Centre for Secure Information Technologies (CSIT) - Phase 3
Centre for Secure Information Technologies (CSIT) - Phase 3
批准号:
EP/X022323/1
负责人:
Máire O'Neill
金额:
$539.59万
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2022
资助国家:
英国
项目状态:
未结题
起止时间:
2022 至 --
中文摘要
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英文摘要
Cyber-attacks such as those recently perpetrated on Solarwinds, Colonial Pipeline and Viasat are scaling at an alarming rate. Resilient cyber security technologies are vital to ensure that society can safely and confidently adopt new digital technologies. As our world becomes increasingly digitally connected for utilities, travel, healthcare, education, and commerce, and with the increasing use of artificial intelligence, cyber-physical infrastructure and the commercialisation of space-based entities, new security vulnerabilities are also emerging. This for novel cyber security solutions and secure technology supply chains presents key opportunities for research, innovation and economic impact. Based at Queen's University Belfast, CSIT is a global research and innovation hub for cyber security, and the UK's Innovation and Knowledge Centre (IKC) for cyber security research. CSIT is therefore in a strong position to make further and significant contributions, maintaining the UK's international research reputation and enhancing its economic and business competitiveness. Through its unique open innovation model with trusted industry partners, CSIT is pioneering research and innovation to protect citizens and businesses and drive economic impact. CSIT's unique model of innovation incorporates a significant engineering and professional services capability differentiating it from other cyber security academic research centres. As a delivery partner of LORCA, the DCMS funded cyber security accelerator, CSIT supported the growth of 70+ UK cyber security companies through knowledge transfer and product development.CSIT has successfully delivered during IKC Phases 1 and 2, and over the next 5 years we will consolidate and raise our level of impact nationally and internationally, continuing to fulfil our key role linking industry, government and academic expertise to promote economic growth. Under the theme of "Securing Complex Systems", CSIT will research and develop new technologies, acting as a nucleating point to accelerate and promote disruptive business opportunities that arise for the wider benefit of the UK cybersecurity industry. This will enable CSIT to seed new research activity in emerging areas of cyber security including, Semiconductor Chip Security, Secure and Resilient Cyber-Physical Infrastructure, Securing Machine Learning, as well as targeting Space Security as a new sectoral focus, with the aim of attracting new funding to drive collaborative research and innovation in these areas.To raise our level of impact, CSIT will build Hubs of Impact with industry partners in one or more of the research areas identified above, modelled on the proposed 'Cyber-AI Technologies Hub' in which CSIT will partner with eight cyber security technology companies to collaborate on the development of new solutions to shared challenges. We conservatively estimate that the £3M investment for CSIT3 could help to unlock up to £10.7M in economic impact across the UK, facilitated by job creation through research projects, support for economic clusters across the UK, engineering support for start-ups and scale-ups, and through public engagement with potential investors to the UK. CSIT3 targets over the next 5 years include: (a) £12M in public research and innovation funding; (b) £900k in industry membership fees; (c) at least 5 examples of successful translation and IP activity from CSIT research; (d) 10 funded industry-academic collaborative projects; and (e) 1 Hub of Impact. Based on CSIT's track record, we fully expect to deliver additional impact beyond these targets and further strengthen the UK's reputation as a global leader in cyber security research and innovation.
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DOI:
10.1109/ijcnn54540.2023.10191743
发表时间:
2023-03
期刊:
2023 International Joint Conference on Neural Networks (IJCNN)
影响因子:
--
作者:
[Ayoub Arous;Amira Guesmi;M. Hanif;Ihsen Alouani;Muhammad Shafique]
通讯作者:
Ayoub Arous;Amira Guesmi;M. Hanif;Ihsen Alouani;Muhammad Shafique
Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing - Use Cases and Emerging Challenges
用于网络物理、物联网和边缘计算的嵌入式机器学习 - 用例和新兴挑战
DOI:
10.1007/978-3-031-40677-5_19
发表时间:
2024
期刊:
影响因子:
--
作者:
[Alouani I]
通讯作者:
Alouani I
Digital Twin-Enhanced Incident Response for Cyber-Physical Systems
网络物理系统的数字孪生增强事件响应
DOI:
10.1145/3600160.3600195
发表时间:
2023
期刊:
影响因子:
--
作者:
[Allison D]
通讯作者:
Allison D
DOI:
10.1109/tdsc.2023.3277939
发表时间:
2024-05
期刊:
IEEE Transactions on Dependable and Secure Computing
影响因子:
7.3
作者:
[Conor Black;Sandra Scott-Hayward]
通讯作者:
Conor Black;Sandra Scott-Hayward
DOI:
10.1109/vts52500.2021.9794253
发表时间:
2022-04
期刊:
2022 IEEE 40th VLSI Test Symposium (VTS)
影响因子:
--
作者:
[Shail Dave;Alberto Marchisio;M. Hanif;Amira Guesmi;Aviral Shrivastava;Ihsen Alouani;Muhammad Shafique]
通讯作者:
Shail Dave;Alberto Marchisio;M. Hanif;Amira Guesmi;Aviral Shrivastava;Ihsen Alouani;Muhammad Shafique
共 10 条
TruDetect: Trustworthy Deep-Learning based Hardware Trojan Detection
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批准号:EP/X036960/1
-
项目类别:Research Grant
-
资助金额:$112.27万
-
财政年份:2023
-
负责人:Máire O'Neill
-
依托单位:
SIPP - Secure IoT Processor Platform with Remote Attestation
-
批准号:EP/S030867/1
-
项目类别:Research Grant
-
资助金额:$164.99万
-
财政年份:2019
-
负责人:Máire O'Neill
-
依托单位:
DeepSecurity - Applying Deep Learning to Hardware Security
-
批准号:EP/R011494/1
-
项目类别:Research Grant
-
资助金额:$97.58万
-
财政年份:2017
-
负责人:Máire O'Neill
-
依托单位:
Next-Generation Data Security Architectures
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批准号:EP/G007586/1
-
项目类别:Fellowship
-
资助金额:$184.8万
-
财政年份:2008
-
负责人:Máire O'Neill
-
依托单位:
海外基金