Update index.html

index.html

@@ -698,6 +698,44 @@
                         <p>Fine-tune the strength-quality trade-off based on your needs: subtle for sharing, aggressive for legal protection.</p>
                     </div>
                 </div>
+
+                <h3 style="margin-top: 50px; margin-bottom: 20px; font-size: 1.8em;">How We Compare to Other Methods</h3>
+                <table class="comparison-table">
+                    <thead>
+                        <tr>
+                            <th>Method</th>
+                            <th>Primary Goal</th>
+                            <th>Mechanism</th>
+                            <th>Key Differentiator</th>
+                        </tr>
+                    </thead>
+                    <tbody>
+                        <tr>
+                            <td class="highlight"><strong>Poisonous Shield for Images</strong></td>
+                            <td class="highlight">Disrupt ML training convergence; make training economically unviable.</td>
+                            <td class="highlight">Targets frequencies to fundamentally disrupt feature extraction and gradient learning. Combines this with cryptographic provenance.</td>
+                            <td class="highlight"><strong>Targets the training process itself, not just the output. Verifiable via cryptographic metadata.</strong></td>
+                        </tr>
+                        <tr>
+                            <td><strong>Glaze</strong></td>
+                            <td>Prevent style mimicry by AI models.</td>
+                            <td>Adds perturbations that mislead models about an artist's specific style, making it difficult to replicate.</td>
+                            <td>Defensive tool focused on protecting artistic style.</td>
+                        </tr>
+                        <tr>
+                            <td><strong>Nightshade</strong></td>
+                            <td>"Poison" the model's understanding of concepts.</td>
+                            <td>A data poisoning attack that manipulates training data to teach the model incorrect associations (e.g., "dogs" are "cats").</td>
+                            <td>Offensive tool that corrupts specific concepts within the model.</td>
+                        </tr>
+                        <tr>
+                            <td><strong>Metadata/Watermarking</strong></td>
+                            <td>Add copyright info or visible marks.</td>
+                            <td>Embeds text in file metadata (EXIF) or places a visible/invisible overlay on the image.</td>
+                            <td>Easily stripped by social media platforms and basic image editing. Offers no protection against training.</td>
+                        </tr>
+                    </tbody>
+                </table>
             </div>
         </div>