Can We Recognize Users Without Cookies or Local Storage?

User Recognition without Cookies or Local Storage

Introduction

This article explores the possibility of detecting the same user without using cookies or local storage, considering the following limitations:

• Cookies can be deleted.
• IP addresses can change.
• Browsers can change.
• Browser cache may be deleted.

Challenges

Identifying a user uniquely without identifiers involves matching random data from the user's device. However, this data can be unreliable and subject to change.

Methods for Data Collection

To create a data profile for user recognition, consider the following elements:

• IP Address (real and proxy)
• HTTP, session, and third-party cookies
• Flash cookies
• Web bugs (PDF, Flash, Java)
• Browsers (click tracking, fingerprinting)
• HTML5 and JavaScript (local storage, geolocation, etc.)

Data Analysis and Identification

• Fuzzy Logic/Neural Networks: Train a system to recognize users based on combinations of data.
• Probabilistic Analysis: Calculate the probability of a specific data profile belonging to a known user.
• Scoring Algorithm: Award points for exact data matches and deduct points for mismatches.

Proof of Concept

A Perceptron-based RNA model can be used to classify and identify users based on data profiles.

Additional Considerations

• Store all possible information about each user (IP, cookies, etc.).
• Use importance weights to resolve conflicts between data points.
• Generate RNA values and labels from collected data.
• Train the Perceptron to classify unknown users based on known users' patterns.

Sample Output

The code implementation can generate output indicating possible matches for an unknown user, ranked by score and difference.

Conclusion

Identifying users without cookies or local storage requires a comprehensive approach involving data collection, analysis, and probabilistic methods. Artificial Neural Networks and scoring algorithms provide promising solutions for this challenging task.

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