社交媒体图片分享链的多线索重构
Multi-clue reconstruction of sharing chains for social media images
摘要：
每天共享的多媒体内容的数量，加上最近的伪造技术所达到的真实程度，有可能损害在线信息源的可信度。上传和共享数据的过程往往会阻碍标准的媒体取证分析，因为多次重新共享的步骤会逐渐隐藏过去操纵的痕迹。但与此同时，平台本身引入了新的痕迹，使数字对象的共享历史得以重建，并可能应用于信息流监控和来源识别。在这项工作中，我们提出了一个监督框架，用于重建社交媒体平台上的图像共享链。该系统被构造为回溯块的级联，每个回溯块每次回溯共享链的一个步骤。块被设计为分类器的集合，这些分类器被训练成通过利用描述媒体对象的内容和容器的不同特征表示来彼此独立地分析输入图像。然后通过后期融合策略将各个决策适当地组合。结果突出了采用多个线索的优势，它可以准确地追溯到共享链的三个步骤。
英文摘要：
The amount of multimedia content shared everyday, combined with the level of realism reached by recent fake-generating technologies, threatens to impair the trustworthiness of online information sources. The process of uploading and sharing data tends to hinder standard media forensic analyses, since multiple re-sharing steps progressively hide the traces of past manipulations. At the same time though, new traces are introduced by the platforms themselves, enabling the reconstruction of the sharing history of digital objects, with possible applications in information flow monitoring and source identification. In this work, we propose a supervised framework for the reconstruction of image sharing chains on social media platforms. The system is structured as a cascade of backtracking blocks, each of them tracing back one step of the sharing chain at a time. Blocks are designed as ensembles of classifiers trained to analyse the input image independently from one another by leveraging different feature representations that describe both content and container of the media object. Individual decisions are then properly combined by a late fusion strategy. Results highlight the advantages of employing multiple clues, which allow accurately tracing back up to three steps along the sharing chain.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
