The cybersecurity company F-Secure has recently created a new AI project that utilizes techniques inspired by “swarm-intelligence”. As AI News reports, F-Secure’s new AI approach makes use of many decentralized AI agents that all collaborate in order to carry out accomplish specific goals.
F-Secure’s new swarm AI is similar in concept to Fetch AI’s earlier take on decentralized AI systems, which have been applied to IoT concepts. However, unlike Fetch AI, F-Secure is aiming to take the concept of decentralized AI and use it in the cybersecurity domain. Specifically, F-Secure is aiming to improve the company’s detection and response capabilities.
As explained by Matti Aksela, the VP of AI at F-Secure, it is commonly believed that AI should aim to copy human intelligence. However, while patterning AI systems after human reasoning and behavior isn’t inherently bad, Aksela explained to AI-News that only patterning AI after human cognition is limiting what we can do with AI. Aksela explained that we can look outside of human cognition and explore other methods of organizing and architecturing AI. A wider range of possible models for AI can augment what people can already accomplish with AI.
Swarm intelligence is a behavior of decentralized systems. It’s a collective behavior that manifests itself in both artificial and natural systems. In terms of biological systems, swarm intelligence is often seen in large colonies of organisms like ants, bees, fish, and birds. For instance, many birds migrate in large flocks and as the flock travels it maintains a consistent formation that fluctuates very little, with the birds only deviating a few inches from one another in their formation. It is thought that flying in such formations reduces the energy that the birds require to fly.
Swarm intelligence has been used for probabilistic routing in telecommunication networks and in the creation of microbots. One example of this concept is the tiny robots created by MicroFactory. The robots are controlled by a circuit board that generates a magnetic field, and the robots themselves are magnets. The robots are also equipped with small manipulation tools that they can use to interact with the environment around them and manipulate objects.
The development of genuinely human-like artificial intelligence, or Artificial General Intelligence, will take some time to be created. Estimates by various AI experts vary, but on average it is thought that it will take around 50 years to succeed in the creation of an AGI. In contrast, the development of distributed autonomous agents like the ones F-Secure should take a significantly shorter time.
According to F-Secure, several years more years of development will be needed to for their distributed intelligence architecture to reach its full potential, but some mechanisms based on the swarm-intelligence model are already in use. F-Scale has used some swarm-intelligence techniques to detect breaches and engineer solutions.
F-Secure’s AI agents are capable of communicating with each other and collaborating.
Swarm intelligence techniques make use of the talents or capabilities of individual agents in the agent pool, and when these skills are networked together there is a robust and flexible system capable of carrying out complex tasks.
“Essentially, you’ll have a colony of fast local AIs adapting to their own environment while working together, instead of one big AI making decisions for everyone,” Aksela explained.
In the specific case of F-Secure the different agents are capable of learning from different networks and hosts, and the agents can thread spread this knowledge through the wider network which joins together different organizations. F-Secure says one of the main benefits of this approach is that it can enable the organization to share sensitive information via the cloud and still remain protected due to superior break and attack detection.