import keyboard
import time
import numpy as np
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
import pickle
PHRASE = "securetyping"
MODEL_FILE = "keystroke_model.pkl"
# --------------------------------------------------
# Capture keystroke timing
# --------------------------------------------------
def capture_keystrokes(prompt):
print("\n" + prompt)
print(f"Type exactly: '{PHRASE}' and press Enter")
timings = []
press_times = {}
def on_press(e):
if e.name == "enter":
return
press_times[e.name] = time.time()
def on_release(e):
if e.name == "enter":
return
if e.name in press_times:
dwell = time.time() - press_times[e.name]
timings.append(dwell)
keyboard.on_press(on_press)
keyboard.on_release(on_release)
typed = input("> ")
keyboard.unhook_all()
if typed != PHRASE:
print(" Incorrect phrase typed.")
return None
return timings
# --------------------------------------------------
# Collect training samples
# --------------------------------------------------
def collect_samples(samples=10):
data = []
print("\n Training Phase")
for i in range(samples):
t = capture_keystrokes(f"Sample {i + 1}/{samples}")
if t:
data.append(t)
min_len = min(len(x) for x in data)
data = [x[:min_len] for x in data]
return np.array(data)
# --------------------------------------------------
# Train ML model
# --------------------------------------------------
def train_model(data):
X = data
y = np.ones(len(X)) # Legitimate user = 1
# Add fake impostor data (noise)
impostor = np.random.uniform(0.05, 0.4, size=X.shape)
X = np.vstack((X, impostor))
y = np.hstack((y, np.zeros(len(impostor))))
X_train, X_test, y_train, y_test = train_test_split(
X, y, test_size=0.25, random_state=42
)
model = LogisticRegression()
model.fit(X_train, y_train)
acc = accuracy_score(y_test, model.predict(X_test))
print(f"\nš Model Accuracy: {acc * 100:.2f}%")
with open(MODEL_FILE, "wb") as f:
pickle.dump(model, f)
print("✅ Model saved.")
# --------------------------------------------------
# Authenticate user
# --------------------------------------------------
def authenticate():
with open(MODEL_FILE, "rb") as f:
model = pickle.load(f)
t = capture_keystrokes("š Authentication Attempt")
if not t:
return
t = np.array(t).reshape(1, -1)
prediction = model.predict(t)[0]
confidence = model.predict_proba(t)[0][1]
if prediction == 1:
print(f" Access Granted (Confidence: {confidence:.2f})")
else:
print(f" Access Denied (Confidence: {confidence:.2f})")
# --------------------------------------------------
# MAIN
# --------------------------------------------------
if __name__ == "__main__":
print("""
Keystroke Biometrics Demo
1. Train new user
2. Authenticate
""")
choice = input("Choose option (1/2): ").strip()
if choice == "1":
data = collect_samples(samples=8)
train_model(data)
elif choice == "2":
authenticate()
else:
print("Invalid choice.")