Open Source Intelligence and OSINT Applications
Tuominen, Sanna (2019)
Tuominen, Sanna
2019
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2019052812391
https://urn.fi/URN:NBN:fi:amk-2019052812391
Tiivistelmä
Emerge of the Internet as a global platform for sharing and exchanging information world-wide has increased exponentially the amount of publicly available data. Open source intelligence [OSINT] aims at addressing specific intelligence requirements utilizing this data. Open source intelligence is traditionally associated with military intelligence, yet users of OSINT today are ranging from governments to businesses and regular citizens. The objective of this thesis was to study what open source intelligence is and demonstrate the use of selected OSINT tools.
In the theory sections, this thesis considered the current state of OSINT and evaluated its future. The popularity of OSINT is increasing, and the usage of OSINT is expanding into new arenas. The main challenge with OSINT is the trouble of finding the meaningful bits from massive data amounts. Hence, this thesis introduced and demonstrated three OSINT solutions displaying the nature and the differing attributes of the selected OSINT solutions. The study of the solutions was conducted as a demonstration assessment, where the use and the results of selected OSINT solutions were recorded and observed.
The thesis findings show that the range of OSINT solutions is wide and scattered. The method of providing the results from OSINT data searches vary significantly between solutions. Combining data from different OSINT solutions for a comprehensive overview and analysis requires effort and use of multiple disjointed solutions while lacking automation.
The visualization of the findings is predicted as a future trend for the development of the OSINT solutions. Individuals’ skills for data searches and processing is another trend to put focus on, whether it is for the ability to utilize the available OSINT solutions more efficiently or for an ability to develop more sophisticated OSINT solutions in the future.
In the theory sections, this thesis considered the current state of OSINT and evaluated its future. The popularity of OSINT is increasing, and the usage of OSINT is expanding into new arenas. The main challenge with OSINT is the trouble of finding the meaningful bits from massive data amounts. Hence, this thesis introduced and demonstrated three OSINT solutions displaying the nature and the differing attributes of the selected OSINT solutions. The study of the solutions was conducted as a demonstration assessment, where the use and the results of selected OSINT solutions were recorded and observed.
The thesis findings show that the range of OSINT solutions is wide and scattered. The method of providing the results from OSINT data searches vary significantly between solutions. Combining data from different OSINT solutions for a comprehensive overview and analysis requires effort and use of multiple disjointed solutions while lacking automation.
The visualization of the findings is predicted as a future trend for the development of the OSINT solutions. Individuals’ skills for data searches and processing is another trend to put focus on, whether it is for the ability to utilize the available OSINT solutions more efficiently or for an ability to develop more sophisticated OSINT solutions in the future.