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Academic Centre of Excellence in Cyber Security Research - University of Northumbria at Newcastle

Academic Centre of Excellence in Cyber Security Research - University of Northumbria at Newcastle
网络安全研究卓越学术中心 - 诺森比亚大学纽卡斯尔分校
批准号:
EP/T009543/1
负责人:
Lynne Coventry
金额:
$6.19万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2019
资助国家:
英国
项目状态:
未结题
起止时间:
2019 至 --

项目摘要

项目成果

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中文摘要
翻译
诺森比亚大学通过网络安全研究小组(CSRG)的工作将多个学科的知识应用到数字安全中-这是一个跨大学的小组,它结合了(i)生物识别加密,无线传感器网络,网络安全协议,声音处理和图像识别的技术研究,(ii)以人为本的可用安全,隐私,信任和行为改变的工作。我们的工作确保各个学科优化他们对自己学科的贡献,同时共同努力了解交互点;计算机和人类的不同优势和弱点,以及他们如何最好地合作来捍卫企业。该研究小组的愿景是通过最大限度地提高技术发展,了解人类网络安全行为并探索影响行为变化的因素,包括设计,法律,政策和社会背景,来保护我们的数字化明天。我们寻求优化公民作为网络卫士的行为,并优化我们对入侵的技术防御。诺森比亚的数字生活主题提供了一个机会,可以将计算和行为科学,法律和设计,特别是围绕安全的大数据和物联网,整个生命周期的个人安全和建设弹性智能城市(我们目前正在与纽卡斯尔大学和纽卡斯尔和盖茨黑德市议会合作,作为EPSRC资助的城市生活伙伴关系的一部分)。此外,作为健康和社会保健多学科研究主题的一部分,我们正在增加我们的研究,重点是健康和社会保健领域的网络安全,因为他们努力将个人信息学,人工智能和嵌入式无线医疗设备的进步与过时的遗留系统,不良的安全行为和弱势群体相协调。我们将通过以下方式实现这一愿景:(i)整合多个学科,以扩大我们对网络安全行为的理解。这将包括法律、道德、政策和设计。(ii)探讨如何最好地促进网络安全行为的改变㈢探讨不同人群的需求,并设计包容性。与此同时,将继续开展工作,以便(四)建立适应性技术防御,用于访问控制、网络入侵检测和网络钓鱼检测,从而减轻用户的负担。
英文摘要
Northumbria University applies knowledge from multiple disciplines, into digital security through the work of the Cyber Security Research Group (CSRG) - a cross university group that combines (i) technical research on biometric encryption, wireless sensor networks, web security protocols, sonification and image recognition, with (ii) human-centred work on usable security, privacy, trust and behaviour change. Our work ensures that the individual disciplines optimise their contribution to their own discipline, while working together to understand the point of interaction; the different strengths and weaknesses of computers and humans and how they can best work together to defend the enterprise. The vision of this research group is to secure our digital tomorrow by maximising technological developments, understanding human cybersecurity behaviours and exploring the factors that influence behaviour change including design, law, policy and the social context. We seek to optimise our citizens behaviours as cyber-defenders as well as optimise our technology defences against intrusions. Northumbria's Digital Living theme provides an opportunity to integrate work across the computational & behavioural sciences, law and design, particularly around secure Big Data & IoT, personal security across the lifespan and building resilient smart cities (where we are currently working in partnership with Newcastle University and Newcastle & Gateshead City Councils as part of the EPSRC funded Urban Living Partnership). In addition as part of the Health and Social Care multidisciplinary research theme, we are growing our research focusing on cybersecurity in the health and social care domains as they struggle to reconcile advances in personal informatics, AI and embedded wireless medical devices with outdated legacy systems, poor security behaviours and vulnerable populations. We will achieve this vision by (i) incorporating multiple disciplines to broaden our understanding of cybersecurity behaviours. This will include law, ethics, policy and design. (ii) exploring how best to facilitate cybersecurity behaviour change (iii) exploring the needs of diverse populations and designing for inclusivity. At the same time work will continue to (iv) build adaptive technology defences for access control, network intrusion detection and phishing detection - thus reducing the burden on users.
期刊论文(10)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1007/s00138-020-01103-3
发表时间: 2020-07
期刊: Machine Vision and Applications
影响因子: 3.3
作者: [Jumma Almaghtuf;F. Khelifi;A. Bouridane]
通讯作者: Jumma Almaghtuf;F. Khelifi;A. Bouridane
The Workplace Information Sensitivity Appraisal (WISA) scale
工作场所信息敏感性评估(WISA)量表
DOI: 10.1016/j.chbr.2022.100240
发表时间: 2022
期刊: Computers in Human Behavior Reports
影响因子: --
作者: [Blythe J]
通讯作者: Blythe J
The 'Northumbria Temporal Image Forensics' Database: Description and Analysis
“诺森比亚时态图像取证”数据库:描述和分析
DOI: 10.1109/codit49905.2020.9263888
发表时间: 2020
期刊:
影响因子: --
作者: [Ahmed F]
通讯作者: Ahmed F
Temporal Image Forensic Analysis for Picture Dating with Deep Learning
利用深度学习进行图片约会的时态图像取证分析
DOI: 10.1109/iccece49321.2020.9231160
发表时间: 2020
期刊:
影响因子: --
作者: [Ahmed F]
通讯作者: Ahmed F
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