示例#1
0
def check_model_3(word):
    model = load_model("./modules/MachineLearning/models/model4.5.h5")
    crs = []
    d = {}
    d = verify_enc.initializare_extins()
    test = []
    encoding = verify_enc.verify_encoding(word, d)
    if (encoding == None):
        encoding = 0
    litere_mari = verify_enc.count_litere_mari(word)
    litere_mici = verify_enc.count_litere_mici(word)
    litere_peste_f = verify_enc.count_litere_mai_mari_de_f(word)
    lungime = verify_enc.get_len(word)
    cifre = verify_enc.count_cifre(word)
    puncte = verify_enc.count_dots(word)
    minus = verify_enc.count_lines(word)
    underscore = verify_enc.count_underscore(word)
    slash = verify_enc.count_slashes(word)
    entropy = verify_enc.get_entropy(word)
    all_lens = verify_enc.get_every_len(word)
    test.append(float(encoding))
    test.append(float(litere_mari))
    test.append(float(litere_mici))
    test.append(float(litere_peste_f))
    test.append(float(lungime))
    test.append(float(cifre))
    test.append(float(puncte))
    test.append(float(minus))
    test.append(float(underscore))
    test.append(float(slash))
    test.append(float(entropy))
    for z in all_lens:
        test.append(float(z))
    crs.append(test)
    X_train = np.array(crs)
    # =============================================================================
    # scaler = StandardScaler()
    # test_scaled=scaler.fit(X_train)
    # =============================================================================
    out = model.predict(crs)
    return int(out[0][0])
示例#2
0
文件: script.py 项目: 0x435446/CANARI
false_ads = verify_enc.read_file('false_extins.csv')

d = {}
d = verify_enc.initializare_extins()
for i in true_ads:
    encoding = verify_enc.verify_encoding(i[0], d)
    litere_mari = verify_enc.count_litere_mari(i[0])
    litere_mici = verify_enc.count_litere_mici(i[0])
    litere_peste_f = verify_enc.count_litere_mai_mari_de_f(i[0])
    lungime = verify_enc.get_len(i[0])
    cifre = verify_enc.count_cifre(i[0])
    puncte = verify_enc.count_dots(i[0])
    minus = verify_enc.count_lines(i[0])
    underscore = verify_enc.count_underscore(i[0])
    slash = verify_enc.count_slashes(i[0])
    entropy = verify_enc.get_entropy(i[0])
    all_lens = verify_enc.get_every_len(i[0])
    array = []
    if (encoding == None):
        encoding = 0
    array.append(float(encoding))
    array.append(float(litere_mari))
    array.append(float(litere_mici))
    array.append(float(litere_peste_f))
    array.append(float(lungime))
    array.append(float(cifre))
    array.append(float(puncte))
    array.append(float(minus))
    array.append(float(underscore))
    array.append(float(slash))
    array.append(float(entropy))