看不见明文，依然看得见攻击

d["delta_prev_total_packets"] = d["total_packets"] - prev["total_packets"]
starts = list(range(0, max(len(base) - seq_len + 1, 1), stride))
if len(base) > seq_len and starts[-1] != len(base) - seq_len:
    starts.append(len(base) - seq_len)
chunk = base[st: st + seq_len]
mat = np.zeros((seq_len, len(FEATURE_NAMES_EFB_V2C)), dtype=np.float32)
for r, d in enumerate(chunk):
    mat[r, :] = np.array([d[n] for n in FEATURE_NAMES_EFB_V2C], dtype=np.float32)

flow_labels = [f["_behavior_label"] for _, f in chunk]
malicious = [f for _, f in chunk if int(f["_y"]) == 1]
if malicious:
    y = 1
    behavior = Counter(f["_behavior_label"] for f in malicious).most_common(1)[0][0]
    binary = "malicious"
else:
    y = 0
    behavior = "BENIGN" if all(lbl == "BENIGN" for lbl in flow_labels) else Counter(flow_labels).most_common(1)[0][0]