Discover Emerging and Disruptive Technologies
Identify, monitor, analyze and forecast trends related to cybersecurity technologies
Data & Tools
Using diverse and reliable data sources is key to producing meaningful results. The Observatory seeks to identify high-quality datasets and apply various analytical tools to ensure robust, trustworthy research, providing valuable insights and supporting informed decision-making.
Publications
By publishing our findings and methods, we aim to contribute valuable knowledge and foster collaboration within the community. This open-access approach encourages the exchange of insights, allowing institutions to refine methods collectively, thereby enriching technological ecosystem.
Technology Trends
Emerging technologies like are transforming the world, bringing both risks and opportunities. It’s essential to work with public and private sectors, academia, and civil society to develop and adopt these technologies, set international standards for responsible use, and maintain a technological edge.
Cybersecurity Landscape
The Swiss National Cyberstrategy (NCS) recognizes cybersecurity research as vital for strengthening Switzerland’s defense against cyberthreats. While the current landscape is not fully understood, the goal of the Observatory is to create a comprehensive view of the ecosystem including academia, stratup and industry.
Building a community-driven and actionable Technology Intelligence for National Security, Market Research, and Strategic Management.
Part of the Swiss Technology Observatory community gathered in 2022 and 2024 in Sachseln (OW) to discuss current scientific challenges in technology monitoring and forecasting research.
Latest Publications
Monitoring Cybersecurity Technology Through the Years: a Technology Mining Approach Through Bibliometrics and Patent Analysis
Abstract: Cybersecurity is one of if not the most critical areas forsecurity for countries, institutes, and people today. Cyberattacks can disable any system, putting lives in danger. This paper investigates the research and development activity in this space....
Leveraging Pre-Trained Extreme Multi-Label Classifiers for Zero-Shot Learning
Abstract: Extreme multi-label (XML) classification involves assigning multiple labels to an instance from an extremely large set of possible labels. Despite its significance, zero-shot learning within the context of XML classification remains relatively understudied....
Follow the Path: Hierarchy-Aware Extreme Multi-Label Completion for Semantic Text Tagging
Abstract: Extreme Multi Label (XML) problems, and in particular XML completion -- the task of prediction the missing labels of an entity -- have attracted significant attention in the past few years. Most XML completion problems can organically leverage a label...