Entropy Redistribution Attacks

Understanding Entropy Redistribution

What Is It?

An Entropy Redistribution Attack is a technique for transforming the information content (or "entropy") distribution within a piece of text. The core idea is to analyze how much surprising information (measured as entropy in information theory) is carried by each sentence, then shuffle or reorganize that density so the text's flow and complexity feels more like human writing—and less like an output from an AI model.

Breaking Down Concepts

Information Entropy is a measure of unpredictability or complexity in data. For a text, sentences with high entropy introduce new ideas, complex vocabulary, or surprising facts; low entropy sentences repeat or elaborate on known information.

Redistribution means rearranging where that "surprise" or density occurs, so rather than clustering all high-entropy content together (like some AI outputs), the text mimics natural human rhythm—alternating dense, complex, and simple sentences.

Why It Matters

AI-generated text can be detected by statistical tools because it sometimes distributes information density differently than a human would—AI models may generate paragraph-long stretches of uniform entropy, whereas humans often mix in short, bland, or offbeat remarks between denser segments. Entropy redistribution attacks disrupt these statistical patterns, making detection harder.

Human vs. AI Entropy Distribution

AI-Generated Text

"Information entropy quantifies uncertainty. It is measured in bits. High entropy means more unpredictability. Low entropy means repetition."

This text exhibits uniform entropy distribution with consistent sentence complexity.

Humanized Text

"Information entropy, simply put, measures uncertainty. Sometimes, it's discussed in terms of bits—a detail technical audiences know well. That said, the more unpredictable something is, the higher its entropy, whereas repetition tends to lower it. Funny how jargon sneaks in, right?"

This version redistributes information density, mixing technical details with conversational asides.

How Entropy Redistribution Works

1. Analyze Original Text

Use information theory metrics to estimate entropy per sentence (e.g., how much "surprise" or novelty is present).

2. Shuffle Information Density

Rearrange, paraphrase, or expand sentences so that complex details are mixed with simple statements and tangents—matching typical human writing patterns.

3. Repeat or Anchor Key Ideas

Humans often return to main points or use uncommon phrases, further spreading entropy across the text.