Leveraging the Multi-Stakeholder Nature of Cyber Security
Leveraging the Multi-Stakeholder Nature of Cyber Security
批准号:
EP/P011918/1
负责人:
Christian Wagner
金额:
$98.17万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2017
资助国家:
英国
项目状态:
已结题
起止时间:
2017 至 --
中文摘要
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英文摘要
Cyber Security (CyS) is a challenging, distributed, multi-stakeholder problem. It is distributed in the sense that the expertise to comprehensively assess the level of security of a given IT system is commonly not all available in one location; e.g. detail on the IT components within a company is available within that company, while detail on operating system software vulnerability may be available to the OS manufacturer and further expert insight may be available to public security agencies, such as CESG. It is a multi-stakeholder problem because a number of human stakeholders, from IT designers to users with varying levels of expertise, need to effectively communicate and work together in order to deliver systems with an appropriate level of CyS assurance.This interdisciplinary project brings together leading academic experts from the University of Nottingham, UK and Carnegie Mellon University, USA, with a strongly integrated project partner: CESG - the UK's National Technical Authority for Information Assurance. The project is designed to leverage the distributed, multiple human stakeholder nature of CyS by developing a novel framework with the necessary scientific underpinning to improve user access to user-tailored CyS information, operationalised as a cutting-edge, data-driven Online CYber Security decision support System (OCYSS). This approach id designed to directly address an acute shortage of availability and access to highly qualified CyS experts by both small-to-large scale users from government to industry. The role of OCYSS is to effectively and efficiently integrate expert and user inputs, capturing commonly uncertain vulnerability levels of individual components as well as vulnerabilities arising from the interaction/combination of these components, to efficiently deliver appropriate, balanced, informed and up-to-date threat analysis and CyS decision support to users. Importantly, the OCYSS framework:- Addresses the limited availability of CyS experts by comprehensively capturing and aggregating their insight and expertise to assess the vulnerability, including associated levels of uncertainty, of individual system components (e.g. intrusion detection, encryption) and their interactions (e.g. SSL 3.0 and weak password). This information is captured centrally by OCYSS and updated regularly. - Avoids delays in threat analysis and potential mitigation by providing a direct pathway for newly discovered component vulnerabilities & component interaction vulnerabilities (and associated uncertainty) to be rapidly put forward, incl. by manufacturers such as Oracle and third party organisations such as Symantec.- Is designed to deliver user-tailored, comprehensive and up-to-date threat analysis and decision support which is continuously updated as new information becomes available. OCYSS two-stage outputs capture uncertainty in A) the threat analysis inputs (e.g. uncertainty around a component vulnerability over time and by different experts) and B) in intuitive benefit-cost analysis on threat mitigation in response to asset ranking by users (e.g. a low value asset may not warrant a high investment to address a low threat).Going beyond the scope of a standard research project, this project is designed to not only deliver cutting-edge science, developing key advances in data science and HCI, but to also deliver a real-world, open source prototype of the OCYSS framework. This enables the project to conduct an exceptional level of evaluation and tailoring to real-world CyS challenges, including the deployment of OCYSS in real-world contexts such as government departments advised by CESG. Further, through this approach, the project is able to deliver both open source algorithms and a substantial open-source software platform prototype, facilitating the academic reproduction of results, as well as substantially boosting the potential of commercial up-take of the project outcomes.
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Responsible research and innovation in practice: Driving both the 'How' and the 'What' to research
实践中负责任的研究和创新:推动研究“如何”和“什么”
DOI:
10.1016/j.jrt.2022.100042
发表时间:
2022
期刊:
Journal of Responsible Technology
影响因子:
--
作者:
[Chen J]
通讯作者:
Chen J
Do People Prefer to Give Interval-Valued or Point Estimates and Why?
人们更喜欢给出区间值估计还是点估计?为什么?
DOI:
10.1109/fuzz45933.2021.9494507
发表时间:
2021
期刊:
影响因子:
--
作者:
[Ellerby Z]
通讯作者:
Ellerby Z
Insights from interval-valued ratings of consumer products-a DECSYS appraisal
消费产品区间值评级的见解——DECSYS 评估
DOI:
10.1109/fuzz48607.2020.9177634
发表时间:
2020
期刊:
影响因子:
--
作者:
[Ellerby Z]
通讯作者:
Ellerby Z
DOI:
10.1109/tfuzz.2021.3136349
发表时间:
2022-09
期刊:
IEEE Transactions on Fuzzy Systems
影响因子:
11.9
作者:
[Laura De Miguel;R. Santiago;Christian Wagner;J. Garibaldi;Z. Takác̆;A.F. Roldan Lopez de Hierro;H. Bustince]
通讯作者:
Laura De Miguel;R. Santiago;Christian Wagner;J. Garibaldi;Z. Takác̆;A.F. Roldan Lopez de Hierro;H. Bustince
DECSYS – Discrete and Ellipse-based response Capture SYStem
DECSYS – 离散和基于椭圆的响应捕获系统
DOI:
10.1109/fuzz-ieee.2019.8858996
发表时间:
2019
期刊:
2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
影响因子:
--
作者:
[Zack Ellerby, Josie McCulloch, J. Young, Christian Wagner]
通讯作者:
Christian Wagner
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