Go read this feature on the 2011 RSA hack that redefined cybersecurity

Wired has published an in-depth feature on the 2011 hack of security company RSA, in which hackers stole the so-called “crown jewels of cybersecurity,” the secret keys forming a “crucial ingredient” of its SecurID two-factor authentication devices. It would go on to “redefine the cybersecurity landscape” with huge implications for not just RSA, but also the organizations that relied on its devices for their own security.

Wired’s Andy Greenberg describes the moment RSA analyst Todd Leetham discovered that hackers had accessed one of RSA’s most important pieces of data:

With a growing sense of dread, Leetham had finally traced the intruders’ footprints to their final targets: the secret keys known as “seeds,” a collection of numbers that represented a foundational layer of the security promises RSA made to its customers, including tens of millions of users in government and military agencies, defense contractors, banks, and countless corporations around the world.

One of the most interesting sections of the report describes how the hack affected the psychology of RSA’s employees, making them intensely paranoid. The company switched phone networks, started holding meetings in person, and shared documents on paper. The building was swept for bugs, and some office windows were covered in paper to prevent surveillance.

Paranoia was beginning to take hold in the company. The first night after the announcement, [RSA’s head of North American sales] remembers walking by a wiring closet and seeing an absurd number of people walking out of it, far more than he imagined could have ever fit. “Who are those people?” he asked another nearby executive. “That’s the government,” the executive responded vaguely.

The RSA hack was not only blamed for a subsequent hack of “at least one” US defense contractor, but it opened much of the world’s eyes to the danger of supply chain attacks. Rather than attacking a target directly, a supply chain attack sees hackers infiltrating one of their target’s suppliers to get behind their defenses, like what we saw with last year’s SolarWinds hack.

After 10 years of rampant state-sponsored hacking and supply chain hijacks, the RSA breach can now be seen as the herald of our current era of digital insecurity—and a lesson about how a determined adversary can undermine the things we trust most.

Wired’s feature is well worth a read.

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AI Redefined commits to better training models under new CEO

Join Transform 2021 this July 12-16. Register for the AI event of the year.

AI Redefined (AIR) is the developer behind an open source Cogment framework that makes it simpler for humans to train virtual agents created using AI models. Today the startup named G. Craig Vachon to be its CEO in place of Dorien Kieken, who will now assume the role of president.

Vachon is the founder of seed investment firm Chowdahead Growth Fund and has raised more than $1.6 billion in private equity, with investments in more than 30 companies across seven countries. He also serves on the Board of Directors for Yseop, provider of a natural language AI, and as a special advisor to the CEO of SupplyShift, a supply chain transparency platform used by Walmart and Amazon.

AI is a work in progress

As AI continues to evolve, it’s becoming clear humans will not be at the center of a lot of decision-making for much longer, Vachon told VentureBeat. The problem is that today’s AI models lack ethics, morality, and, for that matter, common sense. An AI model in a car may recognize a bouncing ball on a street, but — unlike a human — it will not reason that the presence of the ball means there is likely a child nearby unless it’s specifically trained to do so, Vachon noted.

Similarly, an AI model won’t recognize that a pizza order made to a 911 number might be a plea for help from someone being held hostage, he added.

Cogment provides a platform for humans to train AI models in a way that goes beyond simply recognizing different types of cat images, he said. For example, the framework provides the orchestration capabilities needed to create simulations involving multiple actors and enable humans to train virtual agents. “We want to keep the human in the loop,” Vachon said.

This approach to AI training will result in models that better augment the capabilities of humans rather than simply replacing them in the name of economic efficiency, Vachon added. There will eventually come a day when every individual has an AI model that has been trained to make optimal decisions and recommendations based on their personal preferences, he said. The challenge will be training those AI models to make decisions and recommendations that go beyond an analytics calculus.

More empathetic AI

In many ways, the ability to infuse AI models with some sense of empathy will prove crucial as AI models are embedded deeply within digital business transformation processes. For every user who engages with a chatbot online to resolve an issue, there is another who prefers to engage with a human. Reducing the cost of customer service will require speech-enabled virtual agents that can not only empathize with customers but also understand the lifetime value of a satisfied customer. That virtual agent also needs to be sensitive to the fact that continually upselling individuals with a limited income will create a political backlash once enough customers complain to their local government representative.

It may be a while before AI is pervasively applied, but machine learning algorithms are already being employed in ways that are raising concerns from the local statehouse to capitals around the world. Organizations employing AI models will ultimately need to provide more transparency into how those AI models are trained, especially as more people understand that AI is at its core an instance of complex mathematics that can be gamed to favor one outcome over another.


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