DATAFOG
Smart noise, safer you.
The problem DATAFOG solves
The Problem It Solves
- In today’s digital world, every click, search, and scroll is tracked by advertisers, data brokers, and malicious websites. Most privacy tools only block trackers, but they don’t hide behavioral patterns that can still reveal who you are.
- DataFog solves this by creating AI-generated fake browsing activity — confusing trackers and protecting your true digital footprint.
People can use it to:
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Mask their real browsing behavior from data collectors.
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Improve online anonymity and protect sensitive activities.
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Test websites safely without revealing identity or personal data.
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Make their daily browsing safer, smarter, and tracker-resistant.
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By blending real and fake signals, DataFog makes privacy active, not passive.
Challenges we ran into
Challenges I Ran Into
While building DataFog, the biggest challenges were:
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Manifest V3 restrictions: Chrome’s new extension system limited background scripts. I solved this using Service Workers for async task handling.
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Simulating realistic behavior: Early versions of the AI created repetitive patterns. I integrated Markov Chains and added random delays to make browsing more natural.
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Security sandboxing: Injected scripts needed to be safe from website interference. I solved this by using content script isolation and Chrome’s Content Security Policy (CSP).
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Overcoming these hurdles made the system robust, private, and future-ready.
Tracks Applied (1)
Digital Safety & Privacy
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