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1. Will encryption and regulation obsolete DPI?

   The ongoing importance of network visibility stimulates more and more discussions whether encryption and increasing regulation will make DPI obsolete. Nevertheless, DPI remains important despite increasing encryption, especially for network visibility, security measures and resource allocation. Encrypted traffic intelligence (ETI) can complement DPI to restore visibility into encrypted network traffic. It combines advanced DPI with artificial intelligence and machine learning to gain insights into the encrypted data traffic.

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2. The impact of encryption and AI on open source in DPI: challenges and opportunities

   The rise of encryption protocols is transforming network security, presenting both challenges and opportunities for open-source deep packet inspection (DPI) solutions. While open-source DPI excels at handling common encryption methods, it struggles with newer techniques, as well as anonymization and obfuscation strategies. The growing reliance on AI and machine learning in commercial DPI products offers a potential path forward, but open-source projects face obstacles in integrating these technologies due to challenges around data privacy, training, and model sharing.

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3. Is DPI still relevant in the age of encryption?

   Deep packet inspection, a staple for real-time network analytics, is very much dependent on packet readability. Unfortunately, as more and more IP networks and applications start using advanced encryption protocols, the resulting visibility gaps raise questions about the efficacy and the relevance of DPI in delivering accurate traffic analysis at the packet and flow level. Read this article to learn more about the growing need for encrypted traffic intelligence and the demand for next-gen DPI featuring advanced inspection techniques such as machine learning and deep learning.

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4. Encryption and emerging application complexities challenge open-source DPI efficiency, Rohde & Schwarz report reveals

   Leipzig, Germany, May 30, 2024 — ipoque, a Rohde & Schwarz company and a leading provider of next-gen deep packet inspection (DPI) software, today unveiled key findings from its latest research report ‘State of open-source DPI: challenges, opportunities and alternatives’.

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5. The downside to decryption and why you need encrypted traffic intelligence

   Often, networks run millions of decryption and re-encryption loops that come with various security, latency and performance implications. In our latest blog, we discuss the downside of decryption in traffic analysis, and how ipoque’s encrypted traffic intelligence (ETI) can be used to tackle even the most stringent encryption protocols without decrypting a single packet!

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6. DPI and VPNs: It's obfuscated...

   Virtual private networks (VPN), such as Psiphon, TOR and NordVPN, use various obfuscation techniques, including encryption and dynamic IP addresses, to ensure the security and privacy of data. The same techniques, inadvertently, create huge blind spots in network monitoring, leaving the network open to attacks and abuse. This article assesses how next-gen DPI by ipoque, via a rich repository of VPN signatures, identify VPN services and deliver application and threat awareness.

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7. QUIC: How DPI with encrypted traffic intelligence supports the web’s latest protocol

   QUIC is a network layer protocol that uses the UDP protocol and TLS-based encryption to deliver web traffic between devices. This article discusses the visibility challenges introduced by QUIC and the impact of this on traffic management and security. It also assesses how deep packet inspection (DPI) with encrypted traffic intelligence (ETI) addresses these challenges and powers networking and cybersecurity tools against the rapid growth of QUIC traffic.

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8. 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

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9. 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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10. Cryptocurrency and DPI: Unearthing threats in the blockchain world

    Crypto transactions can significantly strain modern networks given their growth, intensity and susceptibility to mass-scale attacks. Also, using encryption to anonymize cryptocurrency transactions creates huge gaps in traffic observability. Find out how the capabilities of DPI in identifying crypto protocols and applications help network operators and security vendors secure networks and devices while protecting the platforms transacting and storing cryptocurrencies.

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