The Cyber Defence (CYD) Campus of armasuisse Science and Technology and the Swiss Federal Institute of Technology in Lausanne (EPFL) are jointly launching a talent programme for research and training in the field of cyber defence. These Cyber Defence Fellowships are open to researchers at master, PhD and postdoc level.
More efficient defence against cyber attacks based on machine learning – the Cyber Defence Campus is showing the first results. This is thanks to the close connection with the basic research at the ETH Zurich and the operative cyber organisational units of the Swiss Armed Forces.
How are growing megacities, increased mobility, faster information exchange and ever newer communication channels changing the development of future armed forces? The research program “Technology Forecasting” is dedicated to this and other topics in the latest DEFTECH publication on the subject of «Urbanity».
Military vehicle platforms today consist of a variety of subsystems that need to be compatible with each other. armasuisse S+T is actively involved in setting up the «NATO Generic Vehicle Architecture» implementation standard. This ensures the interoperability as well as a cost-effective integration of electronic subsystems on military platforms.
The Cyber Defence Campus is presenting itself together with Swisstech at the «Consumer Technology Association (CES) - Conference 2020» in Las Vegas. The president of ETH Zürich, Prof. Dr. Joël Mesot and the president of EPFL, Prof. Dr. Martin Vetterli are also attending the conference.
Eleven international teams competed against each other for the first time in the DARPA Robotic Challenge in summer 2019. Their robots duelled their skills in mapping tunnels and recognising artefacts. A Swiss team represented by the ETH Zurich and an SME, with a walking robot from armasuisse, were present.
Is the Swiss Innovation System for National Security ready for the future? This question was discussed at the Deftech Day in Thun based on various different perspectives and experiences on November 13, 2019.
armasuisse S+T was able to successfully test the experimental system SAMURAI (Swiss African Multistatic Radar Initiative) together with the research partners CSIR (Council for Scientific and Industrial Research) from Pretoria, South Africa and Palindrome Remote Sensing GmbH from Landquart.
During the image analysis process, machine-learning (ML) methods are used as standard for automatic image classification and feature recognition. These methods attempt to group image-specific characteristics in a training data set and assign predetermined classes (e.g. «landscape», «dog» and «person») in order to generalise new images.
With the current density of communication media and radar, the question arises as to
whether the two formats are compatible with one another. This issue is compounded
by the fact that some devices use similar frequencies.
