## Chart Type: Receiver Operating Characteristic (ROC) Curves ### Overview The image is a Receiver Operating Characteristic (ROC) curve chart, comparing the performance of different attack scenarios (No Attack, Dipper-5, Dipper-10, Dipper-10-5) against a random guess baseline. The chart plots the True Positive Rate (TPR) against the False Positive Rate (FPR). The Area Under the Curve (AUC) is provided for each scenario, indicating the model's ability to distinguish between positive and negative classes. ### Components/Axes * **Title:** Receiver Operating Characteristic (ROC) Curves * **X-axis:** False Positive Rate (FPR), ranging from 0.0 to 1.0 in increments of 0.2. * **Y-axis:** True Positive Rate (TPR), ranging from 0.0 to 1.0 in increments of 0.2. * **Legend:** Located in the bottom-right corner, it identifies the different attack scenarios and their corresponding AUC values: * Blue: No Attack (AUC=1.0000) * Green: Dipper-5 (AUC=0.9818) * Orange: Dipper-10 (AUC=0.9799) * Red: Dipper-10-5 (AUC=0.9692) * Dashed Gray: Random Guess ### Detailed Analysis * **No Attack (Blue):** The blue line rises sharply to a TPR of 1.0 at a very low FPR (close to 0.0), and remains at 1.0 for all subsequent FPR values. This indicates perfect classification. * **Dipper-5 (Green):** The green line rises quickly, reaching a TPR of approximately 0.9 at an FPR of around 0.05. It then gradually increases to 1.0 as the FPR approaches 0.4. * **Dipper-10 (Orange):** The orange line follows a similar trend to Dipper-5, but its initial rise is slightly slower. It reaches a TPR of approximately 0.8 at an FPR of around 0.05, and gradually increases to 1.0 as the FPR approaches 0.4. * **Dipper-10-5 (Red):** The red line has the slowest initial rise among the attack scenarios. It reaches a TPR of approximately 0.8 at an FPR of around 0.1, and gradually increases to 1.0 as the FPR approaches 0.4. * **Random Guess (Dashed Gray):** The dashed gray line represents a random guess, with TPR equal to FPR. It is a diagonal line from (0.0, 0.0) to (1.0, 1.0). ### Key Observations * The "No Attack" scenario has the highest AUC (1.0000), indicating perfect classification. * The "Dipper-10-5" scenario has the lowest AUC (0.9692) among the attack scenarios, indicating the worst performance. * All attack scenarios outperform the "Random Guess" baseline. * The ROC curves for "Dipper-5" and "Dipper-10" are very close, suggesting similar performance. ### Interpretation The ROC curves illustrate the performance of different attack scenarios in terms of their ability to correctly classify events. The "No Attack" scenario represents an ideal situation where the system can perfectly distinguish between positive and negative cases. The "Dipper" attack scenarios represent varying degrees of compromise, with "Dipper-10-5" being the most challenging to detect. The AUC values provide a quantitative measure of the performance of each scenario, with higher AUC values indicating better performance. The fact that all attack scenarios outperform the "Random Guess" baseline suggests that the system has some ability to detect these attacks. The closer the ROC curve is to the top-left corner, the better the performance of the model.

## Chart: Receiver Operating Characteristic (ROC) Curves ### Overview The image presents Receiver Operating Characteristic (ROC) curves for four different scenarios: "No Attack", "Dipper-5", "Dipper-10", and "Dipper-10-5", alongside a "Random Guess" baseline. The curves plot True Positive Rate (TPR) against False Positive Rate (FPR), providing a visual assessment of the performance of a binary classification model under varying threshold settings. The Area Under the Curve (AUC) is provided for each scenario. ### Components/Axes * **Title:** Receiver Operating Characteristic(ROC) Curves * **X-axis:** False Positive Rate (FPR) - Scale: 0.0 to 1.0 * **Y-axis:** True Positive Rate (TPR) - Scale: 0.0 to 1.0 * **Legend:** Located in the bottom-right corner. * "No Attack" - Blue solid line (AUC = 1.0000) * "Dipper-5" - Orange solid line (AUC = 0.9818) * "Dipper-10" - Yellow solid line (AUC = 0.9799) * "Dipper-10-5" - Green solid line (AUC = 0.9692) * "Random Guess" - Gray dashed line ### Detailed Analysis * **No Attack (Blue Line):** The curve starts at (0.0, 0.0) and quickly rises vertically to (approximately 0.0, 1.0) and remains at TPR = 1.0 for all FPR values. This indicates perfect classification performance with an AUC of 1.0000. * **Dipper-5 (Orange Line):** The curve starts at (0.0, 0.0) and rises rapidly, reaching a TPR of approximately 0.8 at an FPR of 0.1. It continues to rise, approaching TPR = 1.0 as FPR approaches 1.0. The AUC is 0.9818. * **Dipper-10 (Yellow Line):** The curve starts at (0.0, 0.0) and rises, but less steeply than the "Dipper-5" curve. It reaches a TPR of approximately 0.75 at an FPR of 0.1. The curve continues to rise, but remains below the "Dipper-5" curve. The AUC is 0.9799. * **Dipper-10-5 (Green Line):** The curve starts at (0.0, 0.0) and rises, but is the least steep of the four scenarios. It reaches a TPR of approximately 0.7 at an FPR of 0.1. The curve remains below the "Dipper-5" and "Dipper-10" curves. The AUC is 0.9692. * **Random Guess (Gray Dashed Line):** This line represents a diagonal from (0.0, 0.0) to (1.0, 1.0). It serves as a baseline for comparison; any curve above this line indicates performance better than random guessing. ### Key Observations * The "No Attack" scenario exhibits perfect classification, as evidenced by the ROC curve reaching TPR = 1.0 almost immediately. * The "Dipper-5" scenario demonstrates the best performance among the "Dipper" scenarios, with the highest AUC. * As the "Dipper" scenarios become more complex ("Dipper-10" and "Dipper-10-5"), the AUC values decrease, indicating a reduction in classification performance. * All four scenarios perform significantly better than random guessing, as their ROC curves lie above the diagonal "Random Guess" line. ### Interpretation The ROC curves demonstrate the effectiveness of a classification model in distinguishing between positive and negative cases under different conditions. The "No Attack" scenario represents an ideal situation where the model can perfectly identify the absence of an attack. The "Dipper" scenarios likely represent different types or levels of attacks, with "Dipper-5" being the easiest to detect and "Dipper-10-5" being the most challenging. The decreasing AUC values as the "Dipper" scenarios become more complex suggest that the model's ability to accurately classify attacks diminishes with increasing complexity. The "Random Guess" line provides a crucial benchmark, highlighting that the model consistently outperforms chance. This data suggests that the model is effective at detecting attacks, but its performance is sensitive to the type and complexity of the attack. Further investigation could focus on improving the model's ability to classify the more complex "Dipper" scenarios.

## Chart: Receiver Operating Characteristic (ROC) Curves ### Overview The image displays a Receiver Operating Characteristic (ROC) curve chart comparing the performance of four models: "No Attack," "Dipper-5," "Dipper-10," and "Dipper-10-5," against a "Random Guess" baseline. The chart evaluates the trade-off between True Positive Rate (TPR) and False Positive Rate (FPR) for each model, with AUC (Area Under the Curve) values provided in the legend. ### Components/Axes - **X-axis**: False Positive Rate (FPR), ranging from 0.0 to 1.0 in increments of 0.2. - **Y-axis**: True Positive Rate (TPR), ranging from 0.0 to 1.0 in increments of 0.2. - **Legend**: Located in the bottom-right corner, with the following entries: - **Blue**: No Attack (AUC=1.0000) - **Green**: Dipper-5 (AUC=0.9818) - **Orange**: Dipper-10 (AUC=0.9799) - **Red**: Dipper-10-5 (AUC=0.9692) - **Dashed Gray**: Random Guess (diagonal line from (0,0) to (1,1)). ### Detailed Analysis 1. **No Attack (Blue Line)**: - A horizontal line at TPR=1.0, indicating perfect detection with no false positives. This is an idealized scenario, as it suggests no false alarms occur. - AUC=1.0000 confirms perfect classification. 2. **Dipper-5 (Green Line)**: - Starts at (0,0) and rises sharply to (1,1), with a smooth, near-linear trajectory. - AUC=0.9818 indicates high performance, slightly below the ideal. 3. **Dipper-10 (Orange Line)**: - Similar trajectory to Dipper-5 but with a slightly flatter slope, indicating marginally lower performance. - AUC=0.9799, slightly lower than Dipper-5. 4. **Dipper-10-5 (Red Line)**: - Starts at (0,0) but has a more gradual ascent compared to Dipper-5 and Dipper-10. - AUC=0.9692, the lowest among the Dipper models, suggesting reduced effectiveness. 5. **Random Guess (Dashed Gray Line)**: - A diagonal line from (0,0) to (1,1), representing a baseline performance where TPR equals FPR. - All models outperform this baseline. ### Key Observations - **No Attack** is the only model achieving perfect performance (AUC=1.0000), but this is unrealistic in practice. - **Dipper-5** outperforms the other Dipper models, with the highest AUC (0.9818). - **Dipper-10-5** has the lowest AUC (0.9692), indicating it is the least effective among the Dipper variants. - All models (except No Attack) start at (0,0) and end at (1,1), but their paths diverge, reflecting differences in discrimination ability. ### Interpretation The ROC curves demonstrate that: - **No Attack** is theoretically optimal but impractical, as it assumes no false positives. - **Dipper-5** is the most effective model among the Dipper variants, balancing high TPR and low FPR. - **Dipper-10-5** underperforms compared to Dipper-5 and Dipper-10, suggesting that its configuration or parameters may be suboptimal. - The **Random Guess** line serves as a critical benchmark, confirming that all models provide meaningful improvements over chance performance. The AUC values quantify the models' ability to distinguish between classes, with higher values indicating better performance. The slight decline in AUC from Dipper-5 to Dipper-10-5 highlights the importance of model tuning to maximize discrimination.