In recent times, the debate surrounding Deep Packet Inspection (DPI) has agitated various sectors of society, from scientists to politicians. While some defend its usefulness in network and security management, others raise questions about its ethics and legality with regard to user privacy. In this blog, we will explore how Artificial Intelligence (AI) can offer a more ethical alternative for classifying network packets.

Network ratings and their usefulness

Network classification is a fundamental practice for understanding and managing the traffic that flows through a network infrastructure. By categorizing and identifying different types of traffic, organizations can implement security policies, optimize network performance, and prioritize critical applications.

What is DPI and how does it work?

DPI is a technique used by companies and service providers to analyze the content of data packets that travel on a network. It allows you to identify the type of traffic, applications used, and even inspect the content of the data, including texts, images, and videos.

The legality of DPI

The issue of the legality of IPR varies depending on the legislation of each country and the policies of the organizations that use it. While in some places its use is strictly regulated and limited to specific purposes, in others its implementation may be questionable in terms of ethics and privacy.

A frequently cited example is the case of China, where DPI is used to censor and filter content arbitrarily. Recently, there was an incident where an emblematic image of the “Heavenly Peace Square Massacre” was accessed through a maneuver that circumvented the filters, where users searched for “Big Yellow Duck” to view the blocked image.

In Brazil, the Internet Civil Framework, in its article 9, expressly prohibits blocking, monitoring, filtering, or analyzing the content of data packets, except in specific circumstances provided for by law.

Alternatives for using DPI in network classification

A promising alternative to conventional DPI is the application of AI algorithms for the classification of network packets. Instead of examining the content of the data, these algorithms analyze traffic patterns and behavior to identify applications and types of traffic, without compromising user privacy.

Machine learning techniques can be used to identify application usage patterns based on network packet metadata, such as source and destination ports, packet sizes, and communication patterns. This approach preserves user privacy while providing valuable information for network and security management.

Advantages of AI in classifying network packets:

● Preserved privacy: Unlike DPI, which analyzes data content, AI focuses only on metadata and traffic patterns, ensuring user privacy.

● Adaptability: AI models can be trained and continuously updated to adapt to new traffic patterns and emerging threats.

● Regulatory compliance: The AI approach to classifying network packets helps organizations comply with privacy and data protection regulations, reducing the risk of violations and penalties.