory performance in terms of achievable rate.

Every day, on average, eight cybercrimes targeting IoT networks occur, leading to a cumulative loss of ${\$}$ 10 million The main reason for these attacks is the ability of unauthorized devices to gain access to IoT networks by replicating the hardware and software configurations of authorized devices. To tackle this pressing issue, cryptographic keys are used to authenticate devices in IoT networks. Given the requirements of this process, authentication is performed once at the beginning. However, this makes devices susceptible to cyber-attacks like spoofing, Sybil attacks, distributed denial-of-service (DDoS), and Advanced Persistent Threats (APT). To address this, we propose a novel Continuous Device-to-Device Authentication (CD<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>A) framework based on two components: 1) Identity Establishment and 2) Continuous Authentication. In the Identity Establishment phase, we use manufacturing imperfections to model unique device behaviours. A novel device fingerprint algorithm is proposed that leverages impurities of built-in components of the device, like crystal oscillators, and is measured in a graphical processing unit (GPU) by isolating each core at a time in the central processing unit (CPU). In the Continuous Authentication phase, we implement a dynamic timeline to establish device identity at regular intervals. Each device is continuously authenticated by using machine learning techniques. To protect devices from cyber-attacks like spoofing, Sybil attacks, DDoS, and APT, we track device legitimacy by calculating the Device Authentication Score (DAS) and the Device Risk Factor (DRF) in view of varying security risks. We evaluate the CD<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>A framework on an IoT system with 11 devices. The CD<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>A framework achieves an average authentication accuracy of 99.96% and9 99.85% when used in tandem with CatBoost and XGBoost machine learning algorithms, respectively.

Abstract Phishing, a persistent cyber-attack, continues to cause data breaches affecting both individuals and corporations. Web-based phishing, often spread through social media posts and emails, remains a significant threat due to the risks posed by phishing URLs. Traditional detection methods, primarily relying on supervised learning, require extensive datasets and computational power, compromising user privacy. These methods also struggle to keep pace with evolving threats, especially those generated using advanced AI techniques. Unsupervised clustering methods have been explored, but challenges related to scalability and detection accuracy persist. In this extended work, we present a more robust phishing detection framework that utilizes large language models (LLMs) to create a refined embedding space, significantly enhancing cluster cohesion and silhouette scores. A key contribution of this work is the push towards Explainable AI (XAI), which provides in-depth visualizations of phishing clusters, including scatter plots and keyword-based cluster explanations. These visualizations enable a clearer understanding of the clustering process, revealing insights into campaign patterns, such as those targeting specific sectors (e.g., finance). In relation to that, we also introduce enhanced campaign detection visualizations, offering a more detailed characterization of phishing campaigns, including their evolution and sector-specific targeting. Our system remains fast, scalable, and privacy-preserving, providing a comprehensive solution for real-time phishing campaign detection while enhancing interpretability through XAI.

Our demonstration highlights the use of semantic communication to transmit stereo frame streams and its application in immersive media. Considering the limitations of traditional stereo compression with digital transmission under poor channel conditions, such as the cliff effect and high latency in computation and transmission, we employ the Deep Joint Source and Channel Coding (Deep JSCC) framework to transmit semantic information of stereo streams between the sender and receiver. To address channel instability, we propose a dynamic rate adjustment method that adapts to channel conditions while maintaining transmission efficiency and reconstruction quality. Furthermore, we extend this work to stereo stream applications, enabling the real-time synthesis of multiple novel view streams of the streamer. The overall design of this demo enables an immersive multi-view experience by transmitting rate-controlled semantic features from only two perspectives.

We investigate, for the first time, the important research question of which quantum key distribution (QKD) protocol, prepare and measure (P&M) or entanglement based (EB), is more cost-effective in optically switched metropolitan quantum networks without quantum repeaters. To do so, we i) formulated novel integer linear programming (ILP) models aimed to minimise the cost to deploy PM and EB QKD networks whilst achieving a target quantum key exchange rate and ii) applied the ILP models to determine the minimum cost configuration of both types of QKD networks in two cases of study. Our findings suggest that, depending on the cost and technical specifications of network components as well as the target key rate performance, there are clear regimes for which one protocol offers improved costs with respect to the other. For example, in the cases studied we found that PM-QKD is preferred as long as the single-photon sources used in PM-QKD are half the cost of the entangled photon sources used in EB-QKD. In contrast, EB-QKD is more cost-effective when the cost of the sources is similar, but the cost of the detectors is low and EB-QKD can exploit multiple channels to exchange keys.