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1. DPI conquers encrypted traffic 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.

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2. Powering network analytics with machine learning & AI

   From energy grids to advanced smart cities, from space travel to military missions: data-dependent industry verticals need real-time network traffic analytics to manage the growing number of encrypted applications and services. In this article, we discuss the integration of artificial intelligence (AI) and machine learning (ML) into network analytics, with a particular focus on the challenges posed by encryption and how these technologies improve visibility and understanding of network traffic. Explore the essential shift to next-gen DPI for a compelling journey in network analytics.

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3. 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

4. Using AI-based deep packet inspection to power AI-driven networks

   In traffic management, AI-powered predictive capabilities enable networking devices to align rules and policies to the future state, ensuring virtually zero policy lags, while removing potential over-corrections that are typical in automation frameworks. This blog post examines how ipoque’s DPI technology and encrypted traffic intelligence enable AI-powered networks to deliver superior predictions and improved outcomes.

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5. How next-gen DPI addresses the shortcomings of SSL/TLS inspection

   Decryption using SSL/TLS inspection is admittedly the simplest method to address the loss of traffic visibility due to encryption. Deciphering the payload information provides all the prerequisite information at the packet level, allowing network administrators to manage and secure traffic flows effectively and efficiently. This article highlights the shortcomings of SSL/TLS. It discusses how next-gen DPI, equipped with encrypted traffic intelligence (ETI) addresses these limitations by combining advanced techniques such as machine learning, deep learning and advanced caching.

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6. TLS 1.3, ESNI, ECH and QUIC: Taming new age cryptography with DPI and AI/ML-based encrypted traffic intelligence

   Complex encryption protocols often lead to huge gaps in traffic visibility. This article explores the latest encryption protocols, such as TLS 1.3, DoX and ESNI, and how progressive erosion of traffic information, such as handshake and packet payload data, impact traditional DPI. It looks at how AI-based techniques, including machine learning and deep learning, tackle these protocols and why next-gen DPI is a must for modern networks.

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7. Building trust and security for 6G networks with DPI

   Distributed AI, intelligent edge and intelligent RAN are some of 6G’s prime characteristics. Managing 6G security requires deep packet inspection for real-time insights on new and emerging threat patterns arising from vulnerabilities of a new architecture, an expanded network surface and the rapid proliferation of end nodes. With DPI, operators can implement application-aware security policies for high-performant, reliable and trustable 6G networks.

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8. Powering next-gen firewalls with DPI and encrypted traffic intelligence

   In response to the challenges posed by advanced encryption protocols and increasing cybersecurity threats, LANCOM has integrated the AI-powered R&S®PACE 2 DPI engine into its next-gen firewalls. This enhancement enables real-time application filtering and advanced threat detection, even in encrypted traffic. As a result, LANCOM R&S®Unified Firewalls deliver improved visibility, security and performance for enterprise networks. Read our case study to find out how this partnership strengthens the network in versatile manners.

   Case Study

9. Whitepaper: Encrypted traffic visibility

   Encryption is rapidly becoming synonymous with network security and privacy. However, encryption presents challenges in the form of diminished network visibility and control which can be disruptive to networks that are highly reliant on deep network insights into managing and securing their data and assets. This whitepaper reviews encryption protocols, loss of traffic visibility and the associated adverse impact on network functionalities. It provides insights on how the incorporation of encypted traffic intelligence (ETI), including cutting-edge ML / DL techniques, circumvents the limitations associated with conventional deep packet inspection.

   Whitepaper

10. 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 [...]

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