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Static and dynamic analysis of events for threat detection


Be on top of your game - Static and dynamic analysis of events for threat detection

In 2017, an average of 200,000 new malware samples have been captured, each day. Cybercriminals have stepped up their game and are using advanced techniques to penetrate organization defenses. Therefore, cyber defense departments have to reinvent their defense mechanisms to keep up with the new threats. This evolving landscape of threats demands innovation.

On this talk we plan to present a data analytics platform for threat detection. We will discuss some of the underlying challenges, the key components and techniques that we used. These include a fully featured correlation engine built using Flink, Kafka and Redis, and the employment of machine learning to detect sophisticated threats.

Speaker Bio

Pedro Chaves

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Cyber Security Professional @ Siemens

Topics: SIEM \ Security \ Distributed Systems \ Stream Processing \ Open Source \ Data-Driven Apps Tools & Languages: Java \ Maven \ Git \ SQL \ Python \ Linux

Carlos Cunha Rodrigues

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Data Scientist | Lead Cloud Engineer | AWS @ Siemens

I am a highly self-motivated person with a deep interest in Tech and Security. I have been working between Lisbon and London helping costumers from different industries. My fields of expertise are AI/ML, Cloud Computing (AWS) and Serverless Architecture.

As an open source user and supporter, I firmly believe that sharing is a must and the way to go since this is what enables the companies and the world to move at this fast-growing pace.


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