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- Trend snippet: Underinvestment in support (knowledge, guidance, research investment) and incentives (market forces, regulation) for developing emerging technologies securely
Trends in Security Information
The HSD Trendmonitor is designed to provide access to relevant content on various subjects in the safety and security domain, to identify relevant developments and to connect knowledge and organisations. The safety and security domain encompasses a vast number of subjects. Four relevant taxonomies (type of threat or opportunity, victim, source of threat and domain of application) have been constructed in order to visualize all of these subjects. The taxonomies and related category descriptions have been carefully composed according to other taxonomies, European and international standards and our own expertise.
In order to identify safety and security related trends, relevant reports and HSD news articles are continuously scanned, analysed and classified by hand according to the four taxonomies. This results in a wide array of observations, which we call ‘Trend Snippets’. Multiple Trend Snippets combined can provide insights into safety and security trends. The size of the circles shows the relative weight of the topic, the filters can be used to further select the most relevant content for you. If you have an addition, question or remark, drop us a line at info@securitydelta.nl.
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Underinvestment in support (knowledge, guidance, research investment) and incentives (market forces, regulation) for developing emerging technologies securely
Security is not being considered an integral component of technology innovations. This means it is likely that technologies will be developed with little or no consideration for malicious threats, as has happened in the past. Without the right incentives to prevent this, there is a risk of insufficient security functionality and later costly retrofit. Further, the complexity of supply chains and systems may mean that innovators will make false assumptions about the security inherent in the systems upon which their solutions are layered, causing hidden risk. This hidden risk may also manifest where organizations exploit machine learning without an ability to determine the integrity of and absence of bias in the algorithms.