RandomLSB 输出流，使用密码学种子驱动的伪随机序列散布嵌入位， 抵抗针对顺序 LSB 的卡方统计攻击。
| 10 | |
| 11 | |
| 12 | class RandomLSBOutputStream: |
| 13 | """RandomLSB 输出流，使用密码学种子驱动的伪随机序列散布嵌入位， |
| 14 | 抵抗针对顺序 LSB 的卡方统计攻击。""" |
| 15 | |
| 16 | def __init__(self, image: Image.Image, data_length: int, |
| 17 | filename: str, config: LSBConfig, password: str = None): |
| 18 | self.image = image.copy() |
| 19 | self.config = config |
| 20 | self.header = LSBDataHeader(data_length, config.get_max_bits_used_per_channel(), |
| 21 | filename, config) |
| 22 | |
| 23 | self.pixels = np.array(self.image) |
| 24 | self.height, self.width, self.channels = self.pixels.shape |
| 25 | |
| 26 | bits_per_pixel = self.channels * config.get_max_bits_used_per_channel() |
| 27 | total_bits = (len(self.header.to_bytes()) + data_length) * 8 |
| 28 | if (total_bits + bits_per_pixel - 1) // bits_per_pixel > self.width * self.height: |
| 29 | raise ValueError(f"图像太小，无法嵌入 {data_length} 字节的数据") |
| 30 | |
| 31 | seed = CommonUtil.password_hash(password) if password else 0 |
| 32 | total_positions = self.width * self.height * self.channels |
| 33 | # NumPy 实现的 Fisher-Yates 洗牌，比纯 Python list+shuffle 快约 20 倍 |
| 34 | rng = np.random.default_rng(seed % (2 ** 63)) |
| 35 | self.position_sequence = rng.permutation(total_positions) |
| 36 | |
| 37 | self._buffer = bytearray(self.header.to_bytes()) |
| 38 | |
| 39 | def write(self, data: bytes): |
| 40 | self._buffer.extend(data) |
| 41 | |
| 42 | def flush(self): |
| 43 | self._embed(bytes(self._buffer)) |
| 44 | self.image = Image.fromarray(np.clip(self.pixels, 0, 255).astype(np.uint8)) |
| 45 | |
| 46 | def _embed(self, data: bytes): |
| 47 | bits_per_ch = self.config.get_max_bits_used_per_channel() |
| 48 | bits = np.unpackbits(np.frombuffer(data, dtype=np.uint8)) |
| 49 | n = len(bits) |
| 50 | |
| 51 | if bits_per_ch == 1: |
| 52 | positions = self.position_sequence[:n].astype(np.int64) |
| 53 | pixel_indices = positions // self.channels |
| 54 | channel_indices = positions % self.channels |
| 55 | rows = pixel_indices // self.width |
| 56 | cols = pixel_indices % self.width |
| 57 | self.pixels[rows, cols, channel_indices] = ( |
| 58 | (self.pixels[rows, cols, channel_indices].astype(np.int32) & 0xFE) | bits |
| 59 | ).astype(np.uint8) |
| 60 | else: |
| 61 | # 多位模式：第 i 个 bit 写入第 (i // bits_per_ch) 个位置的第 (i % bits_per_ch) 位 |
| 62 | for i, bit in enumerate(bits): |
| 63 | ch_pos = i // bits_per_ch |
| 64 | bit_slot = i % bits_per_ch |
| 65 | pos = int(self.position_sequence[ch_pos]) |
| 66 | pixel_idx = pos // self.channels |
| 67 | channel = pos % self.channels |
| 68 | row = pixel_idx // self.width |
| 69 | col = pixel_idx % self.width |