Anonymised Machine Learning with Distributed -full title is in the event details
Description changed:
This is a joint Scottish Blockchain and Scotland Data Science & Technology Meetup
Title: Towards Anonymization for Learning, Transactions and Credentials Within Distributed Trust Infrastructures
Speakers: Will Abramson, Liam Bell, Bill Buchanan, Adam Hall: Blockpass ID Lab.
Date: Tuesday 25th June 2019 @ 6pm
Outline:
GDPR defines an increased focused on encryption and pseudo-anonymization. But many recent data breaches have shown that organisations often have poor practice when it comes to the anonymisation of personally identifiable information. And so, in future systems, we need to focus on the anonymisation the lowest layers of our data gathering, and then identify methods of revealing the information. But how are we going to apply machine learning into infrastructure which use encrypted data? And how are we going to identify individuals within anonymised infrastructures? And how are we going to be able to regulate for consent, privacy and governance?
This Meetup will outline current research into areas such as machine learning on encrypted data, anonymised and trusted credentials, range proofs, and in the trusted deletion of data.
Speakers:
Anonymised and Distributed Machine Learning, Adam Hall. 20 min - https://www.linkedin.com/in/adam-james-hall-1b0229113
Trusted Deletion of Data, Liam Bell. 20 min - https://www.linkedin.com/in/liamjohnbell
Anonymised and Trusted Credentials, Will Abramson. 20 min.
Range Proofs, Mimblewimble, and other Crypto Magic, Prof Bill Buchanan. 20 min - https://www.linkedin.com/in/billatnapier
This is a joint Scottish Blockchain and Scotland Data Science & Technology Meetup
Title: Towards Anonymization for Learning, Transactions and Credentials Within Distributed Trust Infrastructures
Speakers: Will Abramson, Liam Bell, Bill Buchanan, Adam Hall: Blockpass ID Lab.
Date: Tuesday 27th August 2019 @ 6pm
Outline:
GDPR defines an increased focused on encryption and pseudo-anonymization. But many recent data breaches have shown that organisations often have poor practice when it comes to the anonymisation of personally identifiable information. And so, in future systems, we need to focus on the anonymisation the lowest layers of our data gathering, and then identify methods of revealing the information. But how are we going to apply machine learning into infrastructure which use encrypted data? And how are we going to identify individuals within anonymised infrastructures? And how are we going to be able to regulate for consent, privacy and governance?
This Meetup will outline current research into areas such as machine learning on encrypted data, anonymised and trusted credentials, range proofs, and in the trusted deletion of data.
Speakers:
Anonymised and Distributed Machine Learning, Adam Hall. 20 min - https://www.linkedin.com/in/adam-james-hall-1b0229113
Trusted Deletion of Data, Liam Bell. 20 min - https://www.linkedin.com/in/liamjohnbell
Anonymised and Trusted Credentials, Will Abramson. 20 min.
Range Proofs, Mimblewimble, and other Crypto Magic, Prof Bill Buchanan. 20 min - https://www.linkedin.com/in/billatnapier
This is a joint Scottish Blockchain and Scotland Data Science & Technology Meetup
Title: Towards Anonymization for Learning, Transactions and Credentials Within Distributed Trust Infrastructures
Speakers: Will Abramson, Liam Bell, Bill Buchanan, Adam Hall: Blockpass ID Lab.
Date: Tuesday 27th August 2019 @ 6pm
Outline:
GDPR defines an increased focused on encryption and pseudo-anonymization. But many recent data breaches have shown that organisations often have poor practice when it comes to the anonymisation of personally identifiable information. And so, in future systems, we need to focus on the anonymisation the lowest layers of our data gathering, and then identify methods of revealing the information. But how are we going to apply machine learning into infrastructure which use encrypted data? And how are we going to identify individuals within anonymised infrastructures? And how are we going to be able to regulate for consent, privacy and governance?
This Meetup will outline current research into areas such as machine learning on encrypted data, anonymised and trusted credentials, range proofs, and in the trusted deletion of data.
Speakers:
Anonymised and Distributed Machine Learning, Adam Hall. 20 min - https://www.linkedin.com/in/adam-james-hall-1b0229113
Trusted Deletion of Data, Liam Bell. 20 min - https://www.linkedin.com/in/liamjohnbell
Anonymised and Trusted Credentials, Will Abramson. 20 min.
Range Proofs, Mimblewimble, and other Crypto Magic, Prof Bill Buchanan. 20 min - https://www.linkedin.com/in/billatnapier
GDPR defines an increased focused on encryption and pseudo-anonymization. But many recent data breaches have shown that organisations often have poor practice when it comes to the anonymisation of personally identifiable information. And so, in future systems, we need to focus on the anonymisation the lowest layers of our data gathering, and then identify methods of revealing the information. But how are we going to apply machine learning into infrastructure which use encrypted data? And how are we going to identify individuals within anonymised infrastructures? And how are we going to be able to regulate for consent, privacy and governance?
This Meetup includes presentations on:
Anonymised and Distributed Machine Learning, Adam Hall. 20 mins - https://www.linkedin.com/in/adam-james-hall-1b0229113
Digital Wallets, Will Abramson. 20 mins. https://www.linkedin.com/in/will-abramson-639975120/
The Future of Cryptography: Range Proofs, Mimblewimble, and other Crypto Magic, Prof Bill Buchanan. 30-40 mins. https://www.linkedin.com/in/billatnapier
