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Performance Analysis of Evaluate Side Channel Attack

 

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Performance Analysis of Evaluate Side Channel Attack Countermeasures for the A

Implementation Plan
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Scenario 1: (using ASCAD with masked variants):
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Step 1: Initially, we collect power traces and metadata from the ASCAD dataset(masked variants).

Step 2: Next, we extract plaintext, key, and compute SBox-based labels for the target byte from the dataset.

Step 3: Next, we normalize the traces, encode the labels, and split the dataset into training, validation, and testing sets.

Step 4: Next, we build a CNN model with convolutional layers and fully connected layers for AES key byte classification.

Step 5: Next, we train the CNN model using cross-entropy loss and validate it to improve accuracy.

Step 6: Next, we evaluate model performance using key rank analysis to measure the trace count needed to identify the key byte.

Step 7: Finally, we plot performance for the following metrics:

7.1: Number of epochs vs. Accuracy (%)

7.2: Number of epochs vs. Precision (%)

7.3: Number of epochs vs. Recall (%)

7.4: Number of epochs vs. F1-score (%)

Scenario 2: (using ASCAD with unmasked variants):
————————————————————–

Step 1: Initially, we collect power traces and metadata from the ASCAD dataset (unmasked variants).

Step 2: Next, we extract plaintext, key, and compute SBox-based labels for the target byte from the dataset.

Step 3: Next, we normalize the traces, encode the labels, and split the dataset into training, validation, and testing sets.

Step 4: Next, we build a CNN model with convolutional layers and fully connected layers for AES key byte classification.

Step 5: Next, we train the CNN model using cross-entropy loss and validate it to improve accuracy.

Step 6: Next, we evaluate model performance using key rank analysis to measure the trace count needed to identify the key byte.

Step 7: Finally, we plot performance for the following metrics:

7.1: Number of epochs vs. Accuracy (%)

7.2: Number of epochs vs. Precision (%)

7.3: Number of epochs vs. Recall (%)

7.4: Number of epochs vs. F1-score (%)

Software Requirement:
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1. Development Tool: Python 3.11.4 or above

2. Operating System: Windows 10 (64-bit) or above

Dataset Link:
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https://static.data.gouv.fr/resources/ascad-atmega-8515-variable-key/20190903-083349/ascad-variable.h5

https://static.data.gouv.fr/resources/ascad-atmega-8515-variable-key/20190903-084119/ascad-variable-desync50.h5

https://static.data.gouv.fr/resources/ascad-atmega-8515-variable-key/20190903-084306/ascad-variable-desync100.h5

Note:
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1) If the plan does not meet your requirements, provide detailed steps, parameters, models, or expected results in advance. Once implemented, changes won’t be possible without prior input; otherwise, we’ll proceed as per our implementation plan.

2) If the plan satisfies your requirement, Please confirm with us.

3) Project based on Simulation only, not a real time project.

4) If you have any changes in the Dataset , kindly provide before implementation. Our work is completely based on dataset values.

5) Please understand that any modifications made to the confirmed implementation plan will not be made after the project development.

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