18 research outputs found
The Kingdom at a Crossroads:Saudi Arabia’s nuclear prospects in an era of strategic competition
Get PDFSaudi Arabia faces an existential threat from a potentially proliferating Iran and an unpredictable ally in the Trump administration. Zoha Naser and Sarah Tzinieris explore how the country is carefully weighing up its strategic partnerships as it pursues a civil nuclear programme
The Kingdom at a Crossroads:Saudi Arabia’s nuclear prospects in an era of strategic competition
Get PDFSaudi Arabia faces an existential threat from a potentially proliferating Iran and an unpredictable ally in the Trump administration. Zoha Naser and Sarah Tzinieris explore how the country is carefully weighing up its strategic partnerships as it pursues a civil nuclear programme
Securing the nuclear supply chain::Addressing the issue of counterfeiting
No full textIn 2024, exploding pagers and walkie-talkies in Lebanon dramatically highlighted the importance of supply chain security and the risk that counterfeiting can pose. This article seeks to explore these issues in the nuclear context. Drawing on new empirical research, it examines how counterfeited materials, items, and technologies have found their way into nuclear supply chains and ultimately to facilities, exploring the impact of this and how the international community has responded. It finds that although counterfeits can and indeed have created significant nuclear risks, historically this issue has received relatively little attention. Here, a general lack of awareness, an overly narrow focus on their impact on critical safety systems, and the absence of comprehensive reporting mechanisms mean that the number of known counterfeits that have penetrated nuclear facilities globally is likely to be significantly underestimated. Although new international efforts in this area aimed at securing the nuclear supply chain have been launched in recent years, there remains much to be done, with considerable variation in the maturity of different countries and organizations’ approaches to this issue
The EU and its China Agenda: Limited cooperation under rising tensions
No full textThe EU defined China as a “cooperation and negotiating partner, an economic competitor, and a systemic rival” in its 2019 Strategic Outlook, the last comprehensive document on EU-China relations. Although elements of rivalry, competition, and tensions are increasingly visible in public discourse – and the recent US administrations under Biden and Trump have actively pushed for a more hawkish stance of the EU on China – Brussels and Beijing continue to engage in day-to-day cooperation, driven by important trading interests for both sides. Drawing on an approach of coopetition, we demonstrate that EU-China competition is mainly limited by systemic factors, namely shifting views in the EU on China amid its rapid rise, China's budding friendship with Russia since the Ukraine war, and the dynamics of the transatlantic relationship. Albeit limited in scope, ongoing EU-China engagement as we argue is the result of complex interdependence, converging policy objectives, and a pragmatic approach to cooperation. This ultimately leads to hedging behaviour on the part of the EU within US-China competition
A Fifth Face? The Evolving Threat of Nuclear Terrorism in the Age of Artificial Intelligence
No full textThe contemporary era is increasingly influenced by artificial intelligence (AI), a technology whose rapid development is reshaping industries, societies, and security around the world. From increasing the efficiency of complex systems to establishing new forms of communication, the transformative potential of AI has become hard to ignore. Yet despite its many benefits, AI also carries the potential to exacerbate existing security vulnerabilities and create new threats. These risks are particularly acute in the nuclear context, where an uncontrolled radiological release would threaten human and ecological life. Although the nuclear community is more sanguine about the prospect of nuclear terrorism two decades on from the alarmism of the 9/11 era, the threat still exists; and into the mix today is the growing risk that non-state actors could exploit AI for nefarious goals. Such use could manifest in a number of ways: terrorist groups might use AI tools to identify security gaps and automate reconnaissance of nuclear facilities; they might also use AI to manipulate cyber-physical systems to bypass important security measures; and in another scenario, AI could be used by non-state actors who intend to acquire or weaponize nuclear capabilities or sabotage nuclear facilities. With the visible lack of recent international attention on the specter of nuclear terrorism, it can be argued that with the advent of AI the risks are higher than at any point since the post-9/11 era. And this is in the context of official threat assessments that continue to emphasize the threats posed by non-state actors seeking diverse methods to cause harm for political purposes. As with all technologies, AI carries benefits as well as risks. Nuclear security involves the protection of nuclear facilities and materials, so advanced technologies can create efficiencies and improvements in the business of protecting critical infrastructure. For example, AI can be used for enhanced threat detection, predictive analytics, and insider risk mitigation. Thus, AI presents a sort of paradox. Most of its capabilities, including algorithms and computational techniques, are easily accessible and can be utilized to facilitate innovation within civilian sectors. However, AI’s ease of access and adaptive nature is equally attractive to those who seek to do harm, and could just as easily be utilized to enhance extremist violence.As AI introduces new elements into the nuclear security landscape, a paradigm shift is required in the nuclear industry. This shift should cover how risks are assessed as well as how mitigation strategies are formulated and implemented. In particular, AI has the potential to significantly lower the level of technical capabilities that have been traditionally required for non-state actors to plan and execute attacks against nuclear assets. With AI tools for image analysis, data processing, and complex system modeling now more accessible, specialized knowledge and software that were once exclusive to states have become more widespread. Consequently, non-state groups with limited capabilities could potentially leverage AI tools for reconnaissance, attack planning, or malicious campaigns against nuclear targets. Likewise, AI might increase the potential for a highly sophisticated cyber-physical attack against the digital control systems of nuclear facilities. The pace of AI development may outstrip existing governance structures and security protocols, which in turn could erode a critical window of vulnerability. In addition, emerging technologies tend to develop in an environment where regulation is still to catch up. Such dilemmas, where defensive and regulatory capacities lag behind the offensive potential, mean that AI tools may become accessible to threat actors before effective countermeasures are in place. This is no longer a theoretical concern but a real vulnerability that needs to be addressed. However, research into the malicious applications of AI remains underdeveloped, and the gap is especially pronounced when it comes to studying AI-enhanced terrorism with a chemical, biological, radiological, and nuclear (CBRN) lens.This article seeks to fill the scholarly gap through its exploration of the nexus of terrorism, AI, and nuclear security. It examines whether use of AI can lower the threshold for planning, optimizing attack vectors, and accessing sensitive materials—all of which make a nuclear terrorist attack more likely. The contributions of the article to the literature are twofold. First, it seeks to reignite debates over nuclear alarmism, revisiting such a discussion through the contemporary lens of AI and emerging technologies. Here, the article argues that previous dismissals of nuclear terrorism as unlikely under this paradigm are no longer true, as the “tremendous effort” of conducting a nuclear terrorist attack has arguably been lessened with the advent of AI. Second, it seeks to refresh nuclear scholarship and scenario building exercises, with a focus on updating Charles Ferguson and William Potter’s seminal work The Four Faces of Nuclear Terrorism for the digital age. In so doing, the article revisits the dormant debate of nuclear alarmism and pessimism over nuclear terrorism to argue that an updated AI lens requires a reckoning on the new vectors and manifestations of nuclear terrorism.<br/
Bespoke Simulator for Human Activity Classification with Bistatic Radar
Get PDFRadar is now widely used in human activity classification because of its contactless sensing capabilities, robustness to light conditions and privacy preservation compared to plain optical images. It has great value in elderly care, monitoring accidental falls and abnormal behaviours. Monostatic radar suffers from degradation in performance with varying aspect angles with respect to the target. Bistatic radar may offer a solution to this problem but finding the right geometry can be quite resource-intensive. We propose a bespoke simulation framework to test the radar geometry for human activity recognition. First, the analysis focuses on the monostatic radar model based on the Doppler effect in radar. We analyse the spectrogram of different motions by Short-time Fourier analysis (STFT), and then the classification data set was built for feature extraction and classification. The results show that the monostatic radar system has the highest accuracy, up to 98.17%. So, a bistatic radar model with separate transmitter and receiver was established in the experiment, and results show that bistatic radar with specific geometry configuration (CB2.5) not only has higher classification accuracy than monostatic radar in each aspect angle but also can recognise the object in a wider angle range. After training and fusing the data of all angles, it is found that the accuracy, sensitivity, and specificities of CB2.5 have 2.2%, 7.7% and 1.5% improvement compared with monostatic radar
Elderly Care - Human Activity Recognition Using Radar with an Open Dataset and Hybrid Maps
Get PDFPopulation ageing has become a severe problem worldwide. Human activity recognition (HAR) can play an important role to provide the elders with in-time healthcare. With the advantages of environmental insensitivity, contactless sensing and privacy protection, radar has been widely used for human activity detection. The micro-Doppler signatures (spectrograms) contain much information about human motion and are often applied in HAR. However, spectrograms only interpret magnitude information, resulting in suboptimal performances. We propose a radar-based HAR system using deep learning techniques. The data applied came from the open dataset “Radar signatures of human activities” created by the University of Glasgow. A new type of hybrid map was proposed, which concatenated the spectrograms amplitude and phase. After cropping the hybrid maps to focus on useful information, a convolutional neural network (CNN) based on LeNet-5 was designed for feature extraction and classification. In addition, the idea of transfer learning was applied for radar-based HAR to evaluate the classification performance of a pre-trained network. For this, GoogLeNet was taken and trained on the newly-produced hybrid maps. These initial results showed that the LeNet-5 CNN using only the spectrograms obtained an accuracy of 80.5%, while using the hybrid maps reached an accuracy of 84.3%, increasing by 3.8%. The classification result of transfer learning using GoogLeNet was 86.0%
Securing the Nuclear Supply Chain: A Handbook of Case Studies on Counterfeit, Fraudulent and Suspect Items
Get PDFThis document, "Securing the Nuclear Supply Chain: A Handbook of Case Studies on Counterfeit, Fraudulent, and Suspect Items", is the product of a nine-month period of desktop and investigatory research. It was funded through an International Atomic Energy Agency (IAEA) Coordinated Research Project (CRP). It is envisaged that this guide on CFSIs, utilising real-life case studies, will be a valuable source for governments, industry and others around the world to help prevent CFSIs, or at least mitigate their effects, within the nuclear supply chain. Compiled by researchers and academics at King’s College London, the objective is to provide comprehensive, evidence-based and objective information about CFSIs and the implications for nuclear security. Through probing a number of case studies, the handbook explores known cases of CFSIs found in the nuclear supply chain where there are particular nuclear security aspects identified or if the events can be extrapolated logically to demonstrate nuclear security risks. In addition, the handbook provides policy recommendations to the IAEA and its Member States for preventing the entry of CFSIs into the nuclear supply chain, mitigating the risks and consequences of their presence, and facilitating their detection and removal
The frequency of questionable research practices in the domain of medical writing among the various health professionals of Pakistan: An analytical cross-sectional study
Get PDFBackground and Aim: The vibrant cases of scientific misconducts have gained a significant attention in the recent times; however less obviously questionable research practices (QRPs) might be more ubiquitous and can thus ultimately severely affect the academic originality. The present study aimed to explore the frequency of questionable research practices among the doctors and dentists of Pakistan. Materials & Methods: The current study was a descriptive-analytical cross-sectional one which included 108 doctors and dentists of different Medical and Dental Colleges of Lahore, Pakistan. All the participants were selected from academia; were briefly explained about the purpose of the study and finally informed consent was obtained prior to their incorporation in the study. The subjects included in the study were questioned about QRPs. The questionnaire included the following questions: 1) Refusal of research data sharing with legitimate authors? 2) Any author addition to research without their contribution? 3) Any honorary authorship claimed without contribution to research? 4) Have you eliminated someone who justified their contribution? 5) Have you submitted any publication data without the consent of other authors? 6) Any research paper submitted to more than one journal at a time? 
The Frequency of Questionable Research Practices in the Domain of Medical Writing Among the Various Health Professionals of Pakistan: an Analytical Cross-sectional Study
No full textBackground and Aim: The vibrant cases of scientific misconducts have gained a significant attention in the recent times; however less obviously questionable research practices (QRPs) might be more ubiquitous and can thus ultimately severely affect the academic originality. The present study aimed to explore the frequency of questionable research practices among the doctors and dentists of Pakistan. Materials & Methods: The current study was a descriptive-analytical cross-sectional one which included 108 doctors and dentists of different Medical and Dental Colleges of Lahore, Pakistan. All the participants were selected from academia; were briefly explained about the purpose of the study and finally informed consent was obtained prior to their incorporation in the study. The subjects included in the study were questioned about QRPs. The questionnaire included the following questions: 1) Refusal of research data sharing with legitimate authors? 2) Any author addition to research without their contribution? 3) Any honorary authorship claimed without contribution to research? 4) Have you eliminated someone who justified their contribution? 5) Have you submitted any publication data without the consent of other authors? 6) Any research paper submitted to more than one journal at a time? 
