romanbredehoft-zama
commited on
Commit
•
8d5cb63
1
Parent(s):
bc345ce
Refactor send files to server
Browse files- app.py +11 -11
- backend.py +24 -44
- server.py +10 -23
- settings.py +1 -1
app.py
CHANGED
@@ -10,7 +10,7 @@ from settings import (
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CHILDREN_MIN_MAX,
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INCOME_MIN_MAX,
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AGE_MIN_MAX,
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-
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FAMILY_MIN_MAX,
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INCOME_TYPES,
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OCCUPATION_TYPES,
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@@ -40,7 +40,7 @@ print("Starting the demo...")
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with demo:
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gr.Markdown(
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"""
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-
<h1 align="center">Credit Card Approval Prediction Using Fully Homomorphic Encryption</h1>
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"""
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)
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@@ -57,10 +57,10 @@ with demo:
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gr.Markdown("### User")
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gender = gr.Radio(["Female", "Male"], label="Gender", value="Female")
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bool_inputs = gr.CheckboxGroup(["Car", "Property", "Work phone", "Phone", "Email"], label="What do you own ?")
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-
num_children = gr.Slider(**CHILDREN_MIN_MAX, step=1, label="Number of children", info="How many children do you have
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-
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-
total_income = gr.Slider(**INCOME_MIN_MAX, label="Income", info="What's you total yearly income (in euros
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-
age = gr.Slider(**AGE_MIN_MAX, step=1, label="Age", info="How old are you
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income_type = gr.Dropdown(choices=INCOME_TYPES, value=INCOME_TYPES[0], label="Income type", info="What is your main type of income ?")
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education_type = gr.Dropdown(choices=EDUCATION_TYPES, value=EDUCATION_TYPES[0], label="Education", info="What is your education background ?")
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family_status = gr.Dropdown(choices=FAMILY_STATUS, value=FAMILY_STATUS[0], label="Family", info="What is your family status ?")
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@@ -69,12 +69,12 @@ with demo:
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with gr.Column():
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gr.Markdown("### Bank ")
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-
account_length = gr.Slider(**ACCOUNT_MIN_MAX, step=1, label="Account length", info="How long have this person had this account (in months
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with gr.Column():
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gr.Markdown("### Third party ")
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-
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-
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gr.Markdown("### Step 3: Encrypt using FHE and send the inputs to the server.")
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@@ -153,7 +153,7 @@ with demo:
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# side to the server
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encrypt_button_user.click(
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pre_process_encrypt_send_user,
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-
inputs=[client_id, gender, bool_inputs, num_children,
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income_type, education_type, family_status, occupation_type, housing_type],
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outputs=[encrypted_input_user],
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)
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@@ -170,7 +170,7 @@ with demo:
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# client side to the server
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encrypt_button_third_party.click(
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pre_process_encrypt_send_third_party,
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-
inputs=[client_id,
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outputs=[encrypted_input_third_party],
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)
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CHILDREN_MIN_MAX,
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INCOME_MIN_MAX,
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AGE_MIN_MAX,
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+
SALARIED_MIN_MAX,
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FAMILY_MIN_MAX,
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INCOME_TYPES,
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OCCUPATION_TYPES,
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with demo:
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gr.Markdown(
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"""
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+
<h1 align="center">Encrypted Credit Card Approval Prediction Using Fully Homomorphic Encryption</h1>
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"""
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)
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gr.Markdown("### User")
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gender = gr.Radio(["Female", "Male"], label="Gender", value="Female")
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bool_inputs = gr.CheckboxGroup(["Car", "Property", "Work phone", "Phone", "Email"], label="What do you own ?")
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+
num_children = gr.Slider(**CHILDREN_MIN_MAX, step=1, label="Number of children", info="How many children do you have ?")
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+
household_size = gr.Slider(**FAMILY_MIN_MAX, step=1, label="Household size", info="How many members does your family have? ?")
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+
total_income = gr.Slider(**INCOME_MIN_MAX, label="Income", info="What's you total yearly income (in euros) ?")
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age = gr.Slider(**AGE_MIN_MAX, step=1, label="Age", info="How old are you ?")
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income_type = gr.Dropdown(choices=INCOME_TYPES, value=INCOME_TYPES[0], label="Income type", info="What is your main type of income ?")
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education_type = gr.Dropdown(choices=EDUCATION_TYPES, value=EDUCATION_TYPES[0], label="Education", info="What is your education background ?")
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family_status = gr.Dropdown(choices=FAMILY_STATUS, value=FAMILY_STATUS[0], label="Family", info="What is your family status ?")
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with gr.Column():
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gr.Markdown("### Bank ")
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account_length = gr.Slider(**ACCOUNT_MIN_MAX, step=1, label="Account length", info="How long have this person had this account (in months) ?")
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with gr.Column():
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gr.Markdown("### Third party ")
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salaried = gr.Radio(["Yes", "No"], label="Is the person salaried ?", value="Yes")
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years_salaried = gr.Slider(**SALARIED_MIN_MAX, step=1, label="Years of employment", info="How long have this person been salaried (in years) ?")
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gr.Markdown("### Step 3: Encrypt using FHE and send the inputs to the server.")
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# side to the server
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encrypt_button_user.click(
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pre_process_encrypt_send_user,
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+
inputs=[client_id, gender, bool_inputs, num_children, household_size, total_income, age, \
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income_type, education_type, family_status, occupation_type, housing_type],
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outputs=[encrypted_input_user],
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)
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# client side to the server
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encrypt_button_third_party.click(
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pre_process_encrypt_send_third_party,
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inputs=[client_id, salaried, years_salaried],
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outputs=[encrypted_input_third_party],
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)
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backend.py
CHANGED
@@ -103,7 +103,7 @@ def _get_client_file_path(name, client_id, client_type=None):
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"""Get the file path for the client.
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Args:
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-
name (str): The desired file name (either 'evaluation_key', 'encrypted_inputs'
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'encrypted_outputs').
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client_id (int): The client ID to consider.
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client_type (Optional[str]): The type of user to consider (either 'user', 'bank',
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@@ -122,33 +122,6 @@ def _get_client_file_path(name, client_id, client_type=None):
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return dir_path / f"{name}{client_type_suffix}"
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-
def _send_eval_key(client_id, evaluation_key_path):
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"""Send the evaluation key to the server.
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Args:
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client_id (int): The client ID to consider.
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evaluation_key_path (Path): Path to the evaluation key to send.
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"""
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# Define the data and files to post
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data = {
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"client_id": client_id,
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}
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files = [
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("files", open(evaluation_key_path, "rb")),
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]
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# Send the evaluation key to the server
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url = SERVER_URL + "send_eval_key"
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with requests.post(
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url=url,
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data=data,
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files=files,
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) as response:
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return response.ok
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def keygen_send():
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"""Generate the private and evaluation key, and send the evaluation key to the server.
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@@ -170,41 +143,46 @@ def keygen_send():
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# Retrieve the serialized evaluation key
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evaluation_key = client.get_serialized_evaluation_keys()
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# Save evaluation key as bytes in a file as it is too large to pass through regular Gradio
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# buttons (see https://github.com/gradio-app/gradio/issues/1877)
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-
evaluation_key_path = _get_client_file_path(
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with evaluation_key_path.open("wb") as evaluation_key_file:
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evaluation_key_file.write(evaluation_key)
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# Send the evaluation key to the server
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return client_id, gr.update(value="Keys are generated and sent ✅")
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-
def
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"""Send the encrypted inputs
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Args:
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client_id (int): The client ID to consider.
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-
client_type (str): The type of client to consider (either 'user', 'bank'
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"""
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# Get the paths to the encrypted inputs
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# Define the data and files to post
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data = {
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"client_id": client_id,
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"client_type": client_type,
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}
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files = [
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("files", open(
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]
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# Send the encrypted inputs
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url = SERVER_URL + "
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with requests.post(
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url=url,
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data=data,
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@@ -237,9 +215,11 @@ def _encrypt_send(client_id, inputs, client_type):
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input_slice=INPUT_SLICES[client_type],
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)
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# Save encrypted_inputs to bytes in a file, since too large to pass through regular Gradio
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# buttons, https://github.com/gradio-app/gradio/issues/1877
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-
encrypted_inputs_path = _get_client_file_path(
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with encrypted_inputs_path.open("wb") as encrypted_inputs_file:
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encrypted_inputs_file.write(encrypted_inputs)
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@@ -247,7 +227,7 @@ def _encrypt_send(client_id, inputs, client_type):
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# Create a truncated version of the encrypted inputs for display
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encrypted_inputs_short = shorten_bytes_object(encrypted_inputs)
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-
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return encrypted_inputs_short
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@@ -263,7 +243,7 @@ def pre_process_encrypt_send_user(client_id, *inputs):
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(int, bytes): Integer ID representing the current client and a byte short representation of
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the encrypted input to send.
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"""
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-
gender, bool_inputs, num_children,
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family_status, occupation_type, housing_type = inputs
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# Encoding given in https://www.kaggle.com/code/samuelcortinhas/credit-cards-data-cleaning
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@@ -285,7 +265,7 @@ def pre_process_encrypt_send_user(client_id, *inputs):
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"Phone": [phone],
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"Email": [email],
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"Num_children": num_children,
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-
"Num_family":
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"Total_income": total_income,
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"Age": age,
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"Income_type": income_type,
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@@ -327,14 +307,14 @@ def pre_process_encrypt_send_third_party(client_id, *inputs):
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(int, bytes): Integer ID representing the current client and a byte short representation of
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the encrypted input to send.
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"""
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-
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# Original dataset contains an "unemployed" feature instead of "employed"
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-
unemployed =
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third_party_inputs = pandas.DataFrame({
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"Unemployed": [unemployed],
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-
"Years_employed": [
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})
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preprocessed_third_party_inputs = PRE_PROCESSOR_THIRD_PARTY.transform(third_party_inputs)
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"""Get the file path for the client.
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Args:
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+
name (str): The desired file name (either 'evaluation_key', 'encrypted_inputs' or
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'encrypted_outputs').
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client_id (int): The client ID to consider.
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client_type (Optional[str]): The type of user to consider (either 'user', 'bank',
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return dir_path / f"{name}{client_type_suffix}"
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def keygen_send():
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"""Generate the private and evaluation key, and send the evaluation key to the server.
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# Retrieve the serialized evaluation key
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evaluation_key = client.get_serialized_evaluation_keys()
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file_name = "evaluation_key"
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+
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# Save evaluation key as bytes in a file as it is too large to pass through regular Gradio
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# buttons (see https://github.com/gradio-app/gradio/issues/1877)
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+
evaluation_key_path = _get_client_file_path(file_name, client_id)
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with evaluation_key_path.open("wb") as evaluation_key_file:
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evaluation_key_file.write(evaluation_key)
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# Send the evaluation key to the server
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_send_to_server(client_id, None, file_name)
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return client_id, gr.update(value="Keys are generated and sent ✅")
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+
def _send_to_server(client_id, client_type, file_name):
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"""Send the encrypted inputs or the evaluation key to the server.
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Args:
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client_id (int): The client ID to consider.
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+
client_type (Optional[str]): The type of client to consider (either 'user', 'bank', 'third_party' or
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None).
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file_name (str): File name to send (either 'evaluation_key' or 'encrypted_inputs').
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"""
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# Get the paths to the encrypted inputs
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encrypted_file_path = _get_client_file_path(file_name, client_id, client_type)
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# Define the data and files to post
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data = {
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"client_id": client_id,
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"client_type": client_type,
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"file_name": file_name,
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}
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files = [
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("files", open(encrypted_file_path, "rb")),
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]
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# Send the encrypted inputs or evaluation key to the server
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url = SERVER_URL + "send_file"
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with requests.post(
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url=url,
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data=data,
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input_slice=INPUT_SLICES[client_type],
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)
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+
file_name = "encrypted_inputs"
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# Save encrypted_inputs to bytes in a file, since too large to pass through regular Gradio
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# buttons, https://github.com/gradio-app/gradio/issues/1877
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+
encrypted_inputs_path = _get_client_file_path(file_name, client_id, client_type)
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with encrypted_inputs_path.open("wb") as encrypted_inputs_file:
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encrypted_inputs_file.write(encrypted_inputs)
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# Create a truncated version of the encrypted inputs for display
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encrypted_inputs_short = shorten_bytes_object(encrypted_inputs)
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_send_to_server(client_id, client_type, file_name)
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return encrypted_inputs_short
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(int, bytes): Integer ID representing the current client and a byte short representation of
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the encrypted input to send.
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"""
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+
gender, bool_inputs, num_children, household_size, total_income, age, income_type, education_type, \
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family_status, occupation_type, housing_type = inputs
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# Encoding given in https://www.kaggle.com/code/samuelcortinhas/credit-cards-data-cleaning
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"Phone": [phone],
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"Email": [email],
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"Num_children": num_children,
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+
"Num_family": household_size,
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"Total_income": total_income,
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"Age": age,
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"Income_type": income_type,
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(int, bytes): Integer ID representing the current client and a byte short representation of
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the encrypted input to send.
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"""
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+
salaried, years_salaried = inputs
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# Original dataset contains an "unemployed" feature instead of "employed"
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unemployed = salaried == "No"
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third_party_inputs = pandas.DataFrame({
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"Unemployed": [unemployed],
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+
"Years_employed": [years_salaried],
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})
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preprocessed_third_party_inputs = PRE_PROCESSOR_THIRD_PARTY.transform(third_party_inputs)
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server.py
CHANGED
@@ -1,7 +1,7 @@
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"""Server that will listen for GET and POST requests from the client."""
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import time
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from typing import List
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from fastapi import FastAPI, File, Form, UploadFile
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from fastapi.responses import JSONResponse, Response
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@@ -44,33 +44,20 @@ def root():
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return {"message": "Welcome to Credit Card Approval Prediction server!"}
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-
@app.post("/
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def
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client_id: str = Form(),
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files: List[UploadFile] = File(),
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):
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"""Send the
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# Retrieve the evaluation key
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-
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-
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# Write the file using the above path
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with evaluation_key_path.open("wb") as evaluation_key:
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evaluation_key.write(files[0].file.read())
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-
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-
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@app.post("/send_input")
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-
def send_input(
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client_id: str = Form(),
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-
client_type: str = Form(),
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files: List[UploadFile] = File(),
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):
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"""Send the inputs to the server."""
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# Retrieve the encrypted inputs
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encrypted_inputs_path = _get_server_file_path("encrypted_inputs", client_id, client_type)
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# Write the file using the above path
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-
with
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-
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@app.post("/run_fhe")
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"""Server that will listen for GET and POST requests from the client."""
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import time
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from typing import List, Optional
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from fastapi import FastAPI, File, Form, UploadFile
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from fastapi.responses import JSONResponse, Response
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return {"message": "Welcome to Credit Card Approval Prediction server!"}
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@app.post("/send_file")
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def send_file(
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client_id: str = Form(),
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client_type: Optional[str] = Form(None),
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file_name: str = Form(),
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files: List[UploadFile] = File(),
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):
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"""Send the files to the server."""
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# Retrieve the encrypted inputs or evaluation key
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encrypted_file_path = _get_server_file_path(file_name, client_id, client_type)
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57 |
|
58 |
# Write the file using the above path
|
59 |
+
with encrypted_file_path.open("wb") as encrypted_file:
|
60 |
+
encrypted_file.write(files[0].file.read())
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61 |
|
62 |
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63 |
@app.post("/run_fhe")
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settings.py
CHANGED
@@ -60,7 +60,7 @@ ACCOUNT_MIN_MAX = get_min_max(_data, "Account_length")
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|
60 |
CHILDREN_MIN_MAX = get_min_max(_data, "Num_children")
|
61 |
INCOME_MIN_MAX = get_min_max(_data, "Total_income")
|
62 |
AGE_MIN_MAX = get_min_max(_data, "Age")
|
63 |
-
|
64 |
FAMILY_MIN_MAX = get_min_max(_data, "Num_family")
|
65 |
|
66 |
# App data choices
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|
60 |
CHILDREN_MIN_MAX = get_min_max(_data, "Num_children")
|
61 |
INCOME_MIN_MAX = get_min_max(_data, "Total_income")
|
62 |
AGE_MIN_MAX = get_min_max(_data, "Age")
|
63 |
+
SALARIED_MIN_MAX = get_min_max(_data, "Years_employed")
|
64 |
FAMILY_MIN_MAX = get_min_max(_data, "Num_family")
|
65 |
|
66 |
# App data choices
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