Various sources and types of data are available, be it through social networks, the Internet of Things or public databases. All of this data offers new possibilities, but requires different methods of acquisition, having to consider the veracity and spatio-temporal aspects of the data. The new approaches based on participatory platforms or open sources are very promising.

In terms of operational conduct, it is imperative to have the right information with good quality and at the right time. Expertise is being developed in order to be able to evaluate information systems and modern infrastructures, taking into account the increasing quantity of data (big data problematic), its speed and heterogeneity.

Algorithms based on machine learning are being reviewed in order to identify patterns and the recurrences across data sets. These activities have a wide range of potential applications such as detecting anomalies, classifying signals, texts, languages and images as well as analysing graphs.

Nowadays, data forms the basis of operational decisions. It is therefore necessary to ensure that it is not manipulated by adversaries, and that the decision models are robust in the face of attacks. In addition, the protection of personal data from persons and institutions must be guaranteed against fraudulent use.

The evaluation of information procured from social networks poses new technical and analytical challenges. Using a demonstrator, armasuisse S+T examines the new processes and technologies for researching information, as well as analysing and visualising data from social networks, and presents it in a simple manner.

Translation tools are very widespread today. However, they involve numerous risks as they all depend on an Internet connection and do not permit translation of classified information. armasuisse S+T has trained its own independent translation models which can be optimised for particular syntax and vocabulary (social networks or organised crime).

Conflict anticipation can provide a major tactical advantage in the application of a peace strategy and a political negotiation. Thanks to various sources of public data (social networks and media), armasuisse S+T has developed algorithms capable of identifying that a country is at a turning point in terms of political stability and that a revolution or armed conflict are foreseeable.

The Internet of Things is a paradigm which enables data to be collected from sensors in a distributed manner. The deployment and maintenance of these sensors, however, pose major logistical challenges. armasuisse S+T is examining the possibility of using data coming from participatory platforms (crowdsensing), taking into account the challenges related to the security and authenticity of the information.