We have not yet reached this goal
“Supervised learning” is the term currently used for the AI offered on the cybersecurity market. This means that a learning algorithm tries to find a hypothesis that makes predictions that are as accurate as possible. The hypothesis is an image that assigns the assumed output value to each input value, for example whether a code contains malware or not. To do this, the algorithm needs many data sets from which it learns the desired “laws” and can then apply them to other data. The core prerequisite for this type of intelligence: the set of sample data is good. On the one hand, malware-free data must indeed be “clean”, otherwise AI doesn’t see abnormal data points. On the other hand, care must be taken to ensure that cyber attackers cannot gain access to the “training data”, since they could switch malware and malware-free code, thereby outwitting the system.
In IT development, machine learning is the next step in generating “artificial” knowledge from experience: an artificial system learns from examples and can generalise them once it has completed the learning phase. The examples are not simply memorised, but rather the system “recognises” patterns and laws in the learning data. This means that the system can also assess unknown data through the transfer of learning or even fail to learn unknown data due to overadaptation.
Initial successes have been achieved, for example in one of the largest competence centres for research into automated IT risk identification: the team at RadarServices puts these directly into practice with its customers. However, the experts also remain realistic: “We prefer to stay on the safe side and test our algorithms over a longer period of time before using them as the only analysis tool – without expert involvement,” says Christian Polster, who is responsible for research and technology development at RadarServices.
The computer scientist Donald Knuth summed up the status quo in this way: “Artificial Intelligence does everything that requires thought, but fails to do what humans and animals do automatically without thinking.”