All AI Security & AI Safety Posts
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AI Security
The Dark Art of Model Stealing: What You Need to Know
Model stealing, also known as model extraction, is the practice of reverse engineering a machine learning model owned by a third party without explicit authorization. Attackers don't need direct access to the model's parameters or training data to accomplish this. Instead, they often interact with the model via its API or any public interface, making queries (i.e., sending input data) and receiving predictions (i.e., output…
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Society 5.0
5G Innovation Zones in Canada for Launching AI and 5G in Tandem
In my previous post I argued that if Canada wants to succeed with its AI-focused innovation agenda, it should also be at the forefront of 5G innovation and development. Canada could get ahead in the global 5G race not by being the first to 5G, but by being the first to roll out 5G in the right way – addressing cybersecurity, linking development of AI…
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5G Security
5G and AI – Getting Smart About 5G and AI in Canada
Canada has been investing in machine learning and artificial intelligence (AI) for longer than most of the industrialized world. Dr. Geoff Hinton of Google helped ignite the field of graphics processing unit (GPU) deep learning at the University of Toronto. Then he became chief scientific advisor to the Vector Institute, which in collaboration with the University, aims to produce the largest number of deep learning…
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AI Security
AI and 5G: AI at the 5G Core – A Double-Edged Sword
If you’ve ever been to an expensive restaurant and ordered a familiar dish like, say, lasagna, but received a plate with five different elements arranged in a way that does not at all resemble what you know as lasagna, then you have probably tasted deconstructionism. This approach to cuisine aims to challenge the way our brain makes associations, to break existing patterns of interpretation and,…
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AI Security
Risks of AI – Meeting the Ghost in the Machine
Because it demands so much manpower, cybersecurity has already benefited from AI and automation to improve threat prevention, detection and response. Preventing spam and identifying malware are already common examples. However, AI is also being used – and will be used more and more – by cybercriminals to circumvent cyberdefenses and bypass security algorithms. AI-driven cyberattacks have the potential to be faster, wider spread and…
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AI Security
Digital Double Helix: Why the Fates of 5G and AI are Intertwined
In 2013, George F. Young and colleagues completed a fascinating study into the science behind starling murmurations. These breathtaking displays of thousands – sometimes hundreds of thousands – of birds in a single flock swooping and diving around each other, look from a distance like a single organism organically shape-shifting before the viewer’s eyes. In their research article, Young et al reference the starling’s remarkable…
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AI Security
AI-Exacerbated Disinformation and Cyber Threats to Democracy
Recent events have confirmed that the cyber realm can be used to disrupt democracies as surely as it can destabilize dictatorships. Weaponization of information and malicious dissemination through social media pushes citizens into polarized echo chambers and pull at the social fabric of a country. Present technologies enhanced by current and upcoming Artificial Intelligence (AI) capabilities, could greatly exacerbate disinformation and other cyber threats to…
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AI Security
AI: The Shifting Battlefield in the Cyber Arms Race
Cybersecurity strategies need to change in order to address the new issues that Machine Learning (ML) and Artificial Intelligence (AI) bring into the equation. Although those issues have not yet reached crisis stage, signs are clear that they will need to be addressed – and soon – if cyberattackers are to be prevented from obtaining a decided advantage in the continuing arms race between hackers…
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