Search results

1. Winning the game of truth with network traffic classification accuracy powered by DPI

   As networks move towards automation, AI-based techniques such as machine learning (ML) and deep learning (DL) are employed by new architectures such as SDN to invoke and control network functions autonomously. This automation, however, hinges on both real-time traffic inputs as well as past data on protocols, applications and service types. The more accurate past classification data is, the more meaningful the algorithms and features defined in the AI systems will be. This leads to improved network responses and a higher predictive capability across networks.

   Blog post

2. 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

3. DPI-driven application and protocol classification

   As the internet is at the center of more and more business, application awareness will be needed even more to enable optimal distribution of network content. New and intensified security threats will emerge as business and commerce virtualize. This article discusses how an advanced DPI engine featuring port-based matching, pattern matching and encrypted traffic intelligence can enhance the monitoring performance, security and monetization of networks.

   Blog post

4. How advanced traffic identification complements honeypot networks

   Honeypot networks are fake IT systems used to bait cyberattackers, learn from them and consequently improve actual cybersecurity. They are designed with a well-placed vulnerability to attract hackers. Once a hacker is in the network, the honeypot allows for monitoring and analyzing the malicious activity. For such networks, deep packet inspection is a great asset. It identifies malicious activity almost instantaneously, helping honeypot networks to detect threats as soon as they enter the network.

   Blog post

5. Behind the scenes: How quality assurance drives the DPI technology of ipoque

   Quality assurance (QA) plays a critical role in deep packet inspection (DPI), ensuring the highest level of classification accuracy and reliability. The rigorous QA processes of ipoque ensure that our DPI technology is continuously updated with the latest traffic signatures and provides the application awareness that is required to support a wide range of networking use cases.

   Blog post

6. 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

7. R&S®PACE 2: a lightweight DPI engine for big network performance gains

   Performance vs. cost – Why is having a small memory footprint important for DPI deployed in virtualized and containerized environments? This article discusses the implications of a DPI engine with a small memory footprint on network and application performance, across virtualized and containerized architectures as well as the network functions into which it is embedded.

   Blog post

8. Encrypted traffic intelligence for network traffic analysis

   Encryption greatly enhances the security and privacy of data. However, it introduces new challenges in terms of network monitoring and security, as it gives networks only limited visibility into the underlying traffic flows. To reinstate IP network traffic visibility, ipoque has enhanced its deep packet inspection technology with encrypted traffic intelligence (ETI) for accurate and highly reliable, real-time analysis of encrypted traffic. ETI complements ipoque’s market-leading traffic identification and classification methodologies and metadata extraction to deliver granular visibility for protocols, applications and services that are encrypted.

   Brochure

9. Whitepaper: DPI and 5G

   DPI’s granular classification capabilities help network operators manage an array of new applications and services introduced by 5G. Application awareness and detailed traffic analytics are key for various network services to support 5G's features, such as network slicing and edge computing. Deep packet inspection technology empowers real-time traffic classification, feeding information into the network to support the implementation of these advanced features.

   Whitepaper

10. 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.

    Blog post