CaseScan Proposed Test Plan

First Use Case - Field Work

1. Run CaseScan on a previously worked-on case to establish a benchmark.
2. During scanning, wait 5-10 minutes and click the Preview Results button.
3. Review the results:
   • Hover over images and videos to unblur content.
   • Adjust blur and pointer size as needed.
   • Apply High, Medium, and Low CSAM AI filters.
   • Note if images or videos containing CSAM are displayed.
   • Use the frame navigator to browse video frames, skipping repetitive frames.
   • Note if sufficient evidence was identified for an arrest:
     • Time taken for scanning.
     • Time saved compared to manual sorting.
     • Number of reviewed images/videos required to gather enough evidence.
     • Potential personal exposure to sensitive materials.
4. If insufficient evidence is found, return to scanning, wait 5 more minutes, and repeat the review.

Second Use Case - Lab Analysis

1. Allow CaseScan to complete its full search.
2. Click each CSAM filter and compare results:
   • Compare manually identified CSAM files to those identified by CaseScan.
   • Note new files detected by CaseScan and time saved using the tool.
   • Breakdown of images vs. videos detected.
3. Experiment with additional filters:
   • Nude and Underwear filters.
   • File parameters (e.g., location, device model, file size).

Third Use Case - Report Generation

1. Reset filters and select the High CSAM AI filter.
2. Tag specific images and videos for the Court Report:
   • Add comments and tags (e.g., "Suspect and victim on bed").
   • Note file metadata for filtering.
3. Export results:
   • Set blur level to 25.
   • Include geo-location data, comments, and tags.
   • Save the report as a PDF or print.
4. Highlight features:
   • Ability to focus on key evidence.
   • Customized reports for legal and investigative purposes.

Enhanced Features for Testing

• Frame navigator ensures minimal repetition in videos by displaying unique frames.
• Filtering capabilities streamline search by content type, metadata, or AI classification.
• High accuracy in CSAM identification reduces manual review effort.