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32 results for: "machine learning"


  1. DPI conquers traffic encryption with machine learning and deep learning

    Encryption keeps packets obscure and safe, but it also poses various visibility and monitoring challenges for network operators. In an encrypted world, how can they maintain accurate traffic visibility and classification for reliable threat detection and network management? The answer is Encrypted Traffic Intelligence (ETI). By incorporating machine learning and deep learning, the DPI engine R&S®PACE 2 is able to deliver this intelligence, providing application awareness for encrypted, obfuscated or anonymized traffic.

    Blog post Score: 22

  2. DPI-powered machine learning for network monitoring software

    Protecting your company’s information from data breaches is an ever-present security concern. Data breaches are all the more serious for small and medium companies who cannot afford a dedicated IT security team. oorigin® by Orsec Technologies incorporates the analytics capabilities of R&S®PACE 2 for a faster and more efficient detection of cyberthreats. Thus, Orsec Technologies is able to offer a high-class product at a price affordable for small and medium companies.

    Case Study Score: 14

  3. Orsec Technologies SAS embeds R&S®PACE 2

    "The content and metadata extracted from traffic flows by the DPI engine R&S®PACE 2 provides a rich information feed we use to boost our machine learning for user and device behavior analytics. This empowers our solution to [...]

    Success Story Score: 0

  4. First packet classification in an encrypted world

    As new encryption technologies proliferate, caching-based first packet classification used in DPI will become increasingly ineffective in identifying the underlying applications and services. As a result, there is an urgent need to develop advanced DPI methods, leveraging machine learning (ML) and deep learning (DL) to ensure applications and services are effectively and accurately identified

    Blog post Score: 0

  5. Rohde & Schwarz and Helmut Schmidt University Hamburg conduct joint research

    Leipzig, Germany – April 15, 2019 – ipoque GmbH, a Rohde & Schwarz company, today announced a strategic research partnership with Helmut Schmidt University in Hamburg to establish a program of exchange and collaboration. The R&S subsidiary provides market-leading network analytics solutions for more secure, reliable and efficient networks. The joint research will focus on artificial intelligence, machine learning and big data analytics and runs for 4 years.

    Press release Score: 0

  6. Orsec Technologies boosts next-generation intelligence solution with DPI by Rohde & Schwarz

    Leipzig, Germany – May 22, 2019 – ipoque GmbH, a Rohde & Schwarz company providing market-leading deep packet inspection (DPI) software, today announced that Orsec Technologies SAS has licensed its DPI engine R&S®PACE 2 for their cyber threat hunting solution oorigin®. Providing accurate traffic analytics and a rich set of metadata in real time, R&S®PACE 2 significantly strengthens Orsecs threat hunting capabilities. This allows for more accurate alerts, faster threat detection and enhanced machine learning.

    Press release Score: 0

  7. Rohde & Schwarz and Martin Luther University Halle-Wittenberg establish research partnership

    Leipzig, Germany – May 15, 2019 – ipoque GmbH, a Rohde & Schwarz company, today announced a strategic partnership with Martin Luther University Halle-Wittenberg to establish a joint research program. The R&S subsidiary provides market-leading network analytics solutions for more secure, reliable and efficient networks. The joint research with the Computer Science Institute of the MLU will focus on future technologies like big data analytics, machine learning or artificial intelligence and how they can boost network analytics. The project is intended to run for 4 years..

    Press release Score: 0

  8. Commercial vs open-source DPI: Does it matter?

    Commercial DPI takes traffic detection a notch higher via its ability to detect encrypted and obfuscated traffic. This inherently requires advanced methods such as statistical and behavioral analysis and machine learning, technologies that are not available in the open-source versions. This article debates the advantages of commercial vs. open-source DPI. While it shares the merits of both options, it highlights the reliability, superior performance, efficiency, security and service consistency provided by vendors of commercial DPI and how these qualities help network administrators and managers monitor and secure their networks more effectively.

    Blog post Score: 0

  9. R&S®PACE 2 - First packet classification

    First packet classification refers to the accurate and reliable classification of the very first packet of a flow, instead of waiting for at least 3 to 5 packets before the underlying application is identified. To enable first packet classification the advanced OEM DPI engine R&S®PACE 2 offers advanced caching techniques built on the intelligence developed from traditional DPI methods. This enables traffic policies to be meted out on the first packet itself, and implemented across all other ensuing packets for consistency, application-wide.

    Brochure Score: 0

  10. Product brochure R&S®PACE 2

    R&S®PACE 2 is a software library that uses different technologies – deep packet inspection, behavioral, heuristic and statistical analysis – to reliably detect network protocols and applications, even if they use advanced obfuscation and encryption techniques, and extract metadata in realtime. R&S®PACE 2 is used by network equipment and security vendors to enhance their products with state-of-the-art protocol and application awareness capabilities to deliver full visibility into IP-based network traffic.

    Brochure Score: 0