Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Will Abramson"'
Publikováno v:
Machine Learning and Knowledge Extraction, Vol 3, Iss 2, Pp 333-356 (2021)
A common privacy issue in traditional machine learning is that data needs to be disclosed for the training procedures. In situations with highly sensitive data such as healthcare records, accessing this information is challenging and often prohibited
Externí odkaz:
https://doaj.org/article/3b24c71bd4154361a98b16db0161fe2e
Autor:
Hisham Ali, Jawad Ahmad, Zakwan Jaroucheh, Pavlos Papadopoulos, Nikolaos Pitropakis, Owen Lo, Will Abramson, William J. Buchanan
Publikováno v:
Entropy, Vol 24, Iss 10, p 1379 (2022)
Historically, threat information sharing has relied on manual modelling and centralised network systems, which can be inefficient, insecure, and prone to errors. Alternatively, private blockchains are now widely used to address these issues and impro
Externí odkaz:
https://doaj.org/article/0b85401fac3c4ea9a8c3c42e73c6f365
Publikováno v:
Frontiers in Blockchain, Vol 4 (2021)
Externí odkaz:
https://doaj.org/article/807d8c2e4a9a41e587f4ec24609ea809
Publikováno v:
Blockchain in Healthcare Today (2020)
A substantial administrative burden is placed on healthcare professionals as they manage and progress through their careers. Identity verification, pre-employment screening and appraisals: the bureaucracy associated with each of these processes takes
Externí odkaz:
https://doaj.org/article/1c361ba9424b4b95a8ed1230d89c4332
Publikováno v:
Proceedings of the 8th International Conference on Information Systems Security and Privacy.
Autor:
Iain Barclay, Will Abramson
Publikováno v:
UbiComp/ISWC Adjunct
Artificial Intelligence (AI) systems are being deployed around the globe in critical fields such as healthcare and education. In some cases, expert practitioners in these domains are being tasked with introducing or using such systems, but have littl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7a2c8a2fb9cc22915daa8d41995964ec
http://arxiv.org/abs/2106.08258
http://arxiv.org/abs/2106.08258
Publikováno v:
Machine Learning and Knowledge Extraction, Vol 3, Iss 17, Pp 333-356 (2021)
Machine Learning and Knowledge Extraction
Volume 3
Issue 2
Pages 17-356
Machine Learning and Knowledge Extraction
Volume 3
Issue 2
Pages 17-356
A common privacy issue in traditional machine learning is that data needs to be disclosed for the training procedures. In situations with highly sensitive data such as healthcare records, accessing this information is challenging and often prohibited
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7e0bcabd5c1b5124dff1dd1fbf755a57
Publikováno v:
ICISSP
Scopus-Elsevier
Scopus-Elsevier
Autor:
Adam James Hall, Pavlos Papadopoulos, Nikolaos Pitropakis, Will Abramson, William J. Buchanan
Publikováno v:
Trust, Privacy and Security in Digital Business ISBN: 9783030589851
TrustBus
TrustBus
When training a machine learning model, it is standard procedure for the researcher to have full knowledge of both the data and model. However, this engenders a lack of trust between data owners and data scientists. Data owners are justifiably reluct
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::59329c4e30c484ee0e66cf73178c3e41
https://doi.org/10.1007/978-3-030-58986-8_14
https://doi.org/10.1007/978-3-030-58986-8_14