How it works
The Levenshtein Distance widget calculates the minimum number of single-character edits (insertions, deletions, or substitutions) required to transform one ciphertext into another. This metric is useful for comparing two ciphertexts and determining how similar or different they are.Select Ciphertexts
Choose a source ciphertext and a target ciphertext from your available ciphertexts. The widget will compare these two texts
character by character.
Ciphertext Settings
Levenshtein distance takes into consideration the settings for each ciphertext. These settings include:
- Ignore whitespace
- Ignore punctuation
- Ignore casing
- Genericize text
Distance Calculation
The algorithm computes the minimum edit distance using dynamic programming. For each position in both texts, it determines the
optimal sequence of operations needed to transform one text into the other.
Understanding the Results
Distance Score
The distance score represents the minimum number of edits required:- 0 means the texts are identical
- Higher numbers indicate more differences between the texts
Similarity Percentage
The similarity percentage is calculated as: Where Max Length is the length of the longer text. This gives you an intuitive percentage:- 100% means identical texts
- 0% means completely different texts (every character needs to be changed)
Levenshtein Distance Settings
Display Mode
Score View
Displays the edit distance as a prominent number along with:- Similarity percentage with a color indicator (green for similar, red for different)
- Character counts for both source and target texts
- Labels showing which ciphertexts are being compared
Visual Diff View
Provides a character-by-character visualization of the differences:- Green background: Characters that need to be inserted (present in target but not source)
- Red background: Characters that need to be deleted (present in source but not target)
- Yellow/Blue highlight: Characters that need to be substituted (different character in each text)
- No highlight: Matching characters
Edit Operations
The Levenshtein algorithm considers three types of edits:| Operation | Description | Example |
|---|---|---|
| Insertion | Add a character | ”cat” → “cart” (insert ‘r’) |
| Deletion | Remove a character | ”cart” → “cat” (delete ‘r’) |
| Substitution | Replace a character | ”cat” → “bat” (substitute ‘c’ with ‘b’) |
Practical Applications
Levenshtein distance analysis can be leveraged to:- Detect minor variations: Find ciphertexts that are nearly identical with small alterations
- Identify related texts: Determine if two ciphertexts may have originated from similar sources
- Track modifications: Understand what changes were made between two versions of encrypted content
- Pattern matching: Locate texts that approximate a known pattern despite small differences
Interpretation Guide
| Similarity | Interpretation |
|---|---|
| 90-100% | Nearly identical - minor differences only |
| 70-89% | Highly similar - same general content with some changes |
| 50-69% | Moderately similar - significant overlap exists |
| 25-49% | Low similarity - mostly different content |
| 0-24% | Very different - little to no common content |
Caveats
- Length sensitivity: Very different text lengths will naturally result in higher distances due to the number of insertions or deletions required.
- Position matters: Two texts with the same characters but in different orders will have a high distance.
- Computational limits: Very long texts may take longer to process due to the nature of the comparison algorithm.
- Symmetric metric: The distance from A to B equals the distance from B to A.