The ipoque blog

Beyond speed: building intelligent and optimized private 5G networks with DPI

Private 5G networks promise secure, seamless access to enterprise assets onsite and offsite — but what happens when performance dips or threats go undetected? From disrupted operations to data loss and poor user experience, the stakes are high. That’s where deep packet inspection (DPI) steps in — giving enterprises the visibility they need to detect hidden gaps, before these impact the network. 

Q-Day ready: Building quantum-resistant networks with deep packet inspection

Quantum computers threaten to break RSA and ECDH, exposing years of encrypted traffic to "harvest now, decrypt later" attacks. Deep packet inspection (DPI) delivers the visibility needed to spot ciphertext manipulation, hidden malware, and PQC implementation flaws in real time. Discover how ipoque’s DPI engines, R&S®PACE2 and R&S®vPACE, strengthen quantum‑resistant networks and protect cryptographic keys. 

Comparing DPI and flow-based analysis for network traffic insights

This article compares deep packet inspection (DPI) and flow-based analysis. Benefits of DPI such as granular, real-time application and threat awareness are compared with metadata-driven insights produced in flow-based analysis. Other evaluation criteria such as form factors, deployment complexities and standardization requirements are also discussed to ascertain how each analysis type fits different use cases and networking environments.

How first packet classification drives application performance and security

This article explores the importance of first packet classification (FPC), as an enhancement to deep packet inspection (DPI), in handling URLLC and bandwidth-intensive applications, as well as critical apps used for enterprises, financial transactions and IoT. Apart from enhancing application performance and security, FPC’s instant traffic awareness drives application-based policies and accurate diagnostics for next-gen intelligent networks.

Profinet, DNP3, Modbus and BACnet: Using DPI to decode IIoT traffic

Devil’s Ivy is a chain attack that targets IIoT devices with the aim of infiltrating enterprise networks. Current operational technology (OT) protocols leave IIoT devices vulnerable to such attacks and many other forms of emerging cyber threats. Also, in IIoT, slight lags in the application or cloud performance and minor latencies in last-mile networks can massively impair machines and equipment ground performance. However, these issues can remain undetected for months or even years. DPI tools help in fortifying IIoT networks and securing enterprise production environments

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.

Keeping containers and pods safe in the cloud: How network visibility helps

The architecture of microservices often results in an expanded attack surface of cloud-native applications. However, security risks and vulnerabilities inherent in container environments can be mitigated using real-time packet visibility. Find out more about the role of deep packet inspection (DPI) for container network security in the context of microservices and cloud-native applications.