Difference between revisions of "AFSecurity Seminar"
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| − | | '''TIME:''' | + | | '''TIME:''' Friday 9 June 2023, 14:00h<br />'''PLACE:''' Auditorium Smalltalk, 1st floor, IFI, UiO, Ole Johan Dahls hus, Gaustadalleen 23b, Oslo. [https://kart.finn.no/?lng=10.71782&lat=59.94342&zoom=17&mapType=normap&markers=10.71782,59.94342,r,Gaustadall%C3%A9en+23B See map].<br /> |
Coffee and snacks will be served.<br /> | Coffee and snacks will be served.<br /> | ||
<br />'''AGENDA:'''<br /> | <br />'''AGENDA:'''<br /> | ||
14:00h Welcome at IFI and AF''Security''<br />14:15 Invited talk<br /> | 14:00h Welcome at IFI and AF''Security''<br />14:15 Invited talk<br /> | ||
| − | * TITLE: '' | + | * TITLE: ''Challenges in Learning from Behaviour'' |
| − | * | + | * SPEAKERS: David Aspinall and Robert Flood, University of Edinburgh |
| <center>[[File:photo-Daniela-Poehn.jpg|150px|link=https://dpoehn.de]]</center> | | <center>[[File:photo-Daniela-Poehn.jpg|150px|link=https://dpoehn.de]]</center> | ||
| − | | <center> [[File:logo- | + | | <center> [[File:logo-univ-edinbourgh.png|150px|link=https://www.ed.ac.uk/]]</center> |
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| − | * ABSTRACT:<br /> | + | * ABSTRACT:<br />Artificial Intelligence and Machine Learning are promoted as solutions for cyber security which can adapt to changes in attacker behaviour, learning models from data to distinguish what is normal and what may consitute a threat. Despite much research, there are still fundamental challenges in each stage of the process which prevent us having good benchmarks to understand the robustness of state-of-the-art models. The challenges span: collecting and sharing data safely, ensuring a sufficient fidelity and diversity of data, and then understanding model performance. We will consider these challenges in turn and present some recent research results which address each aspect. Under the second challenge, we will introduce some work-in-progress on identifying "bad smells" for cyber security datasets used for training.<br /> |
'''BIO:''' | '''BIO:''' | ||
| − | <br /> | + | <br />David Aspinall is Professor of Software Safety and Security at the University of Edinburgh. He is Director of the University's UK government recognised Academic Centre of Excellence in Cyber Security Research and was a Fellow of the Alan Turing Institute from 2015-2021. |
| + | His research interests range from foundations for formal methods in software security to more applied areas including anomaly detection in network security. | ||
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| + | Robert Flood is a PhD student in the University of Edinburgh where he previously studied for an MSc in Computer Science. His PhD primarily focuses on synthetic data generation for training anomaly detection systems. He has also worked with cyber security data anonymisation and software correctness with The Turing Institute and The University of Edinburgh. | ||
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Revision as of 13:30, 30 May 2023
| TIME: Friday 9 June 2023, 14:00h PLACE: Auditorium Smalltalk, 1st floor, IFI, UiO, Ole Johan Dahls hus, Gaustadalleen 23b, Oslo. See map. Coffee and snacks will be served.
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- ABSTRACT:
Artificial Intelligence and Machine Learning are promoted as solutions for cyber security which can adapt to changes in attacker behaviour, learning models from data to distinguish what is normal and what may consitute a threat. Despite much research, there are still fundamental challenges in each stage of the process which prevent us having good benchmarks to understand the robustness of state-of-the-art models. The challenges span: collecting and sharing data safely, ensuring a sufficient fidelity and diversity of data, and then understanding model performance. We will consider these challenges in turn and present some recent research results which address each aspect. Under the second challenge, we will introduce some work-in-progress on identifying "bad smells" for cyber security datasets used for training.
BIO:
David Aspinall is Professor of Software Safety and Security at the University of Edinburgh. He is Director of the University's UK government recognised Academic Centre of Excellence in Cyber Security Research and was a Fellow of the Alan Turing Institute from 2015-2021.
His research interests range from foundations for formal methods in software security to more applied areas including anomaly detection in network security.
Robert Flood is a PhD student in the University of Edinburgh where he previously studied for an MSc in Computer Science. His PhD primarily focuses on synthetic data generation for training anomaly detection systems. He has also worked with cyber security data anonymisation and software correctness with The Turing Institute and The University of Edinburgh.
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AFSecurity is organised by UiO Digital Security. | 
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