Collective intelligence is artificial intelligence

A problem big enough for AI and swarm intelligence ’to solve

Are we about to deliver on the promise of artificial intelligence (AI)? In his speech at Slush 2019, Mikko Hyppönen, Chief Research Officer of F-Secure, showed that significant advances in the use of artificial intelligence are possible if one applies inhuman thinking to machine learning.

Mikko recalled an article in a Finnish technology magazine that the time for AI-like technology was “just around the corner”.

These words were published in April 1983.

Today, machine learning and artificial intelligence are advancing faster than ever. However, the discussion about AI still largely revolves around what Mikko called the cliché of “superhuman intelligence” - computers that think or act like humans, but in superhuman ways.

"Maybe that's not the real way to think about it that way," he said. "Maybe we can do better."

Project Blackfin is a new project from F-Secure. It aims to rethink the possibilities of artificial intelligence by using collective intelligence that could mimic superhuman abilities represented by the cooperative behavior of animals such as schools of fish, flocks of birds or colonies of ants.

Mikko suggested that we could use this "swarm intelligence" to solve the bigger problems of security on earth and in cyberspace.

Pretty big problem

"If we do our job right, it stays invisible," said Mikko, comparing computer security on a global scale with the classic video game Tetris. "Your successes disappear, but your failures pile up."

Unfortunately, the possibilities of failure are almost infinite. Cybersecurity professionals “face massive amounts of attacks, millions of malware samples, millions of attacks”. Fighting cybercrime on this scale represents a massive technological challenge for people and companies.

Mikko quoted Gustav Söderström, Spotify’s chief R&D officer at Slush, who said, “You have to have a pretty big problem for artificial intelligence to make sense as a solution.

Computer security, according to Mikko, is “a pretty big problem”.

The wisdom of the swarm

F-Secure first applied machine learning to cybersecurity in 2005. "We didn't call it 'artificial intelligence' because we're Finns," said Mikko. "We called it something much more boring."

The way this company, and cybersecurity companies in general, have used machine learning is to correlate and compare data collected from a large number of endpoints.

“When we take advantage of these new swarm intelligence capabilities, and when we add the intelligence within what is known as an agent, more complicated behaviors and more complex capabilities emerge.

He points out that the use of this technology could be useful in several areas. This includes logistics, energy and of course cybersecurity.

“And then we add things like federal learning mechanisms to agent-based learning. Then it's not just about the intelligence of a single agent. "

The network connection enabled the agents to exchange data to improve decision-making. If the agents can connect to the cloud, the shared data can further increase the effectiveness of the swarm. However, Internet access, which may not be available for various reasons, including a malware attack, is not necessary.

“Federated learning mechanisms work better with network connections. But it doesn't need them, ”said Mikko. “Alone is good. Together they are even better. "

The future is now

F-Secure already uses swarm intelligence in the Rapid Detection & Response Service solution.

“We have already prevented mechanisms from reporting false positives,” said Mikko.

With the massive shortage of cyber security professionals and the incessant rise of increasingly advanced attacks, anything that can help focus resources on the real and pressing issues is beneficial for businesses.

“It already works. And that is the beginning of a multi-year project. "