Use of network analysis techniques to prevent data loss (Q10660): Difference between revisions
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(Removed claim: summary (P836): The network flow analysis technologies are now highly developed and primarily serve the purpose of external security — the detection of malware, botnets or hacking. These procedures are often based on advanced statistical models. The procedures to prevent the loss of data work do not work over the network records, but the work and movement of files at the firm. The objective is to verify that network analysis techniques cannot be modified to d...) |
(Created claim: summary (P836): Network flow analysis technology is currently highly developed and serves primarily for external security – detection of malware, botnets or hacker attacks. These procedures are often based on advanced statistical models. Procedures aimed at preventing data loss work not over network records, but on the work and movement of files in the company. The aim is to verify whether network analysis techniques cannot be modified to detect non-standard da...) |
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Network flow analysis technology is currently highly developed and serves primarily for external security – detection of malware, botnets or hacker attacks. These procedures are often based on advanced statistical models. Procedures aimed at preventing data loss work not over network records, but on the work and movement of files in the company. The aim is to verify whether network analysis techniques cannot be modified to detect non-standard data work to identify data security risks. a. (English) | |||||||||||||||
| Property / summary: Network flow analysis technology is currently highly developed and serves primarily for external security – detection of malware, botnets or hacker attacks. These procedures are often based on advanced statistical models. Procedures aimed at preventing data loss work not over network records, but on the work and movement of files in the company. The aim is to verify whether network analysis techniques cannot be modified to detect non-standard data work to identify data security risks. a. (English) / rank | |||||||||||||||
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| Property / summary: Network flow analysis technology is currently highly developed and serves primarily for external security – detection of malware, botnets or hacker attacks. These procedures are often based on advanced statistical models. Procedures aimed at preventing data loss work not over network records, but on the work and movement of files in the company. The aim is to verify whether network analysis techniques cannot be modified to detect non-standard data work to identify data security risks. a. (English) / qualifier | |||||||||||||||
point in time: 22 October 2020
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Revision as of 15:18, 22 October 2020
Project in Czech Republic financed by DG Regio
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Use of network analysis techniques to prevent data loss |
Project in Czech Republic financed by DG Regio |
Statements
247,499.87 Czech koruna
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329,999.83 Czech koruna
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75.0 percent
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28 April 2017
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30 November 2017
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1 December 2017
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Safetica Services s.r.o.
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50°5'7.19"N, 14°27'56.48"E
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13000
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Technologie analýzy síťového toku je v dnešní době velmi rozvinutá a slouží primárně k externí bezpečnosti - odhalování malware, botnetů či útoků hackerů. Tyto postupy jsou často založeny na pokročilých statistických modelech. Postupy zaměřené na prevenci ztráty dat pracují nepracují nad záznamy o síti, ale o práci a pohybu souborů ve firmě. Cílem je ověřit, zda nelze upravit techniky síťové analýzy tak, aby odhalovany nestandardní práci s daty a identifikovali tak datová bezpečnostní rizika. a. (Czech)
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Network flow analysis technology is currently highly developed and serves primarily for external security – detection of malware, botnets or hacker attacks. These procedures are often based on advanced statistical models. Procedures aimed at preventing data loss work not over network records, but on the work and movement of files in the company. The aim is to verify whether network analysis techniques cannot be modified to detect non-standard data work to identify data security risks. a. (English)
22 October 2020
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Identifiers
CZ.01.1.02/0.0/0.0/16_045/0009614
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