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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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Data technologies
Data technologies support automated extraction, classification, analysis, presentation and encryption of (big) datasets, including text, images, video and audio. Year by year, humans and machines generate an increasing amount of data. To control and obtain benefit from data, companies and governments need adequate technologies. Data technologies such as Big Data Analysis/Data Science, Video/Image analysis & recognition, Speech and text recognition and Encryption are specific for data, but also Artificial Intelligence, Machine Learning and algorithms are used to manage the data sets.
Data technologies are used for a wide variety of activities, for example to support decision-making processes, discover business insights, improve digital marketing and analyse behaviour of humans or machines. The types of deployment are endless: speech recognition used in automated assistants, video analysis by self-driving cars, data science for drug treatments, pattern recogniton for healing patients and predictive analysis for crime fighting. To protect the data and limit access, all sorts of encryption technologies are used next to Identity & Access management. The data technology ecosystem is continuously growing and new technologies come into the picture very rapidly. Collecting the right data and building the right model to interpret it are continued challenges, but also the acceptance of automated decision making, facial recognition, continuous data collection and access to data raise moral and ethical questions.
Related keywords: big data, Artificial Intelligence, DataTech, machine learning, algorithms, IoT, natural language processing, business intelligence, predictive analysis.
Data technologies support automated extraction, classification, analysis, presentation and encryption of (big) datasets, including text, images, video and audio. Year by year, humans and machines generate an increasing amount of data. To control and obtain benefit from data, companies and governments need adequate technologies. Data technologies such as Big Data Analysis/Data Science, Video/Image analysis & recognition, Speech and text recognition and Encryption are specific for data, but also Artificial Intelligence, Machine Learning and algorithms are used to manage the data sets.
Data technologies are used for a wide variety of activities, for example to support decision-making processes, discover business insights, improve digital marketing and analyse behaviour of humans or machines. The types of deployment are endless: speech recognition used in automated assistants, video analysis by self-driving cars, data science for drug treatments, pattern recogniton for healing patients and predictive analysis for crime fighting. To protect the data and limit access, all sorts of encryption technologies are used next to Identity & Access management. The data technology ecosystem is continuously growing and new technologies come into the picture very rapidly. Collecting the right data and building the right model to interpret it are continued challenges, but also the acceptance of automated decision making, facial recognition, continuous data collection and access to data raise moral and ethical questions.
Related keywords: big data, Artificial Intelligence, DataTech, machine learning, algorithms, IoT, natural language processing, business intelligence, predictive analysis.
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