Hello, I hope you are doing well,

I am doing my project, which is Ransomware attack detection using Deep learning CNNs

I got a result of 0.93, which is not good enough, I have tried to improve my accuracy, but I gave up. Could you modify the code feature selection or pre-processing to get a higher result? Even for that result, I have to wait a long time to get it because I increased the epoch, and could you explain the added part?

from keras.models import Sequential

from keras.layers import Conv2D, MaxPooling2D, Flatten, Dense

from keras.preprocessing.image import ImageDataGenerator

# Define the model architecture

model = Sequential()

model.add(Conv2D(32, (3, 3), activation='relu', input_shape=(224, 224, 3)))

model.add(MaxPooling2D((2, 2)))

model.add(Conv2D(64, (3, 3), activation='relu'))

model.add(MaxPooling2D((2, 2)))

model.add(Conv2D(128, (3, 3), activation='relu'))

model.add(MaxPooling2D((2, 2)))

model.add(Flatten())

model.add(Dense(128, activation='relu'))

model.add(Dense(1, activation='sigmoid'))

# Compile the model

model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])

# Data preprocessing

train_datagen = ImageDataGenerator(rescale=1./255)

test_datagen = ImageDataGenerator(rescale=1./255)

train_generator = train_datagen.flow_from_directory(

Thank you in advance.