Izvorni znanstveni članak
https://doi.org/10.37458/nstf.23.1.1
Analytic Black Holes: a data-oriented perspective
Giliam de Valk
Sažetak
In Analytic Black Holes it is advocated to start a new, second, revolution in security and intelligence analysis. After the first revolution, which started in the Netherlands as late as 2006 with the massive training in Structured Analytic Techniques at both the academia and at the MoD (e.g. Defense Intelligence and Security Institute).
A new second revolution – that of Augmented Intelligence – is at hand as a result of two developments, the change in data flows and the need for new products. Data are exploding, especially unstructured data. But the majority of the data remains unused in analyses. Furthermore, hybrid threats and real time intelligence for the protection of the critical infrastructure demand a new approach towards analysis. This gap needs to be filled, among others, by data science cells that can process data automatically. This way, a new analytic approach can be reached – that of Augmented Intelligence – in which humans and machines are paired in the analytic process.
Human Analysis is likely to develop more to-wards to limit the number of data taken into account, but those data will have a high causal significance. Machine Analysis, on the other hand, will process huge amount of data and focus on correlations in the first place. Augmented Intelligence, will be a merger of both, that can manifest itself by different combinations of both. It will deal with data that now re-main unused. It can fill the gap of the identified analytic black holes. Dealing with the analytic black holes will enhance the security, and make us more effective in protecting our critical infrastructure.
Ključne riječi
Hrčak ID:
272049
URI
Datum izdavanja:
7.2.2022.
Posjeta: 543 *