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REASONING ABOUT EVIDENCE USING BAYESIAN NETWORKS

机译:使用贝叶斯网络对证据进行推理

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There is an escalating perception in some quarters that the conclusions drawn from digital evidence are the subjective views of individuals and have limited scientific justification. This paper attempts to address this problem by presenting a formal model for reasoning about digital evidence. A Bayesian network is used to quantify the evidential strengths of hypotheses and, thus, enhance the reliability and traceability of the results produced by digital forensic investigations. The validity of the model is tested using a real court case. The test uses objective probability assignments obtained by aggregating the responses of experienced law enforcement agents and analysts. The results confirmed the guilty verdict in the court case with a probability value of 92.7%.
机译:在某些方面,人们逐渐意识到,从数字证据中得出的结论是个人的主观观点,并且科学依据有限。本文试图通过提出用于数字证据推理的正式模型来解决这个问题。贝叶斯网络用于量化假设的证据强度,从而增强数字法医调查结果的可靠性和可追溯性。该模型的有效性是通过实际案件进行测试的。该测试使用通过汇总经验丰富的执法人员和分析人员的响应而获得的客观概率分配。结果证实了此案的有罪判决,概率值为92.7%。

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