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

机译:具有培训数据的源识别的最佳取证和反务策略

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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:在尝试向多媒体取证提供数学背景,我们介绍了源识别游戏的训练数据。游戏模拟了一种情况,其中法医分析师必须决定是否从源x中绘制了测试序列。反过来,对手采用不同的源A产生的序列以诱导分类误差的方式修改。源X仅通过一个或多个训练序列已知。我们在假设分析师仅依赖于测试序列的第一阶统计数据时获得了游戏的渐近纳什均衡。结果的几何解释与与具有已知源的游戏类似版本的比较给出。两个版本的游戏之间的比较为两场比赛的差异和相似性提供了有趣的见解。

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