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Optimum forensic and counter-forensic strategies for source identification with training data

机译:使用训练数据进行源识别的最佳法医和反法医策略

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In the attempt to provide a mathematical background to multimedia forensics, we introduce the source identification game with training data. The game models a scenario in which a forensic analyst has to decide whether a test sequence has been drawn from a source X or not. In turn, the adversary takes a sequence generated by a different source a modifies it in such a way to induce a classification error. The source X is known only through one or more training sequences. We derive the asymptotic Nash equilibrium of the game under the assumption that the analyst relies only on first order statistics of the test sequence. A geometric interpretation of the result is given together with a comparison with a similar version of the game with known sources. The comparison between the two versions of the games gives interesting insights into the differences and similarities of the two games.
机译:为了为多媒体取证提供数学背景,我们引入了带有训练数据的源识别游戏。该游戏对场景进行建模,在该场景中,法证分析师必须决定是否从源X绘制了测试序列。反过来,对手采用由不同来源生成的序列,并以引起分类错误的方式对其进行修改。仅通过一个或多个训练序列知道源X。我们假设分析人员仅依赖于测试序列的一阶统计量,从而得出了游戏的渐近Nash平衡。给出结果的几何解释,并与已知来源的类似版本的游戏进行比较。两种游戏版本之间的比较为两种游戏的异同提供了有趣的见解。

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