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This is the number one must strategy in preventing attacks to Deep Learning networks.
Any risk mitigation technique which is reactive (read as wait for bad things happening before acting) is destined to fail.
Fighting fire with fire: Using deep learning or any AI-based strategy, as attackers are already leveraging DL and AI to attack DL networks. Traditional rule-based strategies do not fit this scenario.
Unfortunately I cannot share details on this front. By the way, biotech manufacturing cyber security shares risks and mitigation strategies with any other manufacturing business.
Are you implementing any kind of AI projects/programs or techniques for dealing with cyber threats in your company?
There are plenty of opportunities to apply AI to the Cyber Space, during my talk I am going to show some interesting applications of Deep Learning in malware detection. But there is still lack of culture in this direction and most of all, some concerns about ethics or explanation of AI systems applied to cyber security problems, preventing progress in this direction. Personally to me, these concerns don’t make sense (I am going to cover these matters as well during my talk). Unfortunately, at present time I can’t discover details about corporate AI/cyber security strategies.
This is a new frontier of cyber security, but I can still see here the same bad practices applied to traditional on-prem and cloud systems. So, I believe that applying most part of the best practices and the same culture of quality as for other systems would be a good start.
AI, Deep Learning, culture change.
More than a lack of cybersecurity talents, I am seeing a lack of culture about cyber security in the biotech/pharmaceutical industry (same as in some other industries). In particular, I am observing a reactive only approach to cyber security remediation and a cyber security strategy which doesn’t consider its impact on people productivity.
Guglielmo IOZZIA is currently Associate Director at MSD Global and based in the new MSD Biotech facilities in Dublin (Ireland), where he is trying to unlock business value through ML/AI in the biotech manufacturing space, by using in particular computer vision. He was previously at Optum (UnitedHealth Group) Ireland dealing with projects in the PI (fraud, waste and abuse, claims processing) mostly, but also in general in the healthcare space. He has previously worked at IBM Ireland, part of cloud automation first and ethical hacking team then, where he switched his career path from test automation to analytics and machine learning/deep learning.
He is passionate, among other things, about AI and cyber security, not just for professional purposes, but also for personal initiatives and interest.
Starting from 2018 he is being invited to present at several international conferences such as DataWorks Summit, Google I/O Extended, Predictive Analytics World for Industry 4.0, CIO Conference Ireland and UK, Spark+AI Summit and many others. His first technical book “Hands-on Deep Learning with Apache Spark” has been released in January 2019 and his second one about XAI is expected to be released in 2021.