APT-Sweeper Identification of malware based on analysis of the transmission context of data streams

Date: 
01/01/2014 to 31/12/2017

Data streams always consist of information about the content of the message and context of the message (metadata, protocol data, time, etc.). Traditional approaches to identifying malware are based on an analysis of the content of incoming data streams. However, in many areas this procedure is only possible to a limited extent for reasons of data protection or fails because contents are protected against access in encrypted form. In the APT-Sweeper project, on the other hand, the transmission context is analyzed. Because the malware can be hidden in different components of the context, advanced machine learning techniques are combined with approaches to filtering complex data streams. Thus, both the context and the format-specific structure of content in the analysis can be taken into account. In addition, the recognition of alien content is possible without relying on extensive prior knowledge of past attacks.

Week: 
Tuesday, 11 December, 2018

News

PAPAYA: Platform for PrivAcY preserving data Analytics

PAPAYA: Platform for PrivAcY preserving data Analytics is one of the GDPR cluster projects that will help companies to follow a privacy-by-design approach & adopt #PrivacyEnhancingTechnologies to ensure their clients’ privacy is protected.

Future Events

Brussels - Second CW Concertation Meeting, 04/06/2019
04/06/2019
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Resilience. Deterrence. Defence – Calls to action for future cybersecurity and privacy policy
Concertation meeting of H2020 projects from unit "Cybersecurity & Privacy"

 

Join us at the second Cyberwatching.eu Concertation meeting, 04 June 2019!

Annual Privacy Forum 2019
13/06/2019 to 14/06/2019
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LOCATION: LUISS Guido Carli - Rome, Italy

The event encourages dialog with panel discussions and provides room for exchange of ideas in between scientific sessions. Participate to the discussions during APF days, but also by being involved online on our community channels using #APF19

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