用隐写技术追踪生成内容的来源,让虚假信息也能追根溯源。
On the Origin of Synthetic Information by Means of Steganographic Inheritance

- 通过隐写编码将生成内容的血统特征悄悄嵌入后代中。
- 在多种修改和处理下仍能准确识别来源,正确率超90%。
- 适合需要内容可信度的AI生成场景,如新闻、艺术创作。
物种起源是自然科学中的终极谜题。类比地,合成信息的起源,我们认为是信息科学中的终极谜题。这一问题蕴含道德重量,技术解释无法完全解决,也不能忽视其对真实、信任与人类智力的影响。人工智能的强大使合成信息的演化谱系越来越难追溯,因为足够强大的模型生成的后代可能在结构或信号层面与父源几乎无关。如同遗传学中表型相似而基因型不同,我们提出一种基于隐写的类遗传机制:在生成后代时,投影器从父源提取特征,隐写编码器将其不可见地嵌入后代。该特征在数字生态系统中持续存在。当查询来源时,解码器从后代提取特征,并与候选父源库对比,从而提名最可能的源头。理论分析表明谱系准确性依赖于投影器与隐写系统属性;实证评估在多个投影器与隐写系统上验证了该方法在广泛处理操作与语义修改下的可行性。我们设想一个数字生态系统,合成信息携带隐藏但可追踪的血统特征,从简单起点演化出无穷形态。
原文摘要 · Abstract (English)
The origin of species has been the mystery of mysteries in natural science. By analogy, the origin of synthetic information, we suggest, is the mystery of mysteries in information science. The question carries a moral weight that a technical account can neither fully resolve nor responsibly ignore, as its impact on truth, trust, and human intellect extends deep into the broader economy and society. The very power of artificial intelligence makes the evolutionary lineage of synthetic information grow ever harder to trace, for a sufficiently capable model may generate offspring that bear little resemblance, at either the structural or signal level, to the parent source from which they were derived. As in genetics, two individuals may share the same phenotype mirroring each other in outward appearance, yet differ fundamentally in their genotype. We propose, by means of steganography, a mechanism analogous to heredity. At the moment an offspring is reproduced, a projector derives a trait from the parent, and a steganographic encoder invisibly hides it within the offspring. This trait persists throughout the offspring's life cycle in a cyber ecosystem. When parentage is queried, a steganographic decoder extracts the trait from the offspring and compares it against the traits of candidate parents in a reference pool, thereby nominating the most likely one. A theoretical analysis characterises phylogenetic accuracy as a function of projector and stegosystem properties, whilst empirical evaluations across multiple projectors and stegosystems demonstrate the viability of the proposed methodology under a broad spectrum of processing operations and semantic modifications. We envision a cyber ecosystem in which synthetic information, endowed with hidden yet traceable lineage traits, branches from a simple beginning into endless forms that have been, and are being, evolved.
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