## Line Chart: Relative Success Rate vs. Number of Queries for Model Transfer and Greybox Attacks
### Overview
The image is a line chart comparing the performance of two types of adversarial attacks ("Transfer" and "Greybox") against two different target models ("Gemini 1.5 Pro" and "Gemini 1.5 Flash") as the number of queries increases. The chart plots the "relative success rate %" against the "# queries". The data suggests that greybox attacks, which have access to the target model's gradients, consistently achieve positive relative success rates that improve and stabilize with more queries. In contrast, transfer attacks, which rely on adversarial examples crafted on a different model (Gemini 1.0 Nano), show negative relative success rates, indicating they are less effective than a baseline, though their performance varies and shows some improvement at higher query counts.
### Components/Axes
* **Chart Type:** Line chart with markers.
* **X-Axis:**
* **Label:** "# queries"
* **Scale:** Linear scale from approximately 8,000 to 60,000.
* **Major Tick Marks:** 10000, 20000, 30000, 40000, 50000, 60000.
* **Y-Axis:**
* **Label:** "relative success rate %"
* **Scale:** Linear scale from -40% to +10%.
* **Major Tick Marks:** -40, -30, -20, -10, 0, 10.
* **Legend:** Positioned at the top of the chart, outside the plot area. It contains four entries:
1. **Yellow solid line with square markers:** "Transfer Gemini 1.0 Nano -> Gemini 1.5 Pro"
2. **Orange dashed line with star markers:** "Transfer Gemini 1.0 Nano -> Gemini 1.5 Flash"
3. **Red dashed line with downward-pointing triangle markers:** "Greybox on Gemini 1.5 Flash"
4. **Blue solid line with upward-pointing triangle markers:** "Greybox on Gemini 1.5 Pro"
### Detailed Analysis
The chart displays four distinct data series, each with a clear trend:
1. **Greybox on Gemini 1.5 Flash (Red dashed line, downward triangles):**
* **Trend:** Sharp initial increase followed by a stable plateau.
* **Data Points (Approximate):**
* At ~8,000 queries: ~2%
* At ~12,000 queries: ~10%
* From ~18,000 to 60,000 queries: Plateaus between ~10% and ~12%.
2. **Greybox on Gemini 1.5 Pro (Blue solid line, upward triangles):**
* **Trend:** Steady, near-linear increase that tapers off at higher query counts.
* **Data Points (Approximate):**
* At ~8,000 queries: ~-11%
* At ~20,000 queries: ~-3%
* At ~30,000 queries: ~1%
* At ~36,000 queries: ~7%
* From ~36,000 to 60,000 queries: Plateaus around ~7%.
3. **Transfer Gemini 1.0 Nano -> Gemini 1.5 Flash (Orange dashed line, stars):**
* **Trend:** Relatively flat with a slight downward drift, followed by a slight recovery.
* **Data Points (Approximate):**
* From ~8,000 to ~24,000 queries: Hovers around -22%.
* At ~30,000 queries: Drops to ~-29%.
* From ~36,000 to ~54,000 queries: Fluctuates between -29% and -32%.
* At ~60,000 queries: Recovers slightly to ~-25%.
4. **Transfer Gemini 1.0 Nano -> Gemini 1.5 Pro (Yellow solid line, squares):**
* **Trend:** Starts very low, shows consistent improvement, and converges with the other transfer attack line at the highest query count.
* **Data Points (Approximate):**
* At ~8,000 queries: ~-40% (the lowest point on the chart).
* At ~12,000 queries: ~-38%.
* At ~20,000 queries: ~-36%.
* At ~30,000 queries: ~-30%.
* At ~36,000 queries: ~-31%.
* At ~54,000 queries: ~-33%.
* At ~60,000 queries: ~-25%.
### Key Observations
1. **Clear Performance Dichotomy:** There is a stark separation between the two greybox attack series (positive success rates) and the two transfer attack series (negative success rates). The 0% line acts as a clear dividing threshold.
2. **Greybox Attack Superiority:** Both greybox attacks achieve positive relative success rates, with "Greybox on Gemini 1.5 Flash" performing the best overall, plateauing above 10%.
3. **Transfer Attack Ineffectiveness:** Both transfer attacks have negative relative success rates for all query counts shown, meaning they perform worse than the baseline method they are compared against.
4. **Convergence at High Queries:** The two transfer attack lines, which start far apart (-40% vs. -22%), converge to nearly the same point (~-25%) at 60,000 queries.
5. **Diminishing Returns:** All four series show signs of plateauing after approximately 35,000-40,000 queries, suggesting that additional queries beyond this point yield minimal improvement in relative success rate.
### Interpretation
This chart provides a technical comparison of adversarial attack methodologies against Gemini 1.5 models. The data demonstrates a fundamental principle in adversarial machine learning: **attacks with white-box or grey-box access to the target model's gradients (like the "Greybox" attacks here) are significantly more effective than transfer-based black-box attacks.**
* The **positive and stable success rates** of the greybox attacks indicate that having internal model information allows for the efficient generation of successful adversarial examples, with performance saturating as the attacker is given more query budget.
* The **negative relative success rates** of the transfer attacks suggest that adversarial examples crafted on the older Gemini 1.0 Nano model do not transfer well to the newer Gemini 1.5 Pro and Flash architectures. The "relative" metric implies they are being compared to another baseline attack; their negative values mean they are *less effective* than that baseline. The convergence of the two transfer lines at high queries might indicate a fundamental limit to transferability between these specific model generations, regardless of the target model variant (Pro or Flash).
* The **difference between the two greybox lines** (Flash being more vulnerable than Pro to greybox attacks) could imply differences in the models' inherent robustness or the effectiveness of the attack algorithm on their specific architectures.
In summary, the chart underscores the critical importance of model access for attack success and highlights a potential robustness gap or architectural difference between Gemini 1.5 Pro and Flash when facing gradient-based adversarial attacks.
